Dev Rishi, General Manager for AI at cyber resilience firm Rubrik, has argued that India is well-positioned to emerge as a global leader in artificial intelligence without needing to build its own frontier large language models — and that the biggest obstacle to enterprise AI adoption worldwide is not technology, but governance, security, and compliance. Rishi made the remarks ahead of Rubrik's annual Forward conference in Las Vegas, where the company unveiled a suite of AI-focused cyber resilience products.

Early Innings of an AI Shift

Rishi described the current moment in AI as only the beginning of a much larger transformation. 'I actually think we're in the very early innings of AI changing world,' he said. 'The first generation of AI were these LLM models that were mostly informational.'

He sees the next wave moving decisively from information retrieval to action — what he terms a shift 'from generative AI to adjunct AI.' In his view, this transition is where real return on investment will materialise for organisations. 'That is the way that it's going to start to actually lead to a lot of ROI inside organisations,' he said.

Governance, Not Technology, Is the Real Blocker

Rishi argued that the limiting factor for enterprise AI deployment is not capability or cost, but the absence of robust guardrails. 'If you survey enterprise CIOs and CISOs, they'll tell you that the number one blocker towards being able to adopt AI is governance and guardrails and compliance,' he said. 'It's actually not cost, it's not orchestration, it's not even quality.'

His solution is recursive: AI systems must themselves be used to secure and govern AI agents operating inside organisations. Rubrik has launched new products aligned with this thesis, including integrations with Anthropic's Claude AI ecosystem and agent-driven recovery capabilities designed to help enterprises respond faster to cyber attacks.

India's Advantage: Talent and Application-Layer Leadership

Asked about India's place in the global AI landscape, Rishi — who was born in India and holds an Overseas Citizen of India card — pointed to the country's technology talent base and education ecosystem as structural strengths. 'India has an incredibly rich tech sector and a really strong education system that positions it well to be at kind of the forefront for what AI is doing,' he said.

He acknowledged that India has not matched the United States or China in foundation model development, but dismissed the idea that this is disqualifying. 'I don't think that's a core requirement to be a leader in AI,' he said. Instead, he sees India's competitive edge lying in building verticalised applications, business tools, and contextual 'harnesses' around AI — the layer that helps organisations extract ROI more quickly from underlying models.

Notably, Rishi also highlighted government services as a high-impact use case, pointing to public agencies burdened by large backlogs in document review, information synthesis, and approval workflows as areas where AI can deliver significant efficiency gains.

Not Overhyped — Underhyped in the Long Run

Rishi pushed back on the view that AI is experiencing a hype bubble. Drawing a parallel with the internet, he said: 'I think like a lot of other technologies, what we'll see is that it's maybe slightly gets a lot of buzz in the short term. But in the long term we actually find that it's underhyped.' He added, 'I think AI is going to be on a very similar scale.'

This perspective comes as India accelerates efforts to embed AI across public services, education, healthcare, and industry — a push that has gathered pace since the global generative AI surge following ChatGPT's launch in late 2022. Whether India builds its own models or not, Rishi's argument is that the application layer — where India's engineering depth is formidable — may be where the real value is captured.