India’s ‘Third Way’ Redefining Global AI Governance

Syllabus: GS2/Governance; GS3/Science & Technology

Context

• As the AI Impact Summit unfolds in New Delhi, global leaders, policymakers, and technology experts are conscious about governing artificial intelligence (AI) for promoting innovation and managing its real and unknown risks.
• India is positioning itself as offering a ‘Third Way’, an alternative AI governance model distinct from those of the world’s major AI powers.

About AI Governance

• AI governance is about balancing innovation with protection, ensuring AI systems improve society without undermining rights, security, or economic stability.
• It refers to the rules, policies, standards, and institutions that guide how artificial intelligence (AI) is developed, deployed, and monitored to ensure it benefits society while minimizing risks.

Global Governance Divide

• Different regions have adopted sharply contrasting AI governance strategies:
  • European Union: A compliance-heavy, risk-classification regime under the AI Act, emphasizing strict regulatory oversight.
  • United States: A largely market-driven, innovation-first approach with sectoral guidance rather than centralized AI legislation.
  • China: A centralized, state-directed governance structure with strong control over data and algorithm deployment.
• Each model reflects its own economic structure and political traditions. These frameworks do not easily transfer to the realities of the Global South, where digital infrastructure, institutional capacity, and development priorities differ significantly.

India’s Distinct Governance Approach

• Governance Framework: India has released its AI governance guidelines that integrates adoption and diffusion of AI, risk mitigation, capacity-building, international diplomacy, and public-private collaboration.
  • It works within existing legal structures such as the Information Technology Act, 2000, and related digital rules, instead of creating entirely new regulatory architecture.
  • Priority sectors include healthcare, agriculture, education, and public administration. It aligns with India’s broader digital public infrastructure strategy, as seen in platforms like Aadhaar, UPI, and DigiLocker.
• First-of-Its-Kind Disclosure Rules: Recently, the government amended the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules to mandate labeling of AI-generated content that harmful content takedown within a three-hour window.
  • It marks one of the first national-level mandates globally requiring explicit AI-generated content disclosure.
  • However, enforcement presents challenges like policing global technology giants, ensuring compliance at scale, balancing regulation with democratic freedoms, and coordinating across jurisdictions.
  • Implementation risks becoming fragmented, without international cooperation.

Key Issues with India in AI Governance

• Innovation Without Protection: A framework that accelerates AI adoption without protecting workers displaced by automation, mandating transparency from AI developers, protecting whistleblowers, safeguarding vulnerable communities, and promoting public awareness and digital literacy etc risks replicating the same imbalances already visible among AI superpowers.
• Regulatory Gaps and Fragmentation: India has not enacted a standalone AI law. Instead, it relies on the Information Technology Act, 2000, the Digital Personal Data Protection Act, 2023, and amendments to intermediary rules.
  • It creates ambiguity about liability, overlapping enforcement responsibilities, and unclear compliance expectations for companies.
• Data Governance & Privacy Concerns: AI systems depend heavily on data. Although India passed the Digital Personal Data Protection Act, 2023, concerns remain about broad government exemptions, weak independent oversight mechanisms, and limited clarity on algorithmic profiling.
  • Without strong privacy enforcement, AI development could increase risks of surveillance or misuse.
• Worker Displacement & Social Protection: AI adoption affects IT services, customer support, administrative roles, and gig economy platforms. India lacks a comprehensive AI-linked workforce transition policy.
  • Key gaps reskilling frameworks at national scale, social safety nets for displaced workers, and sector-specific automation impact assessments.
• Infrastructure & Compute Dependence: Advanced AI development requires High-performance computing (HPC), semiconductor access, and large-scale data centers.
  • India still relies significantly on foreign cloud providers, imported chips, external foundational models, limiting strategic autonomy and bargaining power in global AI governance.
• Bias & Socio-Cultural Complexity: India’s diversity creates unique AI risks like language diversity (22+ official languages), caste and social bias, and regional inequalities.
  • AI systems trained on global datasets may not reflect Indian realities, leading to discriminatory outcomes.
• Supremacy of Global North: AI investment remains heavily concentrated among a small group of private firms in the Global North.
  • It creates dependency on proprietary systems, limited bargaining power for developing nations, contextual risks poorly understood by external developers, and barriers to local innovation ecosystems.
• Limited Global Coordination Mechanisms: India advocates Global South coordination, but no formal multilateral AI safety alliance yet exists among middle powers;
  • AI standards are still largely shaped by US-EU dynamics;
  • Cross-border enforcement remains weak.

Way Forward

• India’s ‘Third Way’: It emphasizes strategic autonomy, localized governance models, public-private partnerships, shared safety evaluation frameworks, and collaborative research networks among emerging economies.
  • Inclusive AI governance needs to incorporate social protection, labour transition strategies, and accountability mechanisms, not merely innovation scaling.
  • Without these safeguards, the ‘Third Way’ could become a faster route to instability rather than resilience.
• AI Governance Across the Global South: The coming year will determine whether India can successfully integrate innovation, national security, economic development, and human welfare.
  • If successful, the ‘Third Way’ could become a template for AI governance across the Global South.
• Strategic Opportunity: The AI Impact Summit offers India a chance to shape global coordination among middle powers, distribute AI gains more equitably, build shared research and safety infrastructure, and position itself as a hub for agile, collective governance.
  • For countries seeking development pathways aligned with their institutional capacities and strategic interests, India’s model holds real appeal.

Source: TH