Ravi Kumar Dikshit’s New Book AI-DAPT Shifts the AI Debate from Technology to Leadership
With close to three decades of experience across companies like Accenture, Infosys and Kyndryl, Dikshit has seen how large organisations approach technology shifts and where they tend to fall short.
Across boardrooms today, there is a quiet but uncomfortable question doing the rounds. After significant investments in artificial intelligence, what has really changed for the business?
For many organisations, the answer is not straightforward. There have been pilots, proofs of concept, and ambitious roadmaps. But when it comes to measurable outcomes, the link is often unclear.
It is this exact disconnect that Ravi Kumar Dikshit addresses in his new book, AI-DAPT: A Leadership Compass to Thrive in the Human AI Era. With close to three decades of experience across companies like Accenture, Infosys and Kyndryl, Dikshit has seen how large organisations approach technology shifts and where they tend to fall short.
His central argument is simple, but not often stated clearly in organisations. The problem with AI adoption is not really about the technology. It is about how leaders are embracing it.
