The rapid proliferation of artificial intelligence (AI) technologies across industries has triggered an intense global debate regarding the appropriate legal architecture required to govern such systems. Jurisdictions across the world have adopted varying approaches ranging from the European Union’s comprehensive AI Act to the largely market driven, sector specific oversight model visible in the United States. Against this evolving international backdrop, an important question arises for India, is the country moving towards a dedicated standalone AI statute, or will sectoral regulation supported by existing legal frameworks suffice, especially from the point of view that Artificial intelligence today is no longer confined to experimental research environments or niche technological application. It has rather become deeply embedded in the operational fabric of modern economies. AI systems increasingly participate in decisions and this expansion in its footprint has inevitably raised complex legal and regulatory questions concerning accountability, transparency, data governance, liability, and ethical deployment of automated systems.
Across the world, policymakers are grappling with the challenge of designing regulatory regimes that can simultaneously address technological risks while preserving the enormous innovation potential associated with AI. The European Union has adopted a comprehensive and prescriptive framework through the EU Artificial Intelligence Act, which introduces a risk-based classification of AI systems and imposes strict compliance obligations on high-risk AI applications. The United States, by contrast, has largely relied on sector-specific regulation and executive policy initiatives rather than a single overarching statute. Other jurisdictions such as the United Kingdom, Singapore, and Japan are experimenting with flexible governance models centred on principles, regulatory sandboxes, and industry standards.
Amidst this backdrop, the Indian governance structure and the regulatory ecosystem is developing through a combination of existing digital laws, policy guidelines, and sector-specific regulatory oversight rather than a conventional biblical laws on a subject matter. This approach reflects a deliberate policy choice by the Indian government to adopt a principle driven and incremental regulatory strategy, rather than imposing an immediate omnibus legislative framework similar to the EU AI Act. The regulatory philosophy appears to prioritise innovation, technological adoption, and economic competitiveness while gradually embedding accountability and risk-mitigation mechanisms within the existing legal infrastructure. This strategy is significant because the country simultaneously occupies multiple roles within the global AI ecosystem. It is a large consumer market for AI driven technologies, a rapidly expanding hub for AI development and research, and a jurisdiction with complex socio-economic realities. This regulatory preference shapes the domestic innovation and investment in congruence with the broader governance architecture for emerging technologies in the Global South.
While the Digital Personal Data Protection Act, 2023 (DPDP Act), functions as the foundational framework governing the processing of personal data in the digital ecosystem and the same is not AI-specific, its provisions do have implications for AI systems, particularly those reliant on large datasets for training, prediction, and decision-making. In practical terms, many AI systems, especially those that process behavioural, biometric, or personal information, will need to comply with these data protection obligations. Consequently, data governance laws effectively serve as the first layer of regulatory oversight for AI deployments in India.
Alongside statutory law, the Ministry of Electronics and Information Technology (MeitY) has begun shaping India’s AI governance discourse through policy instruments and advisory frameworks. Various governmental initiatives emphasise the concept of “responsible AI”, focusing on core principles such as transparency, fairness, safety, explainability, and human accountability in algorithmic decision-making. These policy frameworks also contemplate the establishment of institutional mechanisms such as expert committees, AI governance bodies, and safety oversight institutions that could guide the development and deployment of AI technologies across sectors. Importantly, these initiatives are intentionally framed as guidance-oriented governance tools rather than rigid regulatory mandates, thereby allowing policymakers to observe technological developments before imposing binding statutory obligations.
Another defining feature of India’s regulatory trajectory is the increasing reliance on sectoral regulators to address AI-related risks within their respective domains. Instead of regulating AI as a single technological category, policymakers appear inclined to regulate AI applications in context, for example, algorithmic credit assessment in financial services, AI-assisted diagnostics in healthcare, predictive analytics in telecommunications, or automated decision-making in digital platforms. Sector specific regulators such as the Reserve Bank of India (RBI), the Securities and Exchange Board of India (SEBI), the Telecom Regulatory Authority of India (TRAI), and healthcare regulators are therefore likely to play a critical role in shaping operational standards for AI within their respective industries. This model allows regulators to account for the unique risk profiles and compliance requirements associated with each domain.
The preference for a sectoral approach is also influenced by structural and economic considerations. Artificial intelligence is a generic purpose technology whose applications span multiple sectors, including finance, manufacturing, logistics, healthcare, media, and public governance. An attempt to even regulate such a broad technological domain through a single comprehensive statute, may risk creating rigid frameworks that quickly become outdated as technologies evolve. In contrast, sectoral regulations allows policymakers to craft context sensitive compliance mechanisms, addressing specific risks such as algorithmic bias in credit scoring, automated medical decision-making, or AI-driven surveillance practices.
From a policy perspective, India’s relatively cautious approach is also closely linked to its economic and technological ambitions. The country seeks to position itself as a global hub for AI innovation, research, and deployment, supported by a rapidly expanding digital economy and a vibrant startup ecosystem. Introducing a heavily prescriptive regulatory regime at an early stage could potentially discourage investment, slow down experimentation, and impose compliance burdens on emerging enterprises. As a result, policymakers appear inclined to adopt an approach which calls for regulate only when it is necessary, keeping a guardian oversight, while the innovation ecosystem matures before introducing more stringent statutory controls. The absence of a standalone AI statute is not indicative that India may permanently rely on a fragmented sectoral oversight. Over time, as AI systems become more deeply integrated into critical sectors and public infrastructure, the demand for uniform governance standards may intensify. Issues such as algorithmic transparency, liability for automated decision-making, accountability for generative AI outputs, and safeguards against systemic bias will likely require harmonised regulatory responses that transcend sectoral boundaries. In such telling circumstances, India will have to gradually introduce targeted legislative amendments, regulatory codes, or ascertain the risk potentials in AI classifications, even if it does not enact a single comprehensive AI law.
In evaluating the merits of the current trajectory, India’s emerging framework can best be understood as a hybrid regulatory model. Rather than choosing between a strict standalone statute and entirely decentralised sectoral governance, the country appears to be constructing a layered system, incorporating data protection law, sector specific regulatory oversight, policy guidelines on responsible AI, and evolving jurisprudence through capable regulators who understand technology. Such a framework offers a degree of regulatory flexibility while enabling the gradual incorporation of safeguards as technological risks become clearer.
The technological renaissance has shifted in its very essence as last witnessed by the world. In this stage of flux, from the technological perspective, where the new world order is yet to be determined, India’s approach can be defined as a calibrated and adaptive governance, structured to combine sectoral regulation, data protection frameworks, and principle-based policy guidance. This approach reflects a pragmatic attempt to balance innovation with accountability in a rapidly evolving technological landscape. Over time, however, the effectiveness of this model will depend on the ability of regulators to understand technology, how the technology is shaping from the social impact perspective and the ability of the lawmakers to introduce clear standards for transparency, liability, auditability, and algorithmic accountability.
