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On October 6, 2025, the Competition Commission of India1 (CCI) released its extensive "Market Study on Artificial Intelligence and Competition,"2 a pivotal report created in partnership with the Management Development Institute (MDI) in Gurgaon.This timely analysis investigates the transformative impact of AI on India's rapidly growing digital economy, forecasting that the domestic AI market will escalate from USD 6.05 billion in 2024 to USD 31.94 billion by 2031, reflecting a compound annual growth rate (CAGR) of 39-43%.On a global scale, the sector is anticipated to surpass USD 1 trillion by 2031.The study, which utilises secondary data and surveys 106 stakeholders, including 50 AI start-ups, 30 user firms from industries such as retail and BFSI, four investors, and 11 legal experts highlights AI's dual-edged effects: promoting innovation and efficiency while presenting risks of market concentration and anti-competitive behaviours.For enterprises, this report serves as a wake-up call to leverage AI's competitive advantages while carefully navigating the regulatory challenges posed by India's evolving legal landscape.This article examines the study's crucial findings, implications for businesses, industry viewpoints, and regulatory frameworks, providing actionable insights for companies looking to excel in an AI-driven environment.
The AI Ecosystem and Sectoral Applications: Foundations of Transformation
The report maps the AI ecosystem as a multi-tiered structure comprising data, computing infrastructure, model creation, fine-tuning, deployment, user engagement, and governance which is predominantly influenced upstream by global hyperscalers such as NVIDIA, AWS, and Google, while Indian start-ups thrive in downstream applications.Valued at USD 45 billion in 2023, India's semiconductor industry is projected to reach USD 21 billion for AI by 2030, supported by initiatives such as the IndiaAI Mission's allocation of INR 10,300 crore for enhanced compute access and skill development.
In various user sectors, the pace of AI adoption is quickening, with 90% of the surveyed companies employing it for monitoring customer behaviour and 69% for forecasting demand.Retail and e-commerce are at the forefront, utilising AI for personalised recommendations, dynamic pricing, and inventory optimisation and are expected to surge from USD 0.86 billion in 2024 to USD 15.7 billion by 2032.Numerous examples illustrate this trend: BigBasket's barcode-free identification and Myntra's social media-driven product launches have elevated customer engagement by 79%, enhancing loyalty and profitability by as much as 20%.The logistics sector reaps the rewards of route optimisation, which cuts transit times by 20% and costs by 15%, as demonstrated by Flipkart's use of predictive analytics.The BFSI sector harnesses AI for fraud detection and robo-advisory services, with its AI market projected to expand to USD 33.68 billion by 2032.Healthcare, the quickest to grow at a CAGR of 43.5%, applies AI for diagnostics and personalised treatments, effectively reducing adverse effects through the analysis of genetic data.
These applications highlight the pro-competitive potential of AI: 68% of users indicate enhanced prediction accuracy, 52% experience significant efficiency improvements, and 62% find it easier for MSMEs to enter the market through scalable solutions like open-source ML frameworks.However, the study cautions about potential risks, including a 48% dependence on third-party AI applications, which may create reliance on established players.
Business Implications: Opportunities, Risks, and Competitive Advantages
For businesses, AI serves as a potent tool for achieving competitive differentiation, facilitating cost reductions of 20-30%, real-time decision-making, and hyper-personalisation.Early adopters in e-commerce realise a 20% increase in profitability through dynamic pricing algorithms that adjust in real-time according to demand and consumer behaviour.In logistics, AI-driven automation such as Amazon's fleet of over 200,000 robots significantly reduces inventory errors and improves visibility, providing agility in fluctuating supply chains.BFSI companies that utilise machine learning for credit risk evaluation streamline their operations, building trust and increasing market share among underserved demographics.
However, the implications are twofold.Positive competitive effects include decreased market concentration and empowered MSMEs that automate resource-heavy tasks to level the playing field against larger competitors.The study's survey indicates that 34% experienced moderate and 52% noted substantial improvements in competitiveness, particularly in customer interactions. Nonetheless, significant risks persist: Algorithmic collusion, where self-learning models inadvertently synchronise prices without human oversight, raises concerns for 37% of start-ups, reflecting global instances such as the EU's E-TURAS penalty for algorithm-enforced discount limits.Price discrimination and predatory pricing may undermine consumer trust, particularly in low-competition markets, potentially resulting in increased long-term prices following the exit of competitors.
Further, entry barriers intensify these challenges: 68% of start-ups identify data scarcity as an obstacle, with 60% recognising the data advantages held by incumbents; talent shortages impact 61%, and funding difficulties affect 56%.Network effects and substantial computing costs reinforce the position of hyperscalers, which could hinder innovation.Mergers such as Flipkart's acquisition of Liv.ai indicate expansion but attract scrutiny regarding conglomerate practices.Companies need to consider these factors as non-adopters face the risk of becoming obsolete and losing their personalised advantages, while excessive dependence on closed-source models leads to potential lock-in.The overall consequence?AI enhances the advantages of first movers but requires careful risk management to prevent regulatory repercussions and exclusion from the market.
Stakeholders' Perspective: Industry Voices in AI Arena
Industry participants, including start-ups, user companies, investors, and specialists, provide intricate perspectives on the competitive landscape of AI.User sectors such as retail and e-commerce, which have a 24% adoption rate, praise AI for contributing to 69% accuracy in demand forecasting and 27% accuracy in supply chain oversight, yet theyobjectthe compliance deficiencies, 91% acknowledge adoption but advocate for government data repositories to ensure equitable access.Stakeholders in BFSI and healthcare highlight the importance of ethical AI to eradicate biases in fraud detection and diagnostics, seeing it as a means to build trust alongside substantial efficiency improvements of 52%.Start-ups, which account for 67% of application-driven firms, view AI as a great equaliser but face challenges: 70-92% report issues with data access and 62% indicate a shortage of skilled talent.They support the use of open-source solutions and synthetic data to compete with the 60% data advantage held by established players, cautioning that exclusive alliances can increase costs for competitors.Investors emphasise that mergers and acquisitions can stimulate innovation but warn against the risks of consolidation, with 50% noting challenges in securing next-level funding: 44% depend on angel investors, highlighting a significant reliance on venture capital.Legal professionals, with 94% perceiving the Competition Act as flexible, advocate for enhancing the capacity of the CCI in algorithmic assessments, improving coordination among regulatory bodies, and establishing sandboxes similar to those in the EU, to cultivate a "dynamic ecosystem."
Overall, industries are leaning towards self-regulation: 93% of AI platforms adhere to international standards such as ISO 42001 for transparency, prioritizing case-specific enforcement rather than universal regulations.MSMEs, which benefit from the targeted scalability of AI, still grapple with concerns over predatory pricing, prompting the need for subsidies in Tier-2/3 cities.These viewpoints illustrate AI as a catalyst for inclusive growth, provided that obstacles are removed, resonating with the study's appeal for balanced oversight to avert monopolistic practices.
India's Legal and Regulatory Framework
India's regulatory system, grounded in the Competition Act of 2002, effectively confronts AI-related challenges through restrictions on anti-competitive agreements (Section 3), dominance abuse (Section 4), and mergers (Sections 5-6).The 2023 Amendment Act enhances this framework by recognising hub-and-spoke cartels (Section 3(3)), establishing deal-value thresholds (INR 2,000 crore for mergers), and introducing settlement mechanisms, which specifically address algorithmic collusion and AI acquisitions.The CCI's investigations into major tech firmsillustrate enforcement efforts, alongside the IT Act of 2000 and the Intermediary Guidelines of 2021, which govern data management.
The DPDP Act of 2023 requires lawful data processing, reducing exploitative discrimination, while the anticipated Digital Competition Bill (2024) proposes ex-ante regulations for Systemically Significant Digital Enterprises, akin to the EU's DMA, to prevent self-preferencing.Broader initiatives, such as NITI Aayog's #AIForAll strategy, the National AI Portal, and MeitY's AI Governance Guidelines set for January 2025, adopt a harm-based, consultative strategy shaped by over 100 public contributions.The draft National Data Governance Framework (2022) encourages data sharing to reduce obstacles.
Drawing inspiration from global frameworks such as the US NIST guidelines on bias, the UK's DMCC Act addressing gatekeeper roles, and the OECD's ex-ante instruments, India's approach strives to balance innovation with public welfare, steering clear of excessive regulation.Companies must embrace compliance: conducting self-audits for algorithmic transparency under the DPDPA, notifying mergers that surpass thresholds, and adhering to ethical standards to lessen potential fines (up to 10% of turnover).This regulatory framework positions India as a leader in AI, aligning with GPAI to meet international standards.
Legitpro's take
The research culminates in a comprehensive action plan involving multiple stakeholders, encouraging CCI to organise workshops focused on AI compliance, enhance technical proficiency in data science, and establish MoUs with MeitY. Businesses are encouraged to perform self-assessments across six key areas i.e. governance, testing, and monitoring and utilising the report's checklist to identify biases or favouritism towards affiliates.The government should increase subsidies for the IndiaAI Mission, while fostering international collaboration through ICN/OECD to track global advancements.
These initiatives promise to create a vibrant ecosystem: Dismantling obstacles could release between USD 17-22 billion in AI value by 2027, enabling industries to innovate in a responsible manner.CCI's study serves as a framework for competition enhanced by AI in India, integrating opportunities such as 43% sectoral compound annual growth rates with protections against collusion and impediments.Companies that gain competitive advantages through personalisation must emphasise compliance within a framework that is evolving due to amendments in 2023 and the DPDPA.As stakeholders come together for transparency, India can achieve #AIForAll, thus, promoting inclusive growth while maintaining fairness.The responsibility lies with enterprises: Audit, adapt, and progress.
Footnotes
1. Competition Commission of India Releases Market Study Report on Artificial Intelligence and Competition conducted through Management Development Institute Society (MDIS). (n.d.).
2. CCI Market study on AI and competition. (n.d.).
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