Dr. (Prof.) T.S. Somashekar is the Director, Centre for Competition and Regulation, NLSIU I. Background An inescapable part of our lives is the way AI influences daily activities, directly or indirectly, in incredibly diverse ways, with enormous implications for productivity across sectors and for direct consumer benefit. The pace of technological evolution is rapid in this segment, and tech firms are quickly adjusting their strategies to retain or enhance their market power. Regulators, in turn, have approached these developments from both an ex ante and ex post perspective. Horizontal ‘relationships’/dependencies and vertical integration in the AI ecosystem can increase the potential for downstream anticompetitive effects. Such ‘relationships’ would traditionally be investigated through merger dynamics testing to assess potential unilateral and coordinated effects that enhance market power. Awake to this fact, big tech companies, predominantly Hyperscale’s (massive cloud computing firms with large networks of data centres), with their large proprietary data and compute resources, resorted to novel methods of horizontal ‘partnerships’ with Foundation Models (FMs), termed ‘reverse acquihires’.[1] FMs are algorithms trained in massive and diverse unstructured data sets and serve as the ‘foundation’ for multiple tasks, unlike traditional ‘Narrow AI’ which are specialised, focusing on individual tasks such as credit card fraud detection or a stock price predictor and so on. By nature, they require massive capex funding for compute power, data to train and deploy models and other infrastructure, including cooling. This creates bottlenecks, as very few firms are capable of providing FM developers with the funding and complementary inputs they need. Proprietary data, so essential for training and deployment/inference, is dominated by the large tech Hyperscale’s, such as Microsoft Azure, Amazon Web Services and Google Cloud Computing, the compute/accelerator layer is dominated by Nvidia’s GPUs with a few fringe players (AMD’s Instinct series) and relatively a few more players in the ASICs segment (used for the specialized inference stage) such as Google TPU — and distribution, through ‘operating systems’ and office suites, again by the same firms that dominate proprietary data. The fabrication of chips/semiconductors itself is concentrated with TSMC in Taiwan, with concerns of high geopolitical risk. Recognising the need to be fleet-footed, regulators across countries have undertaken studies and investigations related to potential horizontal (cartelisation – hub and spoke coordination), vertical (exclusionary) anticompetitive issues, relationship/agreements between complementary input providers, hyperscalers and FMs, and potential ‘killer acquisition’ situations.[2] The CMA paper highlighted certain potential concerns arising out of the agreements between Hyperscalers and FMs: restriction of choice of FMs in downstream markets; restricting access to FMs to prevent competition for themselves and entrenching the position of existing players. Similar concerns have been raised by the US FTC, i.e., restriction of access to inputs to non-partner AI developers; creation of switching costs for the partner FM and AI firms, etc. The Microsoft/Inflection agreement, an example of ‘reverse acquihire’ and ‘killer acquisition ’, was recognised as a merger but was cleared by the UK CMA and the EU as it did not have potential unilateral effects. A similar investigation into the agreement between Alphabet Inc and Anthropic PBC, which involved the acquisition of non-voting shares of Alphabet and non-exclusive compute and distribution agreements, was green-lit by the CMA as it did not amount to ‘material’ influence – a lower threshold. These clearances have adapted to the strategic barriers that such agreements may create, but have not escaped criticism for under-enforcement. Hyperscalers have preferential access to these AI models, to the detriment of smaller competitors in the downstream market, and can use their ‘relationship’ to cement users in their wider product/service ‘ecosystems’ (tying and bundling), thereby allowing for higher pricing. Regulators have responded by revisiting their thresholds and expanding their investigations into ecosystem practices to reduce such possibilities. Some of these concerns, along with the ecosystem structure, are briefly encapsulated in Figure 1. Figure 1: The FM/AI Ecosystem and the Vertical Stack Layer 5 - Applications ChatGPT, Claude.ai, Copilot, Gemini, Perplexity, Enterprise SaaS, AI agents Competition concern: self-preferencing via vertical integration, bundling with OS, browser and office suites Layer 4 – Foundation Models OpenAI, Anthropic, Google DeepMind, Meta (Llama), Mistral, xAI Competition concern: API dependency with closed FM models (the first three), switching costs, hyperscaler investment, control over FMs Layer 3 – Cloud and compute infrastructure AWS, Microsoft Azure, Google Cloud, Oracle Cloud, CoreWeave Competition concern: compute gatekeeping, exclusive partnerships with FMs built in with ‘agreements’ funding infrastructure, pricing discrimination Layer 2 – Chip design Nvidia (dominant), with fringe players AMD, Intel, Google TPU, AWS Trainium, Meta MTIA. AMD competes directly with Nvidia in the Data Center CPU/GPU/DPU’s, with Intel a distant third. Competition concern: Nvidia market power; hyperscaler vertical integration into custom silicon LAYER 1 - SEMICONDUCTOR FABRICATION TSMC (dominant), Samsung, Intel Foundry This article seeks to provide a quick perspective of the evolving competition law concerns surrounding AI FMs – more specifically the dependency (strategic agreements) of (between) FM firms on (and) Hyperscalers and the degree of competition in this limited ‘market for inference’. Defining the relevant market as such is bound to attract much challenge and effort for a competition agency, and some may argue for an ‘ecosystem’ definition as a better approach. An alternative would be to have an ex ante regulatory framework. India’s proposed Digital Competition Law Bill, however, continues to languish. Understanding the degree of competition between FMs and the downstream consequences requires a look at both structural and behavioural factors, which are examined below. This essentially is a part of a Section 4 analysis, as it focuses on the ability of FMs to act independently of competitive forces using both the benefits of a first mover as well as ecosystem advantages. Market power is sought to be gauged using structural and strategic barriers to entry and its reward in terms of higher market share and pricing power. II. Foundation Models and the Structural Barriers Examining structural factors such as capex and trends in innovation and entry provides a good understanding of barriers and the nature of competition ‘within’ and ‘for’ the market. Of course, sunk costs cannot be ignored. Large capex requirements, expected to touch $ 900 billion this year, create large economies of scale, yet low marginal cost in end-stream deployment for FMs. They also enjoy large economies of scope, as it is more efficient to build and train one foundation model that can then be deployed for multiple AI tasks downstream rather than train a model on one specialised task. Recovery of such large capital costs will need sufficiently high market shares and prices, both of which will require adequate market power, tempting the use of anticompetitive mechanisms and/or a race typical of platforms ( low or zero pricing), which will only see some earn adequate returns on investment, forcing exit and causing entry barriers. Strategic ties with Hyperscalers can make a critical difference to achieve this end, and such relationships need not just reflect dependence. These factors, along with feedback loops, create additional strategic barriers and reduce contestability and the natural tendency for high concentration. But drawing conclusions about first-mover advantage for early FMs will need to account for innovation and switching costs, which can have consequences for entry. Before we proceed, a quick understanding of the categories of FM versions (based on OSAID) will be useful: 1. Closed AI – access only through API (weights, training data and source code not available) includes OpenAI's GPT-4o, Anthropic's Claude versions, Google's Gemini Ultra; 2. Open models (all three available but subject to restrictions) ; 3. Open-weights(only weights are fully downloadable, with restrictions on others) include Meta's Llama series, Mistral AI models, Google's Gemma; 4. Open-source AI (all available freely) includes OLMO, Amber, etc. These categories, and the open-closed binary used in the charts that follow, are necessary simplifications. Scoring eleven leading models across eighteen legal, economic and governance variables, Schrepel and Potts find that most cluster in the middle of the openness spectrum - Llama 3 (open weight) and GPT-4 differ by a mere two points out of thirty-six - and caution against treating openness as binary (Schrepel and Potts, 2025). If models labelled open are only partially open, the restraint they exert on closed-model pricing will be weaker than their number suggests and strategic complementary and vertical relationships/integration can play a significant role. Analysing Entry and Innovation: Entry data allows us to understand the extent of barriers to entry and competition in the market. The larger the number of new firm entrants, the greater the degree of competition. Chart 1 presents a time series frequency chart of the progression of FMs (compute ≥10^23) quarterly since 2019 Q4. This data is sourced from Epoch AI (the “known and unconfirmed compute-intensive models” large-scale subset) and has a different categorisation than the above four, which are collapsed to two (Open weight includes OSAID categories 2-4), and Closed relates to OSAID category – 1. Epoch AI categorises models with training compute ≥10²³ FLOP as ‘large-scale’ models — closely related to FMs, and to the General-Purpose AI (GPAI) models of the, which are presumed to carry systemic risk at ≥10^25 FLOP. Charts 1–4 report two definitions together: (A) models with confirmed, disclosed training compute ≥10²³ FLOP (318 models); and (B) additionally, models Epoch identifies as compute-intensive, but whose compute is undisclosed (526 models in total, from 138 developers). Closed-weight labs rarely disclose compute, so (A) can undercount closed models. We can broadly divide the trend into three periods: 1. Early phase - Domination by a few big tech companies (2019 Q4 – 2022 Q1) - namely, OpenAI, Google, Meta, DeepMind, presumably due to capex and compute barriers; 2. Expansion & Entrant Explosion phase (2022 Q2 – 2023 Q4) - New entrants aided by venture capital and an explosion of ‘open source’ models; 3. Maturation & Incumbent Model Velocity phase (2024–2026) – a normalisation in the growth rate dominated by the top few. Charts 2 to 4 show who releases these models and under what access terms. This shows a significant number of new entrants and the release of new models, indicating dynamic competition. That the number of ‘open weight’ FMs has exploded should ideally act as a competitive restraint on closed models and hence pricing, but as noted above, they are not really so ‘open’. But we also see signs of the market settling down with new entrants decreasing sharply. Along with other structural barriers, feedback loops among the consolidated players can make it more difficult for a native Indian FM entrant. Explanatory note: Bars (left axis) count firms reaching ≥10²³-FLOP scale for the first time each quarter — dark blue= entry with a disclosed-compute model (definition A), light blue = entry via a compute-intensive model whose FLOP is unconfirmed (definition B); the line (right axis) is the cumulative frequency of distinct firms, reaching 138 by 2026 Q3. Entry accelerates sharply from 2023, but a rising firm count overstates rivalry: reaching ≥10²³ once is not sustaining frontier output, and many entrants release a single model. Source: Epoch AI, Data on AI Models (large-scale subset), retrieved 20 Aug 2026. Explanatory note: Quarterly large-scale releases split by whether the developer was a first-time entrant that quarter (orange) or an incumbent already at scale (blue). Incumbents account for 350 of 526 releases and their share grows over 2024–2026: the innovation frontier is being advanced mainly by established labs iterating, not by new entry. Counts use the inclusive population (B). Source: Epoch AI, as Chart 1. Explanatory note: Releases are split by open vs closed weights and, within each, confirmed ≥10²³ (solid) vs unconfirmed compute-intensive (pale). Among the confirmed (A), open dominates — 224 open vs 93 closed; but closed frontier models sit overwhelmingly in the unconfirmed category (156 of 249 closed) because closed labs rarely disclose compute. It’s only in the inclusive view (B) the totals are nearly even — 254 open vs 249 closed. ‘Open dominance’ by release count is thus substantially a disclosure number, and says nothing about capability, usage or revenue. 23 models with undetermined accessibility are excluded. Source: Epoch AI, as Chart 1. Explanatory note: The fifteen developers with the most large-scale models (inclusive definition B) are categorised by open-weight vs closed / API / unreleased. Open-weight output is led by Alibaba, Meta AI, NVIDIA and DeepSeek; closed output by OpenAI, Anthropic, Google DeepMind and Amazon — a very striking firm-specific split. Source: Epoch AI, as Chart 1. Of concern are the deal records. Tracking of AI-related investments, alliances and acquisitions shows activity rising from just a couple in 2022 to 68 in 2025 and 61 in the first seven-and-a-half months of 2026 alone (Chart 5). Agreements related to infrastructure deals - compute capacity, data centres, and increasingly the physical layer beneath them- rose from about a quarter of tracked deals in 2025 to a clear majority in 2026 (Chart 6). These deals now go beyond compute and data-centre capacity to dedicated power generation (including gas and small-modular-nuclear supply), liquid cooling, copper and electrical conductors, and optical interconnects. This is the same vertical stack set out in Figure 1, now being secured through contract and acquisition. For a prospective entrant - including an Indian FM developer - the barrier is therefore not only the headline capex but that the complementary inputs at each layer are being locked up by incumbents that already control the layers above, a barrier that is both structural and strategic. Explanatory note: Deal counts by year using Mogin’s own category labels (‘Infrastructure / Materials’ merged into Infrastructure). Source: Mogin Law A.I. Deal Table (moginlawllp.com/mogin-law-ai-deal-table), retrieved 20 Aug 2026; Year 2019 only partially complete in the source. Explanatory note: The Mogin Law A.I. Deal Table is a non-exhaustive list. Deal values are frequently undisclosed and some entries are reported or unconfirmed. It is used here for the direction and composition of deal-making, not precise totals. Because many values are undisclosed and a few mega-deals would dominate any monetary aggregate, Charts 5–6 use deal counts rather than summed values. Source: Mogin Law A.I. Deal Table, retrieved 20 Aug 2026. III. Behavioural Factors In behavioural factors, pricing and market share trends are considered. They both serve as a reasonable indicator of market power. While