Introduction
A pricing algorithm does not need to call a rival to fix a price. It only needs to watch, learn and adjust. That shift from collusion as something people do to something software can produce on its own is what makes AI driven digital markets such an uncomfortable subject for competition lawyers. The Competition Commision of India’s market study on artificial intelligence, released in October 2025, found that more than a third of surveyed startups already feared algorithm led coordination among bigger rivals. This article discusses everything about Competition Concerns in AI Driven Digital Markets and it also argues that India’s Competition Act, 2002 remains flexible enough for conventional digital competition disputes but is institutionally and structurally inadequate for harms that are distinctly AI driven because the evidence the law demands, the timing at which it intervenes and the expertise it assumes were built for a slower, more visible kind of market. AI now decides what price a customer sees, which seller appears first and which startup gets quite bought out before it becomes a threat. What follows traces that argument through the structure f these markets, the harms they create, the Act’s record so far, comparable approaches abroad and the reform still needed.
Understanding AI Driven Digital Markets
Meaning and Characteristics of AI Driven Markets
An AI driven digital market is one where machine learning systems rather than human judgement alone, shape pricing, ranking and credit decisions. These markets reward scale, since more users generate more data, training better algorithms that attract still more users. Combined with network effects and self learning pricing tools, they can tip toward a single dominant player faster than a regulator built around written agreements is equipped to notice.
Growth of AI Based Platforms in India
India is living through this shift not observing it from a distance. AI now sits inside ecommerce recommendation engines, fintech credit scoring, digital advertising, healthcare diagnostics and ride hailing. The CCI’s 2025 study records India’s AI market roughly doubling between 2020 and 2024, from about USD 3.2 billion to USD 6 billion. What should concern a competition lawyer is where this concentrates: control over data and computing infrastructure sits with a handful of firms, so the asset worth fighting over is a dataset, not a factory.
Competition Concerns in AI Driven Digital Markets
Market concentration and Dominance
Acess to large datasets creates market power that is hard to dislodge once it exists. A platform that captured users early gets a permanent head start, because its algorithms have more to learn from, and that advantage compounds rather than fades.
This matters because Section 4 asseses dominance largely after the fact, by which point the data advantage has usually hardened into something close to permanent.
Algorithmic Collusion
Algorithmic collusion describes pricing software that aligns prices across competitors without explicit human agreement, through tacit coordination each system reaches independently. The CCI’s AI study points to the US Topkins prosecution and the EU’s E Turas ruling as the clearest precedents, and tellingly neither comes from an Indian Tribunal. No Indian authority has tested Section 3 against a purely algorithmic case, and that absence is itself a gap: the provision assumes an agreement between people and a “meeting” between two pieces of code resists that kind of proof almost by definition.
Abuse of Dominant Position
AI sharpens a dominant firm’s ability to abuse its position. Predatory pricing becomes easier to calibrate when algorithms track rivals in real time, and self preferncing becomes harder to catch when the ranking logic sits inside a system nobody outside the system can audit. Indias clearest test came in the Google Android matter: the CCIs 2022 order found Google had abused its dominace across five relevant markets and imposed a penalty of roughly INR 1337 crore for tying its app suite to android licensing a finding the NCLAT largely upheld in Google LLC v. Competition Comission of India 2023. But that conduct was visible and contractual, self preferencing buried inside an algorithm leaves no comparable paper trail which is why a provision that worked against Google’s contracts may struggle against Google’s code.
Data Monopoly and Access to Data
Data increasingly functions like an essential facility: a firm without comparable data cannot compete on equal footing. A food delivery startup can build a better app and still lose simply because the incumbent already knows what customers order and what they will pay during a surge. The Act has no real concept of data as an asset requiring access remedies so this barrier cannot be removed by striking down a contract term, the way Indian competition law usually works.
Mergers and Acquisitions in Digital Markets
A “killer acquisition” is where a dominant firm buys a smaller rival to retire as a future competitor. India saw a version of this in the Zomato-Uber Eats deal, valued at roughly INR 2500 crore, which escaped CCI scrutiny entirely for falling below the thresholds then in force, a gap only legislative reform not interpretation could fix.
