Bengaluru

AI4India has launched AI Diffusion Matrix Report and Assessment Tool on Monday at the AI for India Summit 2026 in Bengaluru, partnering with the Centre for Study of Science, Technology and Policy (CSTEP).

Developed in consultation with NITI Aayog, the report and the tool are designed to help organisations assess the maturity of their AI adoption, identify implementation gaps and build a structured roadmap to move beyond isolated experiments to AI that spreads responsibly across the organisation.

The release highlighted, while many have launched AI pilots and proof-of-concepts, few have been able to integrate AI into core operations, establish appropriate governance systems. "The AI Diffusion Matrix provides a common framework to evaluate where an organisation stands in this journey and what it needs to do next," it said.

The report analyses AI diffusion across four key dimensions -- technology readiness, governance, risk management and value creation. As per the release, it helps organisations examine "whether they have the infrastructure, data systems, talent and technical capabilities required to deploy AI effectively; whether decision-making structures and accountability mechanisms are in place; how they are identifying and managing risks; and whether AI initiatives are delivering measurable improvements in productivity, service delivery, inclusion, innovation or other organisational outcomes."

In a special video message, Prof. Abhay Karandikar, Member, NITI Aayog, said, "India has built strong foundations for this moment, but the real measure of AI will be whether it is genuinely used and whether ordinary people can feel the difference it makes."

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On the other hand, Shashi Shekhar Vempati, Co-Founder, AI4India & Padma Shri Awardee said, "India's AI opportunity will not be defined only by the models we build or the technology we have access to. The real opportunity lies in taking AI into the everyday functioning of enterprises, governments and communities. The AI Diffusion Matrix gives organisations a practical way to understand where they are today, identify what is holding them back and build the capabilities required for AI to become a meaningful national capability."