BRICS Must Tackle AI Divide Defining 74 Years of the 21st Century

For AI researchers, product leaders, and regulators, Tewari's warning is a geopolitical red flag: if frontier AI innovation stays concentrated in a handful of Northern labs, most of the world becomes a consumer of models it cannot audit, train, or govern. The proposed guardrails could reshape data access, model licensing, and compute economics across emerging markets. Watch whether BRICS moves from talk to binding AI standards.

On September 10, 2026, Indian National Congress MP Manish Tewari told ANI that artificial intelligence and the other frontier technologies of the Fourth Industrial Revolution will define the remaining 74 years of the 21st century and must become the foremost priority for BRICS. Speaking from Chandigarh ahead of the BRICS Summit, he argued that the overwhelming share of innovation driving AI and the push toward super artificial intelligence is occurring in the Global North, leaving the Global South exposed to a widening digital divide. He called for guardrails to ensure that the race to build superintelligence does not morph into a 'race to the bottom.'

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Watch whether BRICS moves from talk to binding AI standards.

The intervention is not a formal policy statement from the Indian government — Tewari is an opposition parliamentarian — but it captures an emerging anxiety among political leaders in emerging markets: that AI may become another technology cycle in which value, capability, and governing power concentrate in a small set of wealthy countries and firms. Frontier AI development remains concentrated in US and allied labs, with deep capital markets, advanced chip supply chains, and dense talent clusters. Many Global South economies face structural barriers in compute access, frontier hardware, data governance, and retention of skilled researchers. Tewari's 74-year framing is rhetorical, but the underlying concern is material: if current capability gaps compound, late movers may find themselves locked into dependency on imported models, cloud services, and standards they had little role in shaping.

His remarks also expose an important nuance inside BRICS itself. The grouping includes China, which is one of the world's two leading frontier AI powers alongside the United States. That makes a simple Global North-South binary incomplete: a BRICS China has the compute, capital, and research scale to compete in superintelligence research, while many other members depend on external technology. The practical question for the summit is whether BRICS can build an inclusive AI agenda that spans this internal asymmetry — perhaps by pooling compute, funding multilingual and open-weight models, and creating common governance standards — or whether the divide within the bloc remains as deep as the divide between the bloc and the North.

The 'race to the bottom' warning has specific implications for AI safety and governance. A superintelligence race without shared guardrails could pressure developers to cut corners on safety testing, transparency, labor standards, and data provenance, especially if frontier capabilities become a proxy for geopolitical leverage. Tewari's call aligns with growing international interest in AI safety institutions, but it goes further by linking safety to distributional fairness: in his framing, the absence of guardrails is what allows the Global South to be relegated to a source of data and labor rather than a partner in innovation. For AI companies, this signals that emerging-market governments may increasingly pair market access with demands for local research capability, open model access, and demonstrable safety commitments.