Krishnan pitches AI Summit as Global South blueprint for AI governance

S. Krishnan is using the India AI Impact Summit 2026 to codify how India wants AI to be built, governed and traded—with a deliberate Global South lens and a strong continuity from Digital India to IndiaAI Mission and the semiconductor push. Rather than treating the summit as a generic tech show, he is framing it as India’s “DPI moment” for AI: a place where principles, infrastructure, chips and governance are stitched together and translated into pilotable programmes, playbooks and standards that other countries can reuse.​

Krishnan’s recurring theme in pre‑summit interactions is “democratizing AI”: opening access to compute, models and datasets so a handful of firms or jurisdictions do not dictate who can innovate and on what terms. That links directly to MeitY’s IndiaAI Mission architecture—public compute, open and curated datasets, multilingual LLMs, startup funding and capacity‑building—where AI for governance, health, agriculture and languages is treated as a public good, not just a private product.​

On governance, he is arguing for shared, interoperable global norms that are risk‑based and innovation‑friendly, rather than copy‑pasting heavily prescriptive Western regimes that could lock Global South players out of frontier research and commercial deals. India’s pitch—reflected in MeitY’s own AI advisories and the summit tracks—is to couple “do no harm” and human‑centric AI with agile, iterative oversight, building on its experience with Aadhaar, UPI, DigiLocker and other digital public infrastructure that already operate at population scale.​

Krishnan is also using the Summit to tie AI into supply chains and jobs: panels and working groups extend beyond models and safety into semiconductor fabrication, design, and the digital skilling needed to make India a trusted, neutral node in AI hardware and software value chains. Initiatives clustered around the event—such as Udaan pitch fest (startups), YuvaAI (youth and skilling) and AI by HER (women in AI)—are meant to anchor talent pipelines and ensure the “AI dividend” is widely spread, rather than captured solely by a thin layer of big tech and elite researchers.​

CT Bureau