The government has initiated a comprehensive assessment of potential risks from advanced artificial intelligence models, with Finance Minister Nirmala Sitharaman and IT Minister Ashwini Vaishnaw chairing a high-level meeting on Thursday to review emerging threats. The meeting brought together senior officials from the Reserve Bank of India (RBI), National Payments Corporation of India (NPCI), Indian Computer Emergency Response Team (CERT-In) and CEOs of various commercial banks to discuss the unprecedented nature of threats from new AI models. According to The Times of India, Sitharaman emphasized that the nature of the threat from new AI models is unprecedented and requires greater preparedness and coordination across financial institutions. The Indian Banks' Association was specifically advised to create a coordinated response mechanism for AI-related threats, with banks directed to strengthen cybersecurity systems, engage specialised agencies and ensure real-time sharing of threat intelligence.
India has taken a decisive step forward in building its self-reliant AI ecosystem with Larsen & Toubro (L&T) bringing together its semiconductor arm, data centre business Vyoma, and the BharatGen Technology Foundation to create a fully indigenous AI compute platform. The collaboration signals a shift from fragmented AI efforts to a deeply integrated, national-scale strategy spanning silicon, infrastructure, and foundational models under a five-year roadmap to design and deploy a sovereign AI stack. The initiative aligns closely with the government's broader IndiaAI mission and growing emphasis on data sovereignty, secure infrastructure, and domestic innovation, with the presence of the Principal Scientific Adviser's office at the MoU signing underscoring its national importance.
The partnership combines complementary expertise across the AI stack. L&T Semiconductor Technologies (LTSCT) will focus on building custom AI chips—energy-efficient ASICs and xPU platforms tailored for India-specific workloads, including multilingual large language models and domain-focused AI systems. These chips are expected to prioritize performance-per-watt, low latency, and secure execution areas increasingly critical as AI workloads scale. L&T Vyoma will deliver hyperscale, AI-ready infrastructure with assets like its 30 MW data centre in Kanchipuram, providing the physical and operational backbone needed to run large-scale AI workloads including orchestration layers, AI/ML software stacks, and end-to-end management capabilities.
BharatGen brings the academic and research muscle anchored at IIT Bombay and backed by the Department of Science and Technology, with the consortium including leading institutions such as IIT Madras, IIT Kanpur, and IIIT Hyderabad. Its role will be to define representative workloads—ranging from large language and multimodal models to smaller, efficient systems—and co-optimize them with the underlying hardware and software stack. This co-design philosophy—where chips, models, and infrastructure are developed in tandem—marks a departure from traditional AI deployments that often stitch together global components, focusing instead on tightly integrated systems engineered for India's linguistic diversity, scale, and governance requirements.
The collaboration is expected to set benchmarks for performance, energy efficiency, and security while ensuring compliance with data sovereignty and critical infrastructure norms. For enterprises and policymakers alike, the sovereign AI compute platform could reduce reliance on global hyperscalers and chipmakers, offer greater control over sensitive data, and enable AI solutions tailored to India's unique socio-economic landscape. However, the government's risk assessment reveals growing concerns about advanced AI models like Anthropic's Claude Mythos, which can independently identify and exploit software weaknesses, including previously unknown vulnerabilities in operating systems and web browsers. As per The Times of India, Department of Financial Services secretary M Nagaraju noted that Mythos presents both risks and opportunities, highlighting how AI can improve credit access using alternative data while posing cybersecurity and data privacy risks.
