Enterprise AI adoption held back by skills gap, says Nutanix AI chief

Debojyoti Dutta, chief artificial intelligence (AI) officer at cloud computing company Nutanix, says many enterprises lack the right skilled people, which stymies the adoption of AI. In a video interview with Avik Das, he talks about the company’s AI strategy and how the current AI tools are better versions of calculators, which allow people to do more. Edited excerpts:

What are Nutanix’s strategies to improve AI adoption?

My role is basically to create the AI strategy and figure out how we should help our customers. But over time, we realised, while trying to build better AI solutions, that our AI strategy is essentially three-dimensional. The first dimension is AI on Nutanix, which is being the best platform to run AI workloads on the Nutanix platform. Next is AI in Nutanix, like, how do we use AI and generative AI agents to make our products better. And then the third one is AI at Nutanix, which involves how we use AI within our company to be more effective and upskill employees.

A couple of years ago, we were a little sceptical about whether AI can be used for coding. It was early days. But now, a large fraction of our software engineers use it for not only coding, but bug triaging, design, and all aspects of the software engineering cycle. So we are improving our processes as we go along.

What is hindering AI adoption among enterprises?

2025 was the proof of concept (PoC), and now people are deploying it in production. Initially, they started off building small chatbots, with the main use case being to talk to your own private data. But with agents, while not fully autonomous, people have found that they can automate a lot of repetitive tasks and also take many complex decisions.

That is giving enterprises a lot of confidence, and it is really making people think about how to get to production. But most enterprises do not have the right skilled people to do this. So they are finding it hard. And of course, because they are finding it hard,…

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