Overview of India’s Antitrust Framework
The Competition Act, 2002
The Competition Act 2002 replaced the older MRTP Act after the Raghavan Committee found India’s pre liberalisation regime unfit for a market economy. Its aims are to prevent anti competitive practices, sustain competition and protect consumer interests, language that never anticipates algorithms, so every AI related question must be argued by analogy.
Role of the Competition Commission of India (CCI)
The CCI investigates and enforces the Act, ordering investigations under Section 26, passing remedial directions under Section 27 and reviewing mergers under the combination provisions. Commissioning a dedicated AI study is itself an admission that the toolkit needed closer scrutiny.
Key Provisions Relevant to Digital Markets
Section 3 struggles with collusion that has no human handshake behind it. Section 4 has proved workable in the Android litigation, though largely against visible, contractual conduct. Sections 5 and 6 were widened through the deal value threshold because the original tests missed digital acquisitions that mattered. Together, these provisions tell one story: where conduct is visible, the Act adapts, where it is buried in code or escapes a threshold, it needs outside help.
Assessing the Adequacy of India’s Antitrust Framework for AI Markets
Strengths of the Existing Framework
The acts real strength is its technology neutral drafting so the CCI is never boxed into a pre AI definition of anti competitive conduct. Its abuse of dominance and combination provisions read flexibly, as the Android case shows and for conventional digital dominance disputes the toolkit has held up well.
Limitations in Addressing AI Driven Markets
The gaps surface where AI adds genuine novelty. There are no AI specific provisions, so cases are argued by analogy. Proving algorithmic collusion under Section 3 is difficult without a human agreement, and market definition turns slippery in multi sided markets where a service is free to one set of users and monetised through another. Most fundamentally, the framework is ex post: the CCI acts only after harm occurs, by which point a market may have tipped beyond repair.
Judicial and Regulatory Developments
The same Android litigation that confirmed the Act’s flexibility also exposed its ceiling. The NCLAT set aside several forward looking “gatekeeper” directions the CCI had issued holding that ex ante remedies sit outside what an ex post statute permits, citing the then emerging Digital Competition Law Committee report as proof such power needs fresh legislation. A related Play Store billing dispute saw the NCLAT trim the penalty while invoking the Supreme Court’s ruling in Excel Corp Care v. CCI that penalties must rest on relevant turnover, not total revenue, a limit unrelated to AI but telling about how cautiously tribunals police the Commission’s powers. Together these rulings confirm the pattern this article keeps tracing: courts validate the Act’s flexibility for conduct it was built to catch while denying the CCI power to act before a market has tipped.
Comparative Perspectives: Lessons from Other Jurisdictions
European Union
If India’s problem is timing, the EU has already chosen its answer: the Digital Markets Act identifies “gatekeepers” in advance against objective criteria and imposes fixed obligations before any harm is proven backed by fines of up to ten percent of global turnover.
United States
The American approach stays closer to traditional antitrust principles built around proving actual harm, though the FTC and Department of Justice have grown more assertive about algorithmic pricing. Unlike the EU or UK, the US has not adopted a dedicated ex ante statute.
United Kingdom
The UK’s Digital Markets, Competition and Consumers Act 2024 lets the Competition and Markets Authority designate firms with “Strategic Market Status” and impose bespoke conduct codes, including pricing algorithm transparency duties case by case.
Lessons for India
All three models share a belief that waiting for harm to fully materialise is costly in markets that tip quickly. India need not copy any one model, the information Technology and Innovation Foundation has warned that India’s digital sector shows growth rather than clear market failure and that EU style per se bans could punish legitimate product integration alongside genuine abuse. Even so, some capacity for earlier intervention, calibrated to India’s own conditions looks like the missing piece.
Need for Reform in India’s Competition Law Framework
Recognising Data as a Source of Market Power
Treating data access as a competition variable addresses the gap identified earlier. Mandated data portability, letting users move transaction history to a rival platform would lower the entry barriers that data concentration creates.
Addressing Algorithmic Collusion
Tackling algorithmic collusion needs evidentiary standards that do not depend on finding a human conversation since none exists yet in Indian practice. The CCI’s AI study proposes self audit frameworks documenting design logic and data inputs, alongside transparency duties explaining how algorithms influence outcomes without forcing disclosure of proprietary code.
Strengthening Merger Review Mechanisms
The deal value threshold under the Competition (Amendment) Act 2023 is the clearest reform so far requiring CCI approval for deals exceeding INR 2000 crore where the target has substantial business operations in India, regardless of size, directly answering the Zomato Uber Eats gap.
Introducing Ex Ante Regulation
The Committee on Digital Competition Law’s 2024 report proposed designating large “Systematically Significant Digital Enterprises” bound by obligations such as no self preferencing. As of the latest parliamentary update in August 2025, the government has paused this to reassess thresholds, leaving the policy direction settled but the legislative vehicle stalled.
Capacity Building and Institutional Strengthening
None of this matters without people who can use it. The CCI’s AI study calls for technical expertise in data science within the Commission, closer coordination with regulators such as MeitY and deeper cooperation with bodies like the OECD. A law for AI driven digital markets is only as good as the regulator’s ability to read the algorithm in front of it.
Balancing Innovation and Competition in the Age of AI
None of this argues for regulating AI driven digital markets into stillness. India wants its AI sector to grow without compliance obligations built for global tech giants, and aggressive ex ante rules risk catching fast growing startups in a net meant for someone else. But doing nothing has its own cost since markets that tip irreversibly tend to stay tipped. The CCI’s light touch posture leaning on self audits and advocacy is a reasonable attempt to thread that needle while the technology is still too young to legislate with full confidence.
Conclusion
So, is India’s antitrust framework adequate for AI driven digital markets? The honest answer is split and that split is the real finding here. Against conventional digital dominance, the Act has proved genuinely capable: a 2002 statute reaching a multi billion rupee penalty against one of the world’s largest technology companies as the Google Android litigation shows, is no small achievement. But against conduct that is distinctly AI driven, tacit algorithmic pricing, self preferncing buried in code and acquisitions designed to retire a threat before it grows, the same framework keeps hitting the same wall: it can only act once harm is visible and already done. The deal value threshold shows Parliament can close such gaps when it chooses to, the stalled Digital Competition Bill shows the bigger fix is recognised not abandoned. India needs a sequenced response, not a wholesale import of Brussel’s rulebook: sharper merger review now, calibrated ex ante tools once thresholds are right sized and a regulator able to read an algorithm rather than wait for it to be explained. Until that sequencing happens, India’s competition law will keep winning the cases that involve a contract, and keep losing the race against the code.
Frequently Asked Questions
- What are AI driven digital markets?
These are markets where algorithms and data driven systems rather than human decisions alone, set prices, rankings and recommendations.
- Why do AI driven markets raise competition concerns?
They concentrate power around whoever holds the most data, make collusion possible without human agreement, and let dominant firms self preference through hard to audit code.
- Is the Competition Act 2002 suficient to regulate AI driven markets in India?
It handles conventional digital dominance reasonably well as the Google Android case showsbut strugles with algorithmic collusion and cannot act before a market has already tipped.
- What reforms are required to strengthen competition regulation in AI driven digital markets?
India needs sharper merger scrutiny calibrated ex ante obligations for large platforms clearer data govrnance and a CCI with stronger in house technical capacity.
About the Author
Prisha Chaudhry is pursuing B.B.A. LL.B. (Hons.) at Jindal Global Law School, O.P. Jindal Global University, Sonipat. She is a keen legal researcher and writer with a discerning interest in competition law, corporate law, technology law, and the regulation of digital markets. With a sharp eye for emerging legal and regulatory developments, she enjoys examining the evolving intersection of law, policy, and innovation through analytical and research-driven scholarship. Her work focuses on contemporary commercial and regulatory issues, with an emphasis on developing nuanced perspectives on the legal challenges arising from technological advancement and evolving market practices.
References
- Competition Commission of India, Market Study on Artificial Intelligence and Competition (October 2025):
- Ministry of Corporate Affairs, Report of the Committee on Digital Competition Law (March 2024):
- Regulation (EU) 2022/1925 on contestable and fair markets in the digital sector (Digital Markets Act), European Commission: