The AI Impact Summit 2026, held recently, signified a pivotal transformation in the global discourse on artificial intelligence, shifting focus from mere model launches and pilot initiatives to critical discussions surrounding governance frameworks, long-term capital investments, and the readiness of institutions to embrace AI technologies. India emerged as a significant contributor to this dialogue, positioning itself as a leading voice from the Global South in the crafting of AI regulations while advocating for a principles-based, risk-calibrated approach instead of a singular, comprehensive AI law.
A central theme of the summit was India’s strategy of managing AI through existing legal frameworks and targeted amendments rather than creating an expansive standalone statute. Akshaya Suresh, a partner at JSA Advocates and Solicitors, highlighted that the government’s AI Governance Guidelines and a 2026 white paper from the Office of the Principal Scientific Adviser reflect a “techno-legal approach combining legal instruments, rule-based conditioning, regulatory oversight, and technical enforcement mechanisms embedded within the architecture by design.” This method, she noted, minimizes overlapping compliance burdens that could hinder innovation, which is especially crucial for a developing economy focused on scaling AI adoption.
In contrast to the European Union’s prescriptive AI Act, India’s approach emphasizes a principles-based system aligned with risk and harm considerations. Suresh articulated that India is “moving toward a principles-based, risk-harm-calibrated framework rather than a hard regulatory regime,” in line with the New Delhi AI Impact Declaration’s focus on fostering inclusive and human-centric AI. This strategy prioritizes accountability, safety, and innovation, allowing regulations to evolve in accordance with the maturity of real-world AI applications.
While a standalone AI law is not yet in place, compliance with current regulations is non-negotiable. Existing statutes like the Information Technology Act and Intermediary Guidelines apply to areas such as synthetic media and platform liability. Suresh emphasized that voluntary governance mechanisms—including transparency reports, fairness testing, security reviews, and red-teaming—are expected to “develop into binding regulations in tandem with the ecosystem maturing.” For startups, the recommended trajectory involves adherence to existing laws while progressively adopting voluntary risk controls, particularly for high-impact AI systems.
The summit also underscored that achieving AI leadership necessitates substantial investments in infrastructure, including compute capacity, data ecosystems, and advancements in semiconductors and cloud technology. The message resonated throughout the event: competitive AI ecosystems are established on long-term capital rather than short-term applications.
Moreover, discussions concentrated on the importance of AI literacy, reskilling initiatives, and domain-specific training, alongside operational deployments in sectors such as healthcare, agriculture, and public services. This marks a significant transition from mere experimentation to scaled implementation of AI technologies. The summit’s outcomes suggest a future where AI governance aligns closely with national interests and international collaboration, shaping a landscape that fosters innovation while addressing the complexities of technological advancement.
See also
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