the entry data indicate a competitive market in terms of availability of demand-side substitutes, the number of players need not indicate adequate competitive restraints. To start our discussion, while FMs will need to generate revenue to recoup the large capex, current financials seem to paint a different picture. Revenues generated from AI-based services are approximated at $220 billion but, while growing fast, have proven insufficient to justify the capex expected to touch $900 billion this year. Currently, the ability of consumers to switch between priced and alternate-priced models and free FMs - as the entry of multiple players enhances demand-side substitutability, firm strategies aimed at poaching each other’s clients in a zero-sum game, and slower expansion in width and depth of AI usage all contribute to both revenue growth dampening and increasing within-market competitive restraints. But while this gap is not in itself evidence of monopoly rents today, this large spending far ahead of revenue may actually sharpen the concentration concern. The higher the capital hurdle relative to current revenue, the fewer the firms that can clear it without Hyperscaler funding, and the stronger the incentive to defend margins through pricing and contractual lock-in once scale is reached. This may also explain the rapid slowdown in new entry seen earlier. The following charts provide market share and pricing dynamics which can help provide a deeper perspective. Data is sourced from OpenRouter, which captures only the routed-API segment it represents. Market share trends (Chart 7) reveal that the market is clearly concentrated among a few firms; when revenue is used as the metric, even more so than suggested by the entry data. Going by this data, and reading it only as the routed-API segment it represents, market share trends (Chart 7) reveal that the market is clearly concentrated amongst a few firms; when revenue is taken as the metric, even more tightly than suggested by the entry data. Source: OpenRouter, retrieved August 2026. OpenRouter captures developer/API-routing traffic only — it excludes first-party app and direct-enterprise usage (ChatGPT, Claude.ai, the Gemini app), so it over-represents open and switchable models and cannot be read as whole-market share. If anything, the bias runs against the finding: since the sample over-represents open and switchable models, revenue concentration in the wider market is likely to be higher, not lower. Market share trends over time are a better reflection of competitiveness. Chart 8, sourced from OpenRouter, is three images merged to reflect the dates and colour codes read off a dynamic source chart, so there may be slight image adjustments, but the numbers match the source perfectly. To be noted – this is the market share of the same firms as LLM’s – in the area of text generation – and hence these figures must only be seen as a proxy (the "LLM" layer of the FM stack). Also, as noted earlier, OpenRouter data captures adoption rather than model quality, covers only traffic routed through OpenRouter — not the whole market and not usage on a provider's own first-party API. Given the nature of an API router, it therefore over-represents open-weight and readily switchable models relative to closed frontier models whose volume flows largely through their own APIs Chart 8 : Changing token market shares - August 2025 to August 2026 The numbers indicate a shift from a Google-dominated market in 2025 toward a much more competitive and fragmented market in 2026, with DeepSeek making the largest gain. While this data is subject to OpenRouter’s traffic, the trends are telling - market shares are not stagnant, reflecting the earlier entry and innovation statistics. But Chart 9 provides pricing distribution, which shows a big asymmetry between closed- and open-source FMs. Pricing is as much a function of costs, which have fallen steeply, as of market power. Epoch AI finds that the cost of reaching a fixed performance milestone has fallen by roughly 9x to 900x per year depending on the task, with the sharpest declines most recent. While this can explain price declines, it cannot account for the large asymmetry. Can qualitative factors provide an explanation – are we seeing a differentiated price -quality spread? On Epoch AI’s Capabilities Index (ECI), the most capable open-weight models have lagged frontier closed models by an average of only about four months (roughly 8 ECI points) since January 2026, and Chinese models have trailed the US frontier by an average of seven months since 2023.[3] So a quality lead measured in months cannot on its own account for a price difference of this order; the explanation has to be found elsewhere. Part of it is ordinary price discrimination. Second-degree discrimination is visible in the tariff itself - output tokens are priced several times above input tokens, commonly four to eight times among the frontier closed models, reflecting the greater compute that generation consumes, while tiered versions of the same model invite users to self-select. Third-degree discrimination operates across segments: the leading firms, particularly Anthropic, concentrating on enterprise, coding and agentic workloads where willingness to pay is highest; published prices among closed models of the same vintage differ by as much as twelve times, while measured quality differs by a few percentage points (Value Add VC, June 2026). Further, list prices are also not realised prices – several other usage factors can affect costs. Once these are allowed for a residual remains, and it tracks vertical integration. Closed US FMs are embedded in the service offerings of their Hyperscaler partners - Word, Excel and PowerPoint through Microsoft Copilot, and Workspace through Gemini - which delivers deeper workflow integration, enterprise security and support commitments, and therefore better client response and satisfaction. This is an advantage that Chinese open-weight models cannot presently offer, whatever their benchmark scores, and geopolitical alignment reinforces the pairing of US FMs with US Hyperscalers.[4] From a competition perspective, it means the price asymmetry in Chart 9 should be read as evidence of switching costs and vertical integration rather than of model quality alone - which strengthens the strategic barrier and dependence concern developed earlier. Two points to be noted – Epoch mentions that closed labs may keep their most capable models unreleased, so the true quality gap could be wider, and the ECI measures capability ceilings rather than reliability in deployment. Explanatory note. Source - Layer3Labs pricing index[5]: Open-weight models cluster at $0.10–$0.30 per million tokens (Mistral Large 2 the outlier at $2/$6); i closed models at $1.25–$15.00. Anthropic’s Opus tier ($25 output) is excluded as it would compress the scale IV. Conclusion On a positive note, we see procompetitive trends in innovation rate and new-entry frequency, with lower pricing points and, on Epoch’s capabilities index, a closed-to-open quality gap now measured in months rather than generations. But while options remain, price pressure may persist among consumers with a lower willingness to pay; enterprise solutions will face cost challenges due to strategic tie-ups. Vertical integration and resulting self-preferencing are factors that the CCI can act against within the existing regulations, and reverse acquihires may be viewed through the ‘material control’ prism provided by The Competition Amendment Act (2024). When examining market power, while acknowledging that open-source can play a critical role in restraining pricing power, behavioural factors, switching costs, and brand trust issues may still confer significant market power on closed-end models, as reflected in price asymmetry. The ecosystem integration: the embedding of closed US FMs in the Hyperscalers’ own productivity suites, and the geopolitical alignment now formalised in initiatives such as Pax Silica and informally held together through threats, together sustain a price premium that the narrowing quality gap alone would not support. Price discrimination, while a normal feature in differentiated markets, can still attract the attention of the CCI when considered along with these potential leveraging lock-ins. Diversification of cloud compute and hardware sources will be critical but is unlikely in the immediate future and will require systematic intervention by regulators to democratise data. But government efforts to finance indigenous FMs and to develop data, data centres and compute will be critical in lowering these entry barriers, even if they cannot dismantle all of them. India’s accession to Pax Silica may ease access to trusted compute and equipment, yet it does not by itself address the deeper dependence mapped in Charts 5 and 6 — the progressive locking-up of every layer of the stack, from data centres down to copper, by the same firms that dominate the layers above. That, rather than the number of models released, is the question CCI and other regulators in India will have to confront. From an ex-ante perspective, the Digital Competition Bill, still unenacted, may be better placed to tackle these issues. Hyperscalers would be categorised as Systemically Significant Digital Enterprises, and the clause related to the Associate Digital Enterprise mechanism can pre-empt self-preferencing, tying and restrictive data use to a group entity such as an FM arm that benefits from data collected through that service. These obligations are based on status and hence do not touch merger review. Foundation models could be listed as Core Digital Services. It is encouraging that the Standing Committee on Finance is pressing for finalisation of the Bill. Notes: [1] The term ‘horizontal’ partnerships is used not from a collusion perspective but rather to illustrate the relationship between data / infrastructure and algorithm developing AI firms which are all needed to deliver FMs. Wong discusses how such talent hires can still be termed as ‘asset’ acquisitions and be subject to Section 7 of the Clayton Act which oversees mergers and acquisitions. Such agreements now span critical infrastructure such as power and cooling. See Mogin Law ‘From Data Centre’s to Copper: AI Infrastructure Race Goes Deeper’, available at https://moginlawllp.com/from-data-centers-to-copper-ai-infrastructure-race-goes-deeper/ [2] See Market study on Artificial Intelligence and Competition, CCI, Available at: https://www.cci.gov.in/economics-research/market-studies/details/47/0; UK CMA, ‘AI Foundation Models: update paper’ , 11 April 2024, Available at https://www.gov.uk/government/publications/ai-foundation-models-update-paper ; US FTC, FTC Issues Staff Report on AI Partnerships & Investments Study, January 17, 2025 https://www.ftc.gov/news-events/news/press-releases/2025/01/ftc-issues-staff-report-ai-partnerships-investments-study; European Commission, Commission takes note of the withdrawal of referral requests by Member States concerning the acquisition of certain assets of Inflection by Microsoft , 18 September 2024 [3] Jack Edwards and Luke Emberson, ‘Open models lag state-of-the-art closed models by 4 months’, Epoch AI Data Insight, 2026, https://epoch.ai/data-insights/open-closed-eci-gap; Epoch AI Data Insight, 2026, https://epoch.ai/data-insights/us-vs-china-eci; The Epoch Capabilities Index (ECI) is Epoch’s aggregate measure of model capability. [4] Pax Silica is a US State Department initiative declared in December 2025 to coordinate ‘trusted’ supply chains spanning critical minerals, energy, advanced manufacturing, semiconductors, AI infrastructure and logistics. Founding signatories included the United States, Japan, South Korea, Singapore, the Netherlands, the United Kingdom, Israel, the United Arab Emirates and Australia; membership had expanded to around two dozen partners, including India and the European Union, by the June 2026 summit. See https://www.state.gov/pax-silica. [5] Layer3Labs, ‘AI Model Pricing Compared: Cost Per Token’ (verified 28 July 2026); each row source-linked to the vendor’s official pricing page. https://www.layer3labs.io/ai-model-pricing

Manas Kumar Chaudhuri is a Senior Partner at Khaitan & Co LLP. The evolution of competition law in India (the Competition Act, or the Act) has been slow, and at times surprising, even now — despite the Act having come into being in early 2003. The reasons for the slower development of the jurisprudence are briefly summarised below. As soon as the Act received the assent of the President of India, a writ petition was filed by a private litigant against the composition and structure of the agency. The petition was disposed of by the Supreme Court of India with an express observation that, since the intent of the Act is a combination of adjudication and regulation, the Competition Commission of India (CCI) may have at least two benches — one assigned adjudicatory functions and the other regulatory functions. The Court also observed that a specialised court of first appeal should be set up between the CCI and the Supreme Court, and that the advisory and inquisitorial roles of the CCI would continue to form part of its core functions. On these observations, the Government proposed a short amendment. Several matters, however — neither part of the Court’s observations nor contended by the petitioner — were nonetheless inserted into the Amendment Bill. One notable instance was the removal of benches from the structure of the CCI, with the consequence that the presence of a judicial member became optional, if not redundant. The voluntary regime of merger control was changed to a compulsory one, and the office of the Registrar was converted into an administrative office of the Secretary, CCI. A comprehensive amendment was finally notified that travelled well beyond the core challenges of the petitioner and the final observations of the Court. The Act was then notified in respect of the CCI. In the first phase, the CCI and the Court of First Appeal had full strength, but implementation began cautiously. One core reason was the legacy of the repealed law and the fate of parties affected by the transition, as undecided cases were transferred either to the COMPAT or to the CCI. Amidst that uncertainty, the regulation of combinations was notified, and the CCI became fully functional. Numerous amendments — through the route of public welfare or through statutory regulations — were made on a regular basis. Despite these, the fixed tenures of the Members of the CCI and the COMPAT, and the frequent repatriation of senior functionaries of the CCI and the office of the Director General (the DG) to their parent cadres, produced a recurring loss of institutional memory. The CCI nonetheless stood distinct from its predecessor in a few salient respects. The Supreme Court had been the only appellate authority under the previous regime; the new regime interposes an appellate tribunal. The earlier law could impose no penalty for breach by enterprises or individuals; the present law may remedy breaches with penalties on both. Yet, from publicly available sources, the recovery of penalties over more than seventeen years of the Act’s enforcement does not present a very encouraging picture. Beyond the amendments to the Act and the Regulations, the enforcing and investigating authorities were besieged by constitutional writs almost as a matter of routine. Tellingly, those writs in the major High Courts rarely alleged any breach of the Act itself; they turned almost entirely on due process and the principles of natural justice — a pattern that signalled that more comprehensive amendment was inevitable. In the wake of these bottlenecks, and the emergence of new-age enterprises, the Government constituted a Competition Law Review Committee (CLRC) with representation from all conceivable stakeholders. Its recommendations introduced several new features into the Act, of which the salient ones are: – Hub-and-spoke cartels – Leniency-plus – Commitments and settlements – Deal-value thresholds – The appointing authority for the office of the DG changed from the Union of India to the CCI – Power for the Commission to enter into a memorandum of understanding with other statutory authorities – A limitation period of three years in prohibitor antitrust cases, from the date the cause of action arose – Closure orders made appealable – The merger-control waiting period reduced – Computation of penalties on the basis of global turnover (s. 27(b), explanation) – Appeals maintainable only on an upfront deposit of 25% of the penalty (s. 53B, proviso) A brief word on the intent of some of these amendments follows. Hub and Spoke Though a market-structure concept developed over time between upstream and downstream enterprises, and not always a concern for the authorities, a hub-and-spoke arrangement can pose serious difficulty in the absence of an enabling provision. The want of one limited the CCI’s ability to remedy distortion in several sectors — alcoholic beverages, pharmaceuticals and traditional oligopolies among them. Trade associations and digital intermediaries — the typical hubs — though penalised regularly, often escaped with negligible or no penalty owing to their low financial corpus, so that the remedy was non-deterrent while keeping the CCI occupied with wasteful activity and higher litigation costs. The position is expected to improve. Commitments and Settlements The purpose of these provisions is to shorten litigation. Since leniency and leniency-plus already form part of the Act for cartels and bid-rigging, the legislature adopted broadly similar remedies — arising from the voluntary action of the respondent — for the exclusionary or exploitative conduct of dominant enterprises. The Act affords no right of appeal to the party benefiting from early closure, but neither does it protect that party from follow-on actions and damages claims by other private parties. Limitation Period A logical addition, consonant with the evolution of the enforcement of antitrust cases. Despite the many roadblocks, some landmark decisions of the Supreme Court — and one significant closure by the Commission — offer a measure of hope. The Leading Decisions Excel Crop Care Ltd v. CCI. The penalty for a breach by a multi-product company is to be computed only on the turnover, or profit as the case may be, of the product forming the cause of action. The doctrine of “relevant turnover,” grounded in proportionality and the purposive interpretation of the statute, thus emerged for the computation of penalties. Rajasthan Cylinders and Containers Ltd v. Union of India. Where, in an allegation of bid-rigging, the buyer — exercising countervailing buying power — unilaterally settles the final bid price by negotiation, the price so fixed through monopsony behaviour displaces the inference of collusion on price initially suggested by the suppliers. CCI v. Schott Glass India Pvt. Ltd. Hitherto, the law on abuse of dominance had not developed the principles of theories of harm, objective justification and economic rationale, notwithstanding that the Act rests on the rule of law and natural justice. This decision settled those principles for the first time in a final appeal. Holding in Civil Appeal No(s). 5843/2014 that volume-based rebates are not automatically anti-competitive where applied uniformly across similarly situated buyers and supported by an objective rationale, the Court emphasised the need for an effects-based analysis — requiring both actual or likely anticompetitive effects and the absence of objective justification before conduct is condemned. Amazon.com NV Investment Holdings LLC v. CCI. A classic instance of a non-adversarial merger clearance that became a keenly contested adversarial proceeding. The acquirer, having obtained unconditional approval, faced contentious litigation more than two years later when the Commission reopened the order and initiated proceedings for gun-jumping and suppression of material facts. The Supreme Court set aside the NCLAT judgment — which had arisen from two distinct orders of the Commission, one non-adversarial and the other adversarial — finding untenable facts and a misapplication of law in the order impugned. Kailash Gupta v. AIOCDA & Ors. is a good example of how a fourteen-year-old matter loses relevance beyond a reasonable period. The alleged conduct predated 2011, and the DG relied on evidence of that vintage; when the matter came on for final hearing in 2026, the Commission closed it as too dated to pursue. Conclusion The genesis of the Act lies in the early years of India’s economic liberalisation. In October 1999 the Government constituted a high-level panel — the Raghavan Committee — to consider whether the predecessor regime, the Monopolies and Restrictive Trade Practices Act and the Commission under it, should continue or be replaced. Among its tasks was to examine India’s shift from controlling monopolies to fostering fair market competition. The Committee advised, among other things, that competition law should apply to both private and government monopolies within a single framework to ensure competitive neutrality. As the predecessor regime rested on “deemed illegal” provisions, the Committee recommended an industry-friendly regime built on the rule of reason. These aspirations are not yet fully realised, and the evolution of the law remains a work in progress. Those of us associated with it from the beginning nonetheless expect the authorities to apply the law in letter and spirit, with objective justification. A better harmony between the sole authority and its stakeholders can secure greater consumer surplus and benefit; minimising unnecessary litigation must be an integral part of that journey. Views are personal.

Prof. Alberto Heimler is a Retired Professor of Economic Regulation, National School of Government, Rome Over the past decade, a handful of digital platforms have come to play an extraordinary role in our economic and social lives. Google shapes how we search for information, Apple controls major mobile ecosystems, Amazon has transformed retail, and Meta’s platforms have become essential tools of communication for billions of people. Their success has brought enormous benefits. Digital platforms have reduced transaction costs, facilitated innovation, and created entirely new markets. At the same time, their growing economic power has raised concerns among policymakers worldwide. Can competition survive in markets dominated by a few digital gatekeepers? Are smaller businesses treated fairly when they depend on large platforms to reach customers? And how can regulation encourage innovation without stifling it? Europe has attempted to answer these questions through the Digital Markets Act (DMA), one of the most ambitious efforts anywhere in the world to regulate Big Tech. India is today one of the world’s largest and fastest-growing digital economies. As policymakers debate whether special rules are needed for large digital platforms, the European Union’s regulation offers valuable lessons — not only on the benefits it provides, but also on its potential risks. The European Experience The DMA, adopted in 2022 and applicable from May 2023, represents a major shift in regulatory philosophy. Traditionally, competition authorities intervene only after anti-competitive behaviour has been identified and investigated. Such investigations are often lengthy and complex, particularly in digital markets where technology evolves rapidly. The European Union concluded that waiting for antitrust cases to run their course was no longer sufficient, and introduced an ex ante framework imposing obligations on large digital platforms before harmful conduct occurs. The DMA identifies certain companies as “gatekeepers” where they play a particularly important role in connecting businesses and consumers and possess durable market power — firms operating search engines, app stores, social networks, operating systems, online marketplaces and cloud services. Once designated, they are subject to numerous obligations: to allow users to uninstall pre-installed applications, permit interoperability with competing services, facilitate data portability, avoid self-preferencing their own products, and refrain from combining personal data across services without user consent. The underlying objective is clear: to make digital markets more contestable and fair. Why the DMA Matters Beyond Scope Although the DMA is a European regulation, its significance extends far beyond the Union. India, like many other countries, faces similar challenges: large platforms increasingly serve as essential gateways, and millions of Indian firms rely on online marketplaces, app stores and digital advertising to reach customers. The European experience is therefore instructive. First, the DMA recognises that digital markets possess characteristics that distinguish them from traditional industries — strong network effects, economies of scale and the importance of data may entrench certain platforms very rapidly. Second, it highlights the difficulty of relying exclusively on traditional competition law, since antitrust investigations often take many years, by which time market structures may already have changed irreversibly. Both concerns are highly relevant in India, where digital markets are expanding at remarkable speed. The Risks of Overregulation At the same time, Europe’s approach raises important questions. Many DMA obligations are derived from previous antitrust cases; yet under competition law, practices are normally assessed case by case, taking account of their actual effects and possible efficiency justifications. The DMA instead applies broad obligations automatically to all designated gatekeepers, and this rigidity may create problems. Digital markets are characterised by constant innovation and considerable uncertainty. Practices that appear exclusionary in one context may generate significant efficiencies in another: self-preferencing, bundling or restrictions on interoperability may sometimes benefit consumers by improving quality, security or innovation incentives. A central concern is that excessive regulation could weaken incentives to innovate — large profits are not necessarily evidence of market failure and are often precisely what encourage firms to invest in risky, costly innovation. The economic objective of competition policy is not to eliminate market power entirely or to achieve perfect competition, but to prevent firms from artificially creating, maintaining or extending market power through anti-competitive conduct. That distinction is crucial. The Challenge of Contestability One principal objective of the DMA is to increase “contestability.” In economic theory, a perfectly contestable market is one in which entry and exit barriers are so low that even a monopolist behaves competitively because of the constant threat of entry. As a theoretical benchmark this is useful; as a practical policy objective it can be problematic. No modern economy seeks to eliminate all monopoly profit — some degree of market power is often necessary to reward innovation and encourage investment — and an excessive emphasis on contestability could unintentionally reduce incentives for technological progress. The challenge is therefore to strike the right balance: promoting competition without undermining the incentives that make innovation possible. What Can India Learn? For India, the European experience offers both inspiration and caution. India’s digital economy is growing rapidly and will increasingly confront issues similar to Europe’s. Policymakers may reasonably conclude that traditional tools are insufficient in certain circumstances and that additional instruments are needed. Any future framework, however, should avoid excessive rigidity: a one-size-fits-all approach may prohibit conduct that is in fact beneficial, and regulation should remain flexible enough to distinguish genuinely anti-competitive practices from strategies that enhance efficiency. Particular attention should be paid to protecting smaller firms that depend heavily on platforms and may be vulnerable to opportunistic conduct; at the same time, regulators should avoid shielding large established competitors merely because they face stronger competition from platforms. India also has an antitrust option that Europe did not fully explore before adopting the DMA: strengthening the Competition Commission of India’s existing enforcement powers rather than layering a new ex ante regime on top of them. The debate over India’s own Digital Competition Bill has already exposed this tension. Momentum behind the Bill slowed through 2025, while parliamentary reviewers concluded that the CCI’s capacity, resources and technical expertise — rather than any absence of legal tools — remain the binding constraint on effective digital-market oversight. If that diagnosis is correct, the priority may be institutional rather than legislative: building the CCI’s technical capacity and procedural speed, rather than adding a parallel ex ante framework whose obligations, as the European experience shows, are not easily calibrated to fast-changing digital markets. Conclusion The Digital Markets Act represents one of the boldest regulatory experiments of our time, and whether it ultimately succeeds remains uncertain. Its importance lies not only in its direct effects on European markets but in the global debate it has triggered about how societies should govern digital platforms. For countries such as India, it provides an invaluable laboratory, demonstrating both the necessity of adapting competition policy to the digital age and the dangers of excessive intervention. The future of digital regulation will depend on finding a delicate equilibrium: ensuring that markets remain open and competitive while preserving the incentives that drive innovation and growth. The early evidence offers some reassurance. In its first review of the DMA, published in 2026,¹ the European Commission concluded that the regulation has already generated positive effects — greater consumer choice, increased opportunities for app developers, improved interoperability and easier switching between services. These developments are encouraging, though it remains too early to judge whether the short-term gains will be accompanied by unintended long-term consequences for investment and innovation. For every jurisdiction, India included, strengthening the effectiveness and speed of antitrust enforcement may ultimately prove the preferable path. Timely competition enforcement remains the best alternative to extensive ex ante regulation, allowing authorities to intervene against genuinely anti-competitive conduct while preserving flexibility and avoiding unnecessary constraints on innovation. NOTES 1. European Commission, “Review highlights Digital Markets Act remains fit for purpose and has positive impact,” press release, 28 April 2026.

Viraj Thakur is a fourth-year student at the National Law School of India University, Bengaluru. The Supreme Court of India (‘SC’) in Competition Commission of India v. Schott Glass India Pvt. Ltd. (“Schott Glass”) analysed whether certain commercial arrangements amounted to an abuse of dominant position (“AoDP”) under §4 of the Competition Act, 2002 (“Act”). Holding that it did not (¶77), the SC observed that a finding of AoDP necessitates an effects-based analysis (¶1). Hard evidence must be used to demonstrate proven harm, balanced against commercial justifications (¶1). The significance of Schott Glass extends beyond the immediate dispute. By holding that proof of abuse under §4 requires evidence of actual or likely anticompetitive effects, the Supreme Court has moved Indian competition law closer to the effects-based approach followed in jurisdictions such as the European Union (“EU”). Yet this raises an important institutional question. If establishing abuse now requires extensive economic and factual evidence, can an ex-post enforcement regime respond quickly enough in fast-moving digital markets? This question assumes particular significance in light of the proposed Digital Competition Bill (“DCB”), which adopts an ex-ante framework for large digital enterprises. Accordingly, this paper asks whether the effects-based approach endorsed in Schott Glass reduces the need for ex-ante regulation or instead strengthens the case for maintaining both frameworks in parallel. To demonstrate this, I first cull out the principles for conducting an effects-based analysis. Second, I argue that requiring such evidence may delay proceedings. Consequently, in the specific case of digital markets, I argue that a delay may lead to harms becoming entrenched in the market. Thus, I suggest that a parallel ex-ante framework should exist to regulate AoDP under §4. Effects-Based Analysis In India §4 of the Act deals with AoDP by an enterprise or group. Unlike Art. 102 to the Treaty for the Functioning of the European Union (“TFEU”), there is no explicit legislative requirement to conduct an effects-based analysis in the Act (CLRC Report, ¶4.1). Perhaps consequently, in some decisions, the Competition Commission of India (“CCI”) has not inquired into whether there was an appreciable adverse effect on competition (“AAEC”). That is, it has presumed an AAEC. For instance, in XYZ v Association of Man-Made Fibre of India, Grasim Industries, the CCI inferred competitive harm from Grasim’s conduct without evidence of actual or likely effects. Mere losses from higher pricing were treated as sufficient to establish a violation of §4 (¶¶112, 124). However, the importance of an effects-based analysis has been noted in specific contexts. For instance, demonstrating “anti-competitive effect/distortion” has been held to be necessary (¶¶ 6.23, 6.37, 6.40) to establish an AoDP via denial of market access under §4(2)(c), in the case of In Re: REC Power Distribution Company Ltd. (“REC Power”). In Alphabet Inc. v CCI (Alphabet Inc.), the National Company Law Appellate Tribunal (‘NCLAT’) held that the test to be employed was whether the abusive conduct led to anti-competitive effects (¶66). These effects include both actual harm and harm likely to be caused (¶49). Moreover, given the sweeping power to order structural remedies under §28 of the Act, the absence of an effects-based analysis risks enabling the CCI to mandate breakups without demonstrated competitive harm (p. 42). Against this backdrop of context-specific reliance on effects, the decision of the SC in Schott Glass marks a doctrinal shift in holding that an effects-based analysis is an obligatory component of every inquiry under §4 of the Act. However, effects-based analysis rarely turns on a single metric, instead demanding a cumulative assessment. The multifactor nature of an effects-based analysis can be seen from the manner in which courts and competition authorities have assessed abuse claims. In Schott Glass, the Supreme Court relied on tonnage and output data showing increased purchases and imports by converters, rising EBITDA margins of independent converters, stable or declining downstream prices, and increases in competitor output and capacity. It also considered qualitative factors such as competitor conduct and the cyclical nature of the industry. In WhatsApp, the CCI examined daily active user data and the revenue advantages arising from larger datasets, alongside evidence relating to excessive data collection, competitor testimony regarding entry barriers, user surveys on multi-homing behaviour, and claims regarding security benefits from data-sharing. Similarly, Alphabet Inc. involved both transaction data concerning Play Store-based UPI payments and a technical assessment of the relevant payment architecture. Other decisions reflect the same approach. In REC Power, the inquiry relied on rejection-rate statistics and post-entry market-share data, while also considering evidence that consumer preference stemmed from the expertise of the opposite party. In Yogesh Pratap Singh v PVR Ltd., the CCI examined revenue diversification and the absence of foreclosure, together with commercial justifications relating to consumer demand and screen allocation. This approach is consistent with international guidance. The OECD identifies prices, costs, market shares, the duration and coverage of arrangements, and network effects as relevant indicators, while also emphasising production conditions, market functioning, consumer behaviour, demand segmentation, and marketing practices. Similarly, the European Commission's Guidance on Article 82 Enforcement Priorities highlights factors such as affected sales, market share, duration of conduct, and cost-based tests. These examples demonstrate that an effects-based analysis ordinarily requires the consideration of substantial economic, factual, and market evidence before competitive harm can be established. In any such analysis, pro-competitive effects must be weighed against the anti-competitive effects i.e. the rule of reason is to be followed (CLRC Report, ¶4.1). Concerns In A Digital Market Requiring proof of anticompetitive effects makes detailed evidence essential. However, as in the EU, this may raise the CCI’s evidentiary burden and risk underenforcement (p. 776). In India, the ex-post framework, with multiple investigative and adjudicatory layers, makes delay more likely – especially for digital markets (CDCL Report, ¶2.3). This is because regulating digital markets places substantial demands on the CCI, requiring capabilities that extend beyond traditional legal and economic analysis. Effective oversight of the digital economy increasingly depends on specialised expertise in areas such as big data analytics, algorithmic systems, artificial intelligence, machine learning, and digital market design (Standing Committee Report, p. 89). These demands are likely to intensify if an ex-ante regulatory framework is introduced, necessitating greater reliance on data scientists, technologists, and market analysts alongside legal and economic experts (ibid.). However, even now, CCI presently faces significant capacity constraints. As of 31 March 2024, only 113 of its 195 sanctioned posts were filled, reflecting a substantial staffing shortfall. Similar constraints exist within the Director General's office, where staffing levels declined from 23 filled posts in 2022-23 to only 13 in 2024-25 against a sanctioned strength of 41 (ibid.). Even in a general context, in its evaluation of Regulation 1/2003, the European Commission found that abuse of dominance investigations under Article 102 TFEU lasted on average 5.7 years (EC Evaluation, p. 154). Digital markets are distinct from traditional markets. Inter alia, they are driven by strong network effects where the value of a product or service increases as more people use it, making them prone to tipping (ibid, ¶¶1.12, 2.2). Incumbents, having access to significant data, are able to establish themselves in adjacent markets and thus foreclose new entrants (ibid, ¶¶2.3, 2.9). Against this backdrop, the requirement of evidence may lead to prolonged investigations during which the market may have tipped or harm may have become entrenched (p. 4). For instance, the CCI initiated its suo motu investigation into WhatsApp’s 2021 Privacy Policy on 24 March 2021, yet the final order was delivered only on 18 November 2024, a period of nearly three years and eight months. Similarly, the Google Android matter originated as Case No. 39 of 2018 and culminated in a final CCI order only on 20 October 2022, almost four years later, before entering further appellate proceedings. Moreover, evidence in an adversarial system must be carefully perused, being brought by opposing parties.[1] There may also be a resource gap between well-resourced private actors and capacity-constrained regulators (ibid, p. 5). Therefore, requiring an effects-based analysis for every §4 case is likely to lead to underenforcement. To prevent underenforcement, the ratio of Schott Glass should be read to account for a parallel ex-ante framework as well. In fact, in the EU, the Digital Markets Act (“DMA”) imposes obligations on designated ‘gatekeepers’, through Article 3. Under this ex-ante framework, once a gatekeeper is recognised, there is no need to show anticompetitive effects (DMA, Preamble 11). Instead, gatekeepers must annually justify their expected compliance, and the Commission may additionally seek ex-post proof of actual compliance (DMA, Articles 11 and 21). From the perspective of businesses as well, the DMA gives dominant platforms clearer ex-ante rules of engagement, reducing reliance on prolonged and uncertain competition litigation. Thus, the effects-based analysis applies in conjunction with the DMA i.e. to digital entities which do not fall under the category of gatekeepers. Similarly in India, the now-withdrawn DCB introduced ex-ante rules for systematically significant digital enterprises (“SSDE”). Therefore, given the dynamic nature of digital markets, delaying intervention until anticompetitive effects manifest may lead to irreversible harm. In such cases, it is submitted that parallel ex-ante and ex-post frameworks should regulate a claim for AoDP under §4. The point is not to replace or duplicate §4 enforcement, but to interpret Schott Glass as allowing ex-ante regulation to operate in parallel where warranted. One response is that the Competition (Amendment) Act, 2023 introduced settlements and commitments. These mechanisms may reduce the duration of proceedings by allowing parties to resolve investigations before a final finding of contravention. They therefore partially mitigate concerns regarding delay. However, settlements do not eliminate the need for ex-ante regulation. First, they operate only after proceedings have commenced. Second, they remain dependent upon the regulator identifying and investigating potentially harmful conduct. Third, in rapidly tipping digital markets, significant competitive advantages may already have accrued before a settlement is reached. Conclusion Schott Glass rightly requires proof of competitive harm before imposing liability under §4. The challenge lies not in the doctrinal correctness of an effects-based approach, but in the institutional realities of enforcing it. Digital markets may evolve faster than conventional competition proceedings. Accordingly, the case for ex-ante regulation does not weaken after Schott Glass; if anything, the evidentiary demands introduced by the judgment make a complementary ex-ante framework more important. [1] However, in India, the presence of the Director-General as an investigative entity may mitigate this risk (see Competition Act 2002, ss 16, 26(1)).

Vikram Raj Nanda is a fourth-year student at the National Law School of India University, Bengaluru. Introduction Recently, the Parliament enacted the Insolvency and Bankruptcy Code (Amendment) Act, 2026, which amends the proviso to Section 31(4) in a manner that allows the Resolution Professional, in cases where a Resolution Plan involves a ‘combination’, to obtain approval from the Competition Commission of India (CCI) ‘before the resolution plan is submitted to the Adjudicating Authority’ during a Corporate Insolvency Resolution Process (CIRP). This marks an effective reversal from the earlier position, as affirmed in Independent Sugar v. Girish Sriram Juneja, which mandated prior approval of the CCI before the plan was laid before the Committee of Creditors (CoC). This position was subsequently reaffirmed in the review petition, thereby reinforcing the sequential approval mechanism under which CCI approval had to be obtained before the CoC considered the resolution plan. The amendment, however, departs from this position by permitting CCI approval to be obtained at any stage thereafter, so long as it is secured before the resolution plan is submitted to the Adjudicating Authority. This paper supports the majority judgment in Independent Sugar and argues: first, that the claim that the sequencing mandated in Independent Sugar causes further delays is incorrect, second, that the structure and ex ante logic of the Competition Act, 2002, independently support prior CCI approval before CoC consideration and third, that deferring competition scrutiny till after CoC approval undermines the principle of deference to the CoC’s commercial wisdom, which is a fundamental thread that runs through the IBC and its judicial interpretations. The Myth of Delay: Will the Amendment Actually Save Time? The Report of the Select Committee on the Insolvency and Bankruptcy Bill cites ‘delay’ as being the primary justification for the proposed amendment to Section 31(4) of the IBC. This concern is frequently invoked in light of the broader problem of delays that have plagued insolvency proceedings. However, it is argued that such concerns are often not only unsupported empirically, but the proposed amendment may further end up aggravating delays (further discussed below). The difficulty lies in the temporal mismatch created by pushing CCI approval to a late stage of the CIRP. The primary reason for this is the lack of precise delineation on when the approval of CCI is to be secured: prior to approval of the Resolution Plan by the CoC or after such approval. In this regard, Regulation 40A of the CIRP Regulations, 2016, containing the model timelines for the CIRP, stipulates that resolution plans shall be received by the CoC at most within 135 days of commencement of the CIRP (T + 135d). Then, the CoC shall approve and submit the plans at T + 165d to the AA, which in turn, is expected to approve the said plan by T + 180d. Assuming that these timelines are adhered to, as they ideally ought to be, the effect of the proposed amendment is that the Successful Resolution Applicant (SRA) may be compelled to seek approval of the CCI in the narrow window of around 15 days between CoC approval and adjudication by the Adjudicating Authority. Evidently, such a timeline is not feasible. More importantly, under Section 31(1) of the IBC, the Adjudicating Authority can only approve a plan that satisfies the requirements of Section 30(2), including the mandate under clause (e) that the plan not contravene any law in force. In the absence of prior CCI approval, a plan involving a notifiable combination may fail to meet this requirement, thereby preventing approval by the Adjudicating Authority and necessitating further adjournments of the CIRP process. Hence, rather than streamlining the insolvency process to assist its adherence to the model timelines, the amendment risks introducing further bottlenecks. It is acknowledged that in Committee of Creditors of Essar Steel India Limited v Satish Kumar Gupta, the Supreme Court diluted the rigidity of the 330-day outer limit in limited circumstances by permitting reasonable extensions where delay is not attributable to the parties. However, this concession still cannot diminish the importance of timely resolution – an integral objective of promulgating the IBC in the first place – as prolonged delay continues to erode asset value and heighten the risk of liquidation. Additionally, the CCI’s Annual Report further highlights that CCI takes on an average 16 days for approving most combinations. In fact, in 2024-25, none of the approvals took more than 60 days in total. This trend has been continuing for several years (with the average being 16 days in 2023-24, and 21 days in 2022-23) and empirically, there is no indication that these timelines are likely to change. In sum, both empirically and as a matter of statutory design and objective, the concerns surrounding delay appear to be misplaced. Structure of the Competition Act: Ex Ante Review and Harmonious Construction Moving beyond these concerns even if the CIRP timelines are assumed not to be in conflict, the interpretation adopted in Independent Sugar is nevertheless supported by the structural design of the Competition Act, which not only permits, but also contemplates the initiation of competition scrutiny at an earlier stage. Under Section 6(2) of the Act, a combination becomes notifiable after approval by the Board of Directors or on the execution of ‘any’ agreement or ‘other document’ for acquisition of control. As per the Explanation to Section 6(2), the phrase ‘other document’ is of a wide import and encompasses any document conveying a decision or an agreement to acquire control. The notification obligation under the Competition Act is therefore triggered not by the consummation of the transaction, but by the existence of a sufficiently concrete proposal to acquire control. This stands in contrast to the IBC, under which a Resolution Plan acquires binding legal effect only upon its approval by the Adjudicating Authority under Section 31(1). The significance of this distinction is that the Competition Act does not predicate the CCI's jurisdiction on the legal finality of the underlying transaction. Consequently, although a resolution plan remains contingent and non-binding for the purposes of the IBC, it may nevertheless constitute an ‘other document’ sufficient to trigger the notification requirement under Section 6(2). This was recognised by the majority in Independent Sugar (p. 93), and is a point often missed by its scholarly criticism. Additionally, this is reinforced by CCI’s decisional practice, wherein the CCI often grants approval at the stage of the submission of Resolution Plan, prior to approval by the CoC.[1] Further, in Independent Sugar, the Court held that approval can be sought not only at the stage of submission of Resolution Plans to the CoC (T + 135d), but also prior to that at the stage of issuance of Request for Resolution Plans (T + 105d), or upon submission of plans to the Resolution Professional before they are taken up for consideration by the CoC. This must be read in light of the object of the Act. The suspensory regime therein is an ex ante review, analysing combinations before they have attained binding legal effect. Merger control is designed to prevent distortions to market structure before they occur, rather than to remedy anti-competitive harm ex post facto. Hence, far from creating inconsistency, this approach aligns with the ex ante logic of merger control. Deferring to the Commercial Wisdom of the CoC In addition to the structure of the Competition Act, the interpretation adopted by the majority in Independent Sugar is further supported by the design and the intended operation of the IBC. One of the primary objectives of the Code was to entrust commercial decisions to the CoC, instead of judicial forums. This is evident in the manner in which Section 31(1) and Section 61(3) of IBC are structured, allowing courts very limited grounds for interfering with the CoC’s decision. The Supreme Court also recognised deference to the CoC’s ‘commercial wisdom’ as a foundational principle of the IBC. Notably, in Swiss Ribbons v Union of India, the Court emphasised that the CoC, composed of financial creditors, is best placed to assess the feasibility of restructuring and reorganisation of the corporate debtor and its decision should remain final. However, the objectives pursued by the CoC and the CCI are distinct and may, in practice, conflict. The CoC is concerned with maximising the value of the corporate debtor through a commercially viable resolution, whereas the CCI is tasked with ensuring that the proposed acquisition does not substantially lessen competition. This divergence becomes particularly apparent in the context of the failing business consideration recognised under Section 20(4)(k) of the Competition Act. While the insolvency of the target may justify permitting an otherwise anti-competitive acquisition where the business would inevitably exit the market, the CCI must first satisfy itself that the target is genuinely a failing business, that its exit is unavoidable, and that no less anti-competitive purchaser or transaction is reasonably available. These considerations are fundamentally different from those that guide the CoC, whose inquiry centres on maximising creditor recoveries and identifying the most commercially feasible resolution applicant. It is therefore entirely possible for the CoC to conclude that a particular resolution plan is commercially optimal, while the CCI, applying competition law principles, concludes that the same transaction can only be approved subject to structural modifications, such as divestitures, or that another purchaser would preserve competition more effectively. Hence, permitting CCI approval to be sought after CoC approval may undermine the principle of respecting the CoC’s commercial wisdom. Since the CCI may under Section 31(3) of the Competition Act, direct modifications to a combination that may involve both structural and behavioural remedies, the CoC's commercial assessment ceases to be final and instead becomes contingent upon a subsequent determination by the CCI. . In effect, this may result in a situation where a plan that has already been approved by the CoC would subsequently be altered in material respects pursuant to directions issued by the CCI. This fundamentally unsettles the finality that is sought to be awarded to the CoC’s commercial determination (vide Swiss Ribbons). An instance of this was evident in the factual scenario of Independent Sugar itself, where the CCI approved the plan conditional on the divestment of the Rishikesh plant by AGI Greenpac. Furthermore, in the case of non-approval by the CCI, the resolution process itself may be derailed, exacerbating delay which erodes the asset value of the corporate debtor, and increases the likelihood of liquidation. This analysis also fundamentally addresses Justice Bhatti’s dissent in Independent Sugar which proceeds on the premise that the CoC is only concerned with the ‘viability and feasibility’ of the plan, with the domain of its legality and regulatory compliance being under the purview of the Adjudicating Authority. Though correct, this does not imply that its commercial judgment can be meaningfully exercised in the absence of final and certain clarity on the legal viability of the plan. A plan that remains contingent upon CCI’s approval remains fundamentally indeterminate. Furthermore, the contention that prior competition approval would reduce the pool of eligible resolution applicants is circular (vide Justice Bhatti’s dissent), mistaking the intended effect of the statute as the cause. The exclusion of plans that are incapable of complying with the Act is not an unintended consequence of the framework, but a deliberate and necessary feature of a resolution process that seeks to ensure that only legally and commercially viable plans are placed before the CoC for consideration. Conclusion In conclusion, this paper has argued that the proposed amendment to Section 31(4) of the IBC undermines both the statutory architecture and economic rationale governing insolvency resolution in India. Through an examination of CIRP timelines, the structure of the Competition Act, the principle of commercial wisdom, it has been shown that deferring competition scrutiny to a post-CoC stage neither meaningfully reduces delays nor enhances overall gains. [1] See R Pande, Notice of Combinations in Insolvency Resolution [2021] 14(1) NUJS Law Review, 9-10. The article undertakes an empirical assessment of the stage at which parties usually apply for CCI’s approval.

(Khushi Gupta is a 4th year student at the National Law School of India University, Bengaluru) Introduction Reverse acquihires are no longer a Silicon Valley curiosity; they are now a competition law problem in plain sight. Recent deals by major technology firms have followed a common structure: hiring key teams while licensing technology, without acquiring equity, such as the Microsoft-Inflexion deal or the Amazon-Adept deal. Google has also replicated the structure by hiring Windsurf's CEO, co-founder, and select R&D staff into DeepMind, paying $2.4 billion in licensing fees and compensation. Because they avoid share or asset transfers, these deals typically escape merger review. The structure is consistent with mass hiring combined with IP licensing and compensation, but without any formal transfer of shares or assets that would trigger notification. Regulators have begun to scrutinise such arrangements in AI markets. Against that backdrop, India’s 2024 merger-control reforms introduced a deal-value threshold (DVT) to catch high-value transactions that slip past ordinary asset-and-turnover tests. This article asks whether India’s merger control framework can reach transactions that resemble hiring in form but function as acquisitions in substance. The Deal Value Threshold: A Quantitative Fix with a Definitional Gap The DVT was introduced to capture high-value transactions involving targets with smaller assets or turnover. Under the 2024 Combination Regulations, notification is required where the deal value exceeds INR 2,000 crore and the target engages in substantial business operations in India. In fact, the threshold of "substantial business operations" for digital firms has been set especially to cover those entities that mattered based on large user bases, high Gross Merchandise Value (GMV), or significant revenue from India. DVT’s first full year has given a clear picture of its actual operations. Of the 162 combination notifications approved by the CCI between late 2024 and the end of 2025, only 12.36% were filed solely pursuant to the DVT. While the regime is functioning, the difference is narrow. The DVT expands coverage of small – but valuable – acquisitions, but remains tied to transactions that structurally resemble acquisitions. This fails to cover reverse acquihire, which is typically organised as mass hiring plus ancillary IP licensing or a non-compete arrangement, and may transfer substantial competitive value without transferring the enterprise, its shares, or its control. The DVT is a better measuring stick, but it cannot capture a transaction deliberately structured to avoid stepping onto the scale. Economic Substance Over Legal Form: When Talent Acquisition Becomes Market Acquisition Although hiring and acquisition are formally distinct, their competitive effects may converge in innovation markets. In innovation markets, a startup’s significance lies less in current revenue than in its potential to become a future competitor. As studies show, incumbents often attempt to eliminate such threats at an early stage by acquiring the startup. A reverse acquihire achieves similar results without a formal acquisition. Once a startup’s core team is absorbed, its capacity to evolve into a competitor is effectively eliminated. This effect is particularly pronounced in AI and deep-tech markets, where human capital constitutes the firm’s primary asset. Acquihires can therefore function as mechanisms of talent pre-emption, internalising scarce expertise before it can support competing firms. This blurs the lines between hiring and acquiring in a practical setting. When Google paid approximately $2.4 billion to hire Windsurf's CEO and key R&D staff while licensing its technology, it arguably achieved the economic equivalent of acquiring a potential competitor, without the regulatory burden of a formal acquisition. Reverse acquihires may also produce dynamic deterrence effects. If incumbents can systemically neutralise emerging threats through talent acquisition without any regulation, the incentive to enter the market itself is weakened. In the longer term, it could result in erosion of innovation and rivalry. The Indian AI industry is particularly susceptible to reverse acquihires. India’s GenAI ecosystem has expanded to over 890 startups, but cumulative funding was only about $990 million by mid-2025, heavily skewed toward early-stage deals, with late-stage capital drying up as investors turn selective. This leaves many technically capable yet capital-constrained startups without a clear domestic scaling path, incentivising them to accept liquidity through hiring arrangements rather than formal acquisitions. At the same time, Bengaluru hosts over 600,000 AI/ML professionals concentrated in a few firms, creating a dense talent pool that global incumbents can absorb cheaply without meaningful scrutiny under India’s current merger control framework. Doctrinal Limits: Why Existing Hooks Fail to Capture Reverse Acquihires The economic concern is clear; the legal position under Indian law is not. The doctrinal difficulty is that Indian merger control relies on the idea of “combination” as defined in Section 5 of the Competition Act. Section 5 defines combinations in terms of acquisition of control, shares, voting rights, assets, or mergers. A reverse acquihire does not neatly fall within any category. The incumbent is simply hiring the team and licensing the IP and might be paying non-compete fees, but it is not acquiring the enterprise. There are different potential hooks under the Competition Act which can cover reverse acquihires to some extent, but none of them is complete in itself. Section 5’s Explanation (a) defines control as a material influence, and CCI’s FAQs also mention that “Control” is capacious and that material influence is the lowest level of control, but that requires an enterprise whose decision can actually be influenced. Once the core team is taken away, along with the IP license, the residual entity may be little more than a shell. Another argument could be made under Regulation 9(4) of the Combination Regulations, which requires parties to file a single notice, where the ultimate intended effect of a transaction is achieved as a result of a series of interconnected transactions. A hiring agreement combined with an IP licence and a non-compete payment could, in principle, be framed as interconnected steps achieving the economic equivalent of an acquisition. However, the framework is premised on investment in an enterprise, which hiring does not constitute. Therefore, the rule does not apply to transactions that are not in the form of a combination, even if the ultimate effect is similar. Lastly, Section 20 of the Act allows the CCI to inquire into combinations, but only where a transaction falls within Section 5. It is not a free-standing call-in power for transactions that never look like combinations in the first place. A reverse acquihire never crosses that threshold, and therefore CCI does not have the power to investigate it. The gap is definitional in law. While the 2024 Deal Value Threshold improves notification coverage for high-value transactions with substantial business operations in India, the regulations still operate within the combination framework rather than outside it. Closing the Gap: Toward a Substance-Based and Call-In Driven Framework The solution is not to stretch existing concepts of control, but to adopt a substance-over-form approach. The FTC’s 2025 report on AI partnerships adopts this approach, examining contractual substance and competitive effects rather than formal labels. India should take the same analytical approach. A reverse acquihire should be assessed by its competitive effect, not by whether the parties have dressed it up as hiring plus an IP licence. That interpretive shift would be stronger if paired with an express call-in power for below-threshold transactions that may not neatly qualify as combinations but still reshape market structure. Comparative practice also suggests broader principles, such that a transaction that falls below merger thresholds is not automatically beyond competition scrutiny, and ex post control remains possible in some systems. Finally, the DVT’s “substantial business operations” concept should be read functionally. The CCI has already moved toward recognising that transaction value and Indian operational presence can matter even where assets and turnover do not fully capture significance. In innovation markets, workforce concentration should be treated as an indicator of competitive significance. Conclusion The DVT was a meaningful reform, but it is still a quantitative fix, not a complete answer. The 2024 framework widens notification coverage for high-value deals with substantial business operations in India, yet section 5 of the Act continues to define combinations through control, shares, voting rights, assets, merger, or amalgamation. Reverse acquihires expose the remaining gap: they may look like recruitment, but in economic substance, they can function as acquisitions of competitive capability. If India’s merger-control regime is to keep pace with AI and deep-tech markets, it will need to police not just value, but structure. Image Attribution: https://fastcompanyme.com/work-life/ai-talent-demand-is-soaring-in-the-middle-east-but-is-acquihiring-the-right-strategy/

“Welcome to the garden, we’ve got fun and games We got everything you want …, we know the names We are the people that can find whatever you may need… If you want it you’re gonna bleed but it’s the price to pay… You can taste the bright lights but you won’t get there for free…” (An adapted and abbreviated version of the 1987 hit song – “Welcome to the Jungle” by Guns n Roses, 1987)1 I. The Background – Snowballing Scrutiny, Everyone Wants a Bit(e) of the A(pple)ction In a recent complaint to the Competition Commission of India (CCI), Apple Inc has been accused of abusing its dominance by forcing app developers, who have their apps hosted on the iOS platform, to use its own ‘in- app purchase’ mechanism (IAP) and pay an ‘excessive’ 30% transaction fee. This is not an isolated complaint against Apple as it faces a series of similar suits across the globe, particularly aggravated by Apple’s ‘closed’ iOS ecosystem. Apple’s high degree of vertical integration has led to the description of this ecosystem as ‘walled garden’2– a garden to which it alone determines which app/software can be used (gatekeeper) and by virtue of dependence, possibly tends to keep its users locked-in. Unlike Google’s licensed Android OS, the iOS is not available in the market for other smartphone manufacturers. The current case is that, unlike the earlier investigations which were concerned with exclusionary abuses, including predatory pricing, or merger related issues, concerns potential ‘excessive pricing’ which involves far more complexities of allocating common costs to different segments. I.I Different Agencies, Different Strokes – Time for Coordinated Action? Among the competition agencies currently investigating Apple’s App Store policies include the EU Commission (EUC), which is investigating a complaint related to IAP fees and ‘anti- steering’ contractual rules, specifically related to music-streaming and ebook/audiobook apps3 and, the UK Competition and Markets Authority (UK-CMA) which is examining a civil suit on similar grounds4. The Australian Competition and Consumer Commission (ACCC) has initiated a broad-based inquiry into digital platform services, and has found both, Apple and Google, dominant on their respective mobile operating systems (OS), thereby, giving them ‘significant market power’ in the marketplace for app distribution5. It has recommended transparency with respect to alternate payment mechanisms for IAP’s, but, has refused to be drawn into the debate concerning the excessiveness of IAP fees6. In a very recent settlement with the Federal Trade Commission (Japan), Apple agreed to modify certain restrictive App Store guidelines and allow for in-app links to outside payments portals for ‘reader’ apps.7 To some extent this amounts to a concession in a category of apps where Apple is facing resistance from important competing apps. Netflix and Spotify (a complainant in the EUC case), both reader apps and competitors to Apple’s own digital services8 i.e., Apple TV+ and Apple Music respectively, pulled out from the iOS IAP payment option, in retaliation against Apple’s fees9. Netflix was the single largest IAP fee grosser for iOS, with about $256 million (2018)10 and, Spotify contributed a handsome $156 million (2015-18)11. It remains to be seen if Apple’s intention to apply the settlement globally12 will mollify the EUC. Nevertheless, it still excludes a large number of apps and, the cases in UK and India are not specific to any particular category of apps. Apart from ex-post antitrust scrutiny, Apple faces a host of state regulatory action. The South Korean government, besides looking askance at unilateral deletion of apps or undue delay in their approval, has banned the imposition of their own IAP by Apple and Google13. While Google has responded by saying that IAP revenue allows it to provide the Android OS for free14, trying to draw attention to the economic model of platforms, Apple appears more intransigent by refusing to reverse its deletion of a popular South Korean gaming app ‘Fortnite’, owned by Epic, which had sought to bypass Apple’s IAP by introducing an alternate payment mechanism.15 Acceding to Epic, it may have large revenue consequences for Apple, given that gaming apps are the largest source of app revenue at $47 billion (2020).16 But, in another very recent development, in Epic Games Inc v Apple Inc, a US District Court ruled that Apple should allow app developers to provide links to external websites for payments.17 While there appears unanimity among the agencies/courts that have completed their reviews/investigations or reached a settlement, that Apple needs to change its App Store terms to allow for alternate payment options, there is still divergence with respect to how exactly this needs to be done. While some want this to be applied to all apps, others are concerned only with reader apps. Further, there are differences in both defining the relevant product market and findings related to whether Apple is ‘dominant’ or possesses ‘substantial market power’. In Epic Games v Apple Inc., the judge did not find Apple to have monopoly power (‘substantial market power’) in the market for digital mobile gaming but only found its anti-steering provisions to be creating information asymmetry and hence potential, lock-in effects and exploitation of consumers.18 The ruling appears more like an ex-ante regulatory finding rather than a response to antitrust violation with the judge validating Apple’s business model and the need for earning returns to intellectual property. The ACCC, on the other hand, found both Apple and Google to be dominant, having ‘significant market power’ in a differently defined market i.e., the marketplace for distributing apps.19 In a comparable case, Google Android, the EUC found ‘Android app stores’ to be a relevant product market, as it did not find Apple iOS to be a constraint on licensed Android OS.20 This could be an indication of where the EUC may be headed, although, there may be some divergence given the ‘closed’ nature of iOS. Given the significant global homogeneity in policies adopted by Apple, and other tech companies, it may perhaps be time for major competition authorities to arrive at a coordinated investigation and a standardized approach with, perhaps, some geographically differentiated aspects, to the regulation of these firms. This would save transaction costs of each agency having to investigate separately, the confusion of differential approaches by each country and besides saving on time overruns in investigations. But the Neo Brandeisians may have a different idea. I.II The Neo -Brandeisian assault In the US, the House Judiciary Committee, of the House of Representatives, led a sweeping investigation into potential anticompetitive behavior in digital markets, focused on Apple, Google, Facebook and Amazon, and found them to be abusing their market power arising out of their position as ‘gatekeepers’ to different important digital distribution channels.21 The Committee found both Apple and Google to be dominant in their respective app stores22 and called for regulations that would eliminate ‘self-preferencing’ and other abuses that affected competition.23 But of significance are a series of recommendations, that are based on the conclusion that the current Antitrust laws are both inadequate and improperly enforced, by way of excessive focus on ‘consumer welfare’ as the guiding principle.24 The Committee suggests both institutional and substantial law reforms including: rebasing enforcement on the ‘antimonopoly’ intent of legislations; emphasis on ‘overenforcement’ rather than ‘underenforcement’; protection of the ‘competitive process’, start-up’s, potential and, nascent firms; a more hawkish view of their acquisitions/mergers by/with the large tech firms and; removing the requirement of proving ‘recoupment’ in predatory pricing cases in digital markets.25 We are yet to see any enforceable action based on these recommendations, which have a heavy tilt towards the, so-called, Neo-Brandesian School (NBS) of thought, which inherently suspects bigness and the use of consumer welfare standard (CWS).26 But, the appointment of two prominent proponents of this school of thought, Lina Khan, as the Chairperson of the Federal Trade Commission (FTC) and, Tim Wu, to the National Economic Council, by the US government signals a strong intent in this direction.27 However, the primary arguments of this school have met with strong criticism.28 Some have termed it as ‘hipster’ antitrust or ‘populist antitrust’ which, unwisely, seeks to solve a range of social, economic and political issues through the instrument of antitrust regulation.29 To sum up some of these responses: the NBS approach does not adequately acknowledge the influence of modern Industrial organization theory (including, game theory) and empirical studies which departs substantially from the Chicago School by establishing how anticompetitive strategies are both possible and profitable particularly under conditions of information asymmetry; CWS is an end objective of ‘competitive process’ and not independent of it and besides it provides a more transparent economic objective as compared to political decision making which is open to ‘capture’; departing from conduct based analysis and relying only on size (no-fault antitrust) opens up decisions to false positives which may have larger consequences particularly with respect to platforms; the empirical literature used to show that the US faces increasing industrial concentration and resulting higher profit margins, due to slack antitrust enforcement, are faulty in methodology and data and, in certain circumstances even wrongly inferred and; it is not even a correct reflection of Judge Brandeis’s ideas who, although in favour of small business, preferred economic methods and was less interventionist himself. At the same time there has been recognition of certain weaknesses in the current enforcement approach. Hovenkamp (2019), while supporting the CWS, points out that current enforcement, among others, needs to reexamine the ‘recoupment test’ in predatory pricing cases.30 Werden (2018), while disagreeing with the need for multiple objectives based antitrust, agrees that excessive focus on effects can at times lead to the neglect of competitive process itself.31 These debates and decisions are bound to have significant ramifications for future pricing strategies and other practices of both Apple and Google (Android OS) specifically and, other two-sided or multi-sided platforms, generally. Platforms, in their urge to expand their market size and increase their market power, or tip markets in their favour, by virtue of network effects, often adopt ‘zero’, below marginal cost or even negative pricing32 for users on one side. By charging the other side(s), based on their own-price elasticity and intensity of demand side externalities, theoretically, they have a rational profit maximizing strategy.33 Addressing pricing issues on only one side of the platform can lead to incomplete analysis and possible false positives. In other words, defining the appropriate relevant market for two(multi) sided platforms is important, but at the same tome tricky, particularly as the somewhat settled ‘transaction’ and ‘non-transaction’ platform differentiation approach adopted by agencies, so far, faces new theoretical challenges. The CCI is no stranger to complaints related to platforms and of particular interest would be its decision in the Android OS case, which could provide insights into its definition of relevant markets for apps/app stores and competitive constraints imposed by the iOS – although we need not expect symmetricity in relevant market definition in the Apple case.34 Nevertheless, the significance of this sector cannot be underestimated with app downloads, in India, growing at a scorching pace of 190%, accounting for 14% of the 218 billion apps downloaded globally (2020)35 and a total app-based revenue of approximately $1.4 billion (2021)36. About the Author: Dr. T S Somshekar is Professor of Economics and Director for the Centre for Competition and Regulation, National Law School of India University, Bengaluru. This is the first of the three-part series by Dr. T S Somashekar. This article was originally posted at The NLS Blog. The link for the same is https://www.nls.ac.in/blog/apple-to-face-competition-law-scrutiny-in-india-towards-a-new-platform-pricing-paradigm/ Endnotes: The song’s lyrics has an uncanny (literal) resemblance to the nature of the complaint against Apple Inc. Its actual reference was supposedly the attraction of New York city for those aspiring to make it big and the cost involved. Joanna Stern, “iPhone? AirPods? MacBook? You Live in Apple’s World. Here’s What You Are Missing”, WSJ, June 4, 2021; The US court refers to the same term in its decision in Epic Games, Inc. v. Apple Inc., Case No. 4:20-cv-05640-YGR (N.D. Cal. Sept. 12, 2021) p.3 “Antitrust: Commission opens investigations into Apple’s App Store rules” EUROPEAN COMMISSION (June 16, 2020). “Apple accused of breaking UK competition law by overcharging for apps” THE GUARDIAN (May 11, 2021). “Digital platform services inquiry, Interim report No. 2 – App marketplaces”, AUSTRALIAN COMPETITION AND CONSUMER COMMISSION, (March 2021) p.4. Ibid p. 13. According to Apple, reader apps are “previously purchased content or content subscriptions for digital magazines, newspapers, books, audio, music, and video”; “Closing the Investigation on the Suspected Violation of the Antimonopoly Act by Apple Inc.” Japan Fair Trade Commission (September 2, 2021) (accessed on September 20, 2021); “Japan Fair Trade Commission closes App Store investigation” APPLE NEWSROOM (September 1, 2021). David Curry, “Apple Music Revenue and Usage Statistics (2021)” (Updated: June 2, 2021). Sarah Perez, “Netflix stops paying the ‘Apple Tax’ on its $853 in annual iOS Revenue” TECHCRUNCH (January 1, 2019). Supra n. 8 (David). Shona Ghosh, “This chart shows why Spotify is desperate for every dollar it can get back from Apple,” BUSINESS INSIDER (March 14, 2019). Supra n. 7 (Japan Fair Trade Commission) Jiyoung Sohn, “Google, Apple Hit by First Law Threatening Dominance Over App-Store Payments” WALL STREET JOURNAL (August 31, 2021). Available at https://www.wsj.com/articles/google-apple- hit-in-south-korea-by-worlds-first-law-ending-their-dominance-over-app-store-payments- 11630403335 (accessed on September 22, 2021) Supra n. 8 (David). Siladitya Ray, “Epic Wants Fortnite Back on South Korean App Store After New Legislation, Apple Says No” FORBES (September 10, 2021). Mansoor Iqbal, “App Revenue Data (2021)” BUSINESS OF APPS (Updated: August 4, 2021). Case No. 4:20-cv-05640-YGR (N.D. Cal. Sept. 12, 2021). Ibid pp. 158-160. Gregory J. Werden and Luke M. Froeb, “Antitrust and Tech: Europe and the United States Differ, and It Matters” (August 26, 2019). AT.40099 – Google Android, EU Commission (18/07/2018). “Investigation of Competition in Digital Markets” Majority Staff Report and Recommendations, Subcommittee on Antitrust, Commercial and Administrative Law of the Committee on the Judiciary (2020) p. 11- 16. The Committee found each of them acting as ‘gatekeepers’ or enjoying ‘dominance’ in different segments: Facebook in social media; Google in internet search and online advertising; Amazon in online retailing and Apple in the iOS operating system which gave it ‘monopoly’ market power in the app store market. Ibid at pp. 97 – 99. Ibid at p. 20. Ibid at p. 20 – 21. Ibid at p. 390 – 397. See, Mr. Justice Brandeis, “Competition and Smallness: A Dilemma Re-Examined” 66 YALE L.J. (1956): The school, apparently, looks to go back to the actual objective of antitrust laws which they believe are well reflected in the late Justice Louis D. Brandeis’s views who believed that concentration of industrial power among large corporations could threaten democratic the process and that the answer to that was more small firms Two important works that have propounded the ideas of Judge Brandeis, in recent times, attracting the name ‘New/Neo Brandeis School’, include: Tim WU, “The curse of bigness: antitrust in the new Gilded Age” COLUMBIA GLOBAL REPORTS (2018); and Lina M. Khan, “Amazon’s Antitrust Paradox” 126 YALE L.J. (2016): Lina Khan, attempts to explain and clarify their position in: Lina Khan, “The New Brandeis Movement: America’s Antimonopoly Debate” 9(3) JOURNAL OF EUROPEAN COMPETITION LAW &; PRACTICE (March 2018) pp. 131–132; See also, Daniel Michaels and Brent Kendall, “U.S. Competition Policy Is Aligning With Europe, and Deeper Cooperation Could Follow” THE WALL STREET JOURNAL (July 15, 2021). Seth B. Sacher and John M. Yun, “Twelve Fallacies of the ‘Neo-Antitrust’ Movement” 26(5) GEORGE MASON LAW REVIEW George Mason Law & Economics Research Paper No. 19-12 (2019); Herbert J. Hovenkamp, “Is Antitrust’s Consumer Welfare Principle Imperiled?” 45 J. CORP. LAW 101 (2019); A.D. Melamed, and N. Petit,“The Misguided Assault on the Consumer Welfare Standard in the Age of Platform Markets” 54 REV. IND. ORGAN. 741 (2019) Joshua D. Wright, Elyse Dorsey, Jan Rybnicek and Jonathan Klick, “Requiem for a Paradox: The Dubious Rise and Inevitable Fall of Hipster Antitrust” 51(1) ARIZONA STATE LAW JOURNAL 293 (Spring 2019) Supra n. 28 (Hovenkamp) Gregory J. Werden, “Back to School: What the Chicago School and New Brandeis School Get Right” (September 4, 2018). Rewards offered by Google Pay, Paytm for using their e-wallets can be cited as an example. Of course, it can also be argued that users pay by means of providing transaction and other personal data For an understanding of the elasticity rules for pricing different sides of the platform, the pioneering work of Rochet and Tirole offer us guidance. See, J C Rochet and J Tirole “Platform Competition in Two-Sided Markets,” 1 JOURNAL OF THE EUROPEAN ECONOMIC ASSOCIATION 990 (2003). J.C. Rochet and J. Tirole, “Two-Sided Markets: A Progress Report” 37 RAND JOURNAL OF ECONOMICS 645 (2006) Kshitiz Arya and another v. Google LLC and others, Case No. 19/2020 (CCI) [Order Dated 22/06/2021] Umar Javeed & Others v. Google LLC & Other., Case No. 39/2018 (CCI) [Order Dated 16/04/2019] “India accounted for about 14% of 218 billion global app installs in 2020”, ECONOMIC TIMES (January 19, 2021). Digital Market: Apps (India), Statista.

It is now trite to say that data has become the new oil of the digital economy. Most corporations, across industries, seek to collect as much data as possible and seek to employ it in as varied applications as they can. Not surprisingly, the growing importance of data has resulted in several new challenges to competition, which necessarily require competition enforcement authorities to be on guard. The present paper is an examination of the legal landscape regulating data-related abusive behaviour in digital markets. It maps the recognition of data-related competitive concerns in the European Union where this issue has received considerable attention, with Germany particularly leading the way through its investigation and proceedings against Facebook. Subsequently, the paper examines the position in India by focussing on the Competition Commission of India’s decision in Google v. Matrimony. It finds that the Indian approach to data-related abuses leaves much to be desired, with the CCI failing to effectively engage with such issues. The paper calls for a rationalisation of the legal regime, so that increasing focus is laid on data protection and privacy related issues during substantive competition law assessments. Read full article here Article has been written by Kashish Makkar and Saarthak Jain, 5th Year students at National Law School of India University, Bangalore.

Cartelization hurts competition in various ways, and may be problematic from the perspective of a consumer at an atomistic level, and the entire economy from a more generalist perspective. While it is widely recognized as an antitrust offence, detecting cartels is challenging, especially since the agreement if often a tacit understanding. Deterrence is nevertheless imperative. Leniency programmes contribute to the deterrence objective by offering the means to help identify cartels by adopting a voluntary disclosure process based on an incentive system. Primarily inspired from the success of the US regime, there have been arguments in favour of criminalization of cartel conduct with a justification that leniency programmes cannot be as effective without the former. The paper refutes this claim. This is supported by a discussion on the circumstances specific to the Indian regime, especially the Indian take on the leniency framework. The paper also explores how to strengthen the leniency regime in India, especially from a standpoint which focusses on deterrence and cartel prevention. Read entire article here Article has been written by Saurabh Gupta, 4th Year student at National Law School of India University.

Over the years, predatory pricing has become an important subset of abuse of dominant position under Indian Competition Law. Predatory pricing, especially in the telecommunications sector, has been a persistent global problem for a while now. It has acquired even greater significance in India with the entry of Reliance Jio into the market, and the subsequent onslaught of allegations regarding anti-competitive behaviour. Here, we present a critique of the Competition Commission of India’s judgment in Bharti Airtel Ltd. v. Reliance Industries Ltd. & Anr. The objective of this paper is to show that CCI’s analysis in the case was flawed on three counts- first, what would be the relevant market in the case; second, the ascertainment of Reliance Jio’s dominance in the relevant marker; and third, whether or not Reliance Jio abused its dominant position by indulging in predatory pricing. Article has been written by Ananya HS and Arti Gupta, 4th Year students at National Law School of India University.

The Future of Mobile Ecosystems: Enabling a Choice for Market Players & Consumers in India The issue of “Choice” as an indicator of consumer welfare and effective competition has gained traction as the Digital Economy and its special dynamics increasingly touch on more and more aspects of our daily lives. The powerful effects of economies of scale, low or negligible costs and the momentum of network effects has led to what many perceive as excessive concentration in digital ecosystems, with Mobile technologies being among the most salient and impactful. Our panel of experts will look at the particular case of India, perhaps the largest market yet to fully embrace mobile technology, with the aim of understanding the country’s particular situation, challenges, and opportunities in this area. Antitrust Experts: T.S. Somashekar Professor of Economics, National Law School of India University Rahul Singh Associate Professor of Law, NLSIU Bangalore Geeta Gouri Former Commissioner, CCI Vinod Dhall Senior Adviser, Touchstone Partners and former Head, Competition Commission of India Moderator: Aditya Bhattacharjea Professor of Economics, Delhi School of Economics, University of Delhi

- Harjas Singh and Saurabh Gupta Android is the most popular mobile operating system in the world. For developers, android is a part open-source, part propriety core software that provides a reliable framework for them ­­to use and develop their apps. For regular consumers, it is a convenient operating system, offering the best of apps – Maps, Gmail, Youtube, etc. These free-for-all apps are at the core of the Google Android Antitrust dispute, which shall be discussed in the paper. But first, this paper shall aim to summarise the Google Android[1]case, and then proceed to critically analyse the penalties awarded in the case for their effectiveness, before suggesting alternative sanctions that may be more effective in such cases. The Google Android Case – A Summary In April 2015, the European Competition Commission initiated a formal investigation to examine whether Google had entered into anti-competitive agreements or abused its dominance by tying its apps to the Android software.[2] The investigation sought to identify whether Google had illegally hindered the development and market access of rival mobile applications or services. The Commission identified two markets – the upstream market for the licensing of Android to device manufacturers and the downstream market for end users. It then discussed that there were high barriers to entry in the licensable operating systems market. This was mainly due to network effects in the sense that the more users use a smart mobile operating system, the more developers write apps for that system. This in turn attracts more users. Further, competition in the downstream market did not sufficiently constrain Google’s position in the upstream market. It considered factors like high switching costs between Apple iOS and Google Android, higher price for Apple products, and consumers’ preference for Google services (like Google search) even after switching to Apple iOS to come to this conclusion. The Commission, through its market research, also concluded that Google, which had a market share of more than 95%, held a dominant position in the worldwide market (excluding China) for licensable smart mobile operating systems.[3] Further, it was also held that Google had a dominant position in the search engine market as well, with a market share of around 90%. This market too faced high barriers to entry. The Commission also looked at the market for app stores for Android mobile operating system. It discussed that this market was also characterised by high barriers to entry and lack of competition, and held that Google held a dominant position in the worldwide market (excluding China) for app stores for the Android mobile operating system.Having identified the markets, the Commission now examined three aspects of Google’s conduct that may amount to abuse of dominance: (i)Illegal tying of Google’s own applications or services Google bundled its apps and services with Android software, which made it mandatory for the manufacturers to pre-install all its apps. Since pre-installation creates a status quo bias, the Commission held that this practice reduced the incentives of manufacturers to pre-install competing search and browser apps, as well as the incentives of users to download such apps. This bundling arrangement, therefore, reduced the ability of rivals to compete effectively with Google. This was similar to a situation seen in case of Microsoft’s antitrust violations. Microsoft had abused monopoly power by bundling its web browser (Internet Explorer) as well as the Windows Media Player along with the Windows Operating System. It was held that such bundling restricted the market for the competing web browsers, and was violative of competition law principles. (ii)Illegal payments conditional on exclusive pre-installation of Google Search Google granted significant financial incentives to some of the largest device manufacturers as well as mobile network operators on condition that they exclusively pre-installed Google Search across their entire portfolio of Android devices. While this practice was discontinued in 2014, the Commission still held this to be anti-competitive since Google’s competitors in the search engine business could not possibly compensate the device manufacturer across all devices for loss of revenue share from Google. (iii)Illegal obstruction of development and distribution of competing Android operating systems Google, in order to be able to pre-install on their devices Google's proprietary apps, manufacturers had to commit not to develop or sell even a single device running on an any alternative version of Android that was not approved by Google (commonly referred to as ‘Android fork’). This, as per the Commission, reduced the opportunity for devices running on Android forks to be developed and sold. Therefore, the Commission held that Google denied the users access to further innovation and smart mobile devices based on Android Fork. This also gave Google the power to determine which operating systems could prosper. This was held to be anti-competitive. Taking all this into account, Commissioner Margrethe Vestager, in charge of competition policy, concluded: “…[Google’s] practices have denied rivals the chance to innovate and compete on the merits. They have denied European consumers the benefits of effective competition in the important mobile sphere. This is illegal under EU antitrust rules.”[4]The Commission thus imposed a fine of €4,342,865,000 on Google, which is around 5% of the average turnover of the last three years of Google’s parent company, Alphabet. Further, it threatened to impose a penalty of up to 5% of average worldwide turnover of Alphabet for non-compliance with this decision. Problems with the Sanctions Imposed While the fine imposed by the Commission is the largest it has ever imposed on a company, this section will discuss whether this fine is the appropriate remedy or not in light of the goal of enforcement mechanisms.[5] (i)Google Already Derived Substantial Benefits from Android The Commission looked at Google’s dominance for the past seven years. This meant that the Google had been allowed to derive illegal benefits from its dominant position in the market for seven years. Indeed, Google earned a revenue of €5.25 billion from the Android Play Store in 2017 alone. In comparison, the fine of €4.3 billion is hence, too little too late. The Commission must be proactive to ensure that enterprises are not allowed to derive huge profits by abusing their dominance for years. As things stand, a simple cost-benefit analysis would show that an enterprise stands to benefit from abusing its dominance, even if it is penalised for it later, in the long run. The kind of dominance that Google enjoys in the markets identified initially in the paper, are characteristic of the network effects that have already impacted the markets permanently. The penalty imposed may not lead to a reversal of the damage already done.[6] In 2004, a similar situation of bundling had arisen in the Microsoft Case. EC then had forced Microsoft to release a version of Windows without Windows Media Player and later offer a browser choice screen, which allowed users to select a web browser other than the previously default Internet Explorer. However, it was later discovered that the this version of the Windows had no buyers.[7] Microsoft had already reaped the benefits of the network effects of their antitrust activities. In this case as well, consumers are unlikely to buy a version of Android without Google’s services. Thus, it can be argued that the EU decision has come 5-8 years too late. While the fine and the instruction for discontinuation of antitrust activity may lead to better competition in the long run, Original Equipment Manufacturers (OEMs) will have to offer Google services in the short run in order to satisfy the consumer demand and to be competitive. Moreover, the consumer demand has been manipulated to a level where even if OEMs do not provide Google Services as part of the handset, consumers are likely to download these from the app stores in order to satisfy their needs.[8] All of this adds toward the gravity of the infringement committed, which is a relevant factor in deciding the amount of fine under the European Union policy.[9] (ii)The fine is miniscule compared to Google’s economic power Alphabet generated a turnover of €96.3 billion in 2017.[10] It also earned a net profit of €10.5 billion, despite incurring a fine of €2.42 billion in the Google Shopping case.[11] Before 2017, it had witnessed a rise of €2-3 billion a year in its profits.[12] This year, Google generated a profit of over €8 billion each in the third quarter alone.[13]Thus, Google will continue to be among the top 10 companies of the world in terms of profit, despite the fine.[14] Economic theorists and Behavioural analysts suggest that businesses today are becoming more and more risk averse.[15] This is due to increased professionalism, increased scale of operations, social factors like education and other means of social conditioning as a part of the modernized word today. Research suggests that the fines can be a great deterring factor for such risk averse management.[16] However, the way fines are calculated needs assessment. Under the European Union policy, there is first a calculation of a basic amount of fine, which may be adjusted depending on various mitigating or aggravating factors.[17] The calculation of the basic fine is based entirely on the value of sales, with consideration given to the gravity and duration of the infringement. Thus, as stated earlier, the fine calculated in the Google Android Case too, is one that is based on Google’s sales. It is important to note that while the amount of fine is unprecedented and may look massive prima facie, but for a company as big as Google, whether such a fine entails deterrence needs to be asked. There can be different ways of computing fines. One way can be to levy a fine on the basis of the company’s turnover, as done in this case. However, for a company like Google, where the profit margin is high,[18] such a fine may not be an effective deterrent.[19] An alternative to this approach can be seen in the form of a fine which is calculated on the basis of profits. Such a fine is better placed to be a deterrent as it can provide a constant impact which a sales or assets approach cannot.[20]More importantly, attacking the profits of a firm is a better measure especially for firms having a multidivisional structure, one like Google. While only one division may have committed the antitrust violation, a fine that attacks the profits generated cumulatively by all the divisions builds pressure on the company to restrict any such violation in the future.[21] ​(iii)Aggravating Factor This antitrust violation is the second offence by Google, after the Google Shopping Case. According to the EU policy, a basic fine may be adjusted according to various aggravating and mitigating factors. Repeat offence is an aggravating factor according to the policy,[22] and thus the fine should have been set taking this into consideration. (iv)Specific Increase for deterrence The European Union policy on setting of fines also provides for situations where the fine may be increased in order to increase deterrence.[23] In such instances, the fine imposed on undertakings which have a particularly large turnover may be enhanced in order to ensure greater deterrence. Moreover, the Commission shall also take into account the need to increase the fine in order to exceed the amount of gains improperly made as a result of the infringement. In the instant case, the network effects which have massively impacted the consumer behaviour and preferences need to be considered as improper gains accruing to Google due to its violations. This should lead to an increase in the amount of fine, which would result in the deterrence required. (v)Historic Perspective Microsoft Case[24] Twenty years ago, Microsoft lost the antitrust case against the government of the United States. The case revolved around the monopolization of the internet browser market by Microsoft, which was the world leader in the operating system market. Microsoft was selling its operating system and internet browser as a bundle, and this meant there was little to no opportunity for any other internet browser to have an impact on the market. At that time, the argument furthered by Bill Gates and a few others was that such antitrust regulations impede technological development. Little did they know, the regulations in fact proved to be a boon for innovation. Had this monopolization been allowed, competition would’ve been restricted in not only the browser market, but surely other markets as well. Who knows maybe Google as we know it today would’ve been a company not half as big as Bing, while today it surely leads the search engine market and is making antitrust headlines of its own. Google’s case is indeed similar to the Microsoft antitrust case as mentioned above, especially in relation to bundling. Some believe that the two cases are very different, however that debate is for another time. The point of contention here is whether the fine is an effective remedy in itself to limit behaviour that impeded competition. The two cases illustrate different remedies. In the Microsoft Case, the European Commission made sure that other options of browsers are provided to the consumers, thus making sure that the desired objective of more competition was realised. So, a direct instruction was given with regard to the steps needed for ensuring better competition in the market. In the Google Android Case however, such steps have not been taken and a mere instruction for discontinuation of the violative conduct has been made. This alone cannot be an effective deterrent. Google Shopping Case[25] In this case, there was an allegation that google misused its dominant position in the general search engine market to gain competitive advantage by placing its own comparison shopping service more prominently. Google was thus fined €2.42 billion by the European Commission. The fine however, has not been as effective as it was thought to be. The end has not been achieved as effectively as it was hoped, which was to allow greater competition in the comparison shopping market and to protect the interest of smaller competitors. This is significant from the fact that still, only 6% of the slots available on the European version of Google’s search engine are taken by the rivals to Google’s comparison shopping service. A remedy that could’ve solved the problem here was to create a clear distinction in the comparison shopping services, by dividing the visible space into two parts – one showing Google’s shopping service and the other showing the alternatives. However, this was rejected. Due to no particular prescription of a remedy, Google now auctions the space for these shopping service providers to appear alongside the merchant websites, which leads to more and more revenue for Google. The rejected seems to be the fairest of all here. However, all of this leads to the conclusion that a fine alone may not be an effective deterrent, and there is a need for an equitable remedy to be prescribed in clear terms. Conclusion The culmination of all this analysis is that there has to be something which disincentivizes Google from undertaking any such activities in the future where competition is hampered, and thus acts as a deterrent. The European Commission could do this in a number of ways. A few things that have been suggested in this regard can be - compelling Google to allow competing app stores to distribute its apps, which would make it easier for other firms to launch competing app stores. Another option would be to give consumers a choice, when they first boot up their phone, over which apps they want to use in default. All of this, along with an assessment of fines based on aforementioned recommendations, can go a long way in ensuring better competition in the market. *Singh is a IV Year B.A. LL.B (Hons.) student and Gupta is a II Year B.A. LL.B (Hons.) student at National Law School of India University, Bangalore. [1]Case AT.40099 – Google Android. [2] Commission sends Statement of Objections to Google on comparison shopping service; opens separate formal investigation on Android  (2015) accessed 24 May 2019. [3] Commission fines Google €4.34 billion for illegal practices regarding Android mobile devices to strengthen dominance of Google's search engine (2018) accessed 24 May 2019. [4]ibid. [5]George Stigler, ‘The Optimum Enforcement of Laws’, Essays in Economics of Crime and Punishment 56 (William H Lande& Gary S. Becker (Ed. UMI,1974) . [6]Google’s Android fine is not enough to change its behaviour The Economist (19 July 2018) accessed 24 May 2019. [7]The EU fining Google over Android is too little, too late, say experts The Guardian (18 July 2018) accessed 24 May 2019. [8]ibid. [9]Guidelines on the method of setting fines imposed pursuant to Article 23(3)(a) of Regulation No. 1/2003 (2006) . [10]Google posts its first $100 billion year CNN Business (1 February 2018) accessed 24 May 2019. [11]ibid. [12] CNN Business (n 10). [13]Google’s Parent, Alphabet, Misses on Q3 Revenue But Rakes in $9.2 Billion Net Profit (25 October 2018) accessed 24 May 2019. [14] The Fortune 500's 10 Most Profitable Companies The Fortune (7 June 2017) accessed 24 May 2019. [15]William Breit and Kenneth G. Elizinga, ‘Antitrust Penalties and Attitudes towards Risk: An Economic Analysis’ 86 Harvard law Review (1973) 693, 704. [16]ibid 706. [17]Guidelines on the method of setting fines imposed pursuant to Article 23(3)(a) of Regulation No. 1/2003 (2006) < https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52006XC0901(01)&from=EN>. [18]Alphabet Net Income 2006-2019 | GOOG ; Google's 5 Key Financial Ratios (GOOG) ; Earnings Estimates accessed 24 May 2019. [19]Kenneth G. Elzinga& William Breit, The Antitrust Penalties: A Study in Law and Economics 134 (Yale University Press, London, 1977). [20]ibid 134. [21]Breit and Elzinga (n 15) 712. [22]Guidelines on the method of setting fines imposed pursuant to Article 23(3)(a) of Regulation No. 1/2003 (2006) . [23]Guidelines on the method of setting fines imposed pursuant to Article 23(3)(a) of Regulation No. 1/2003 (2006) . [24]Microsoft Corp v Commission (2007) T-201/04. [25]CASE AT.39740 Google Search (Shopping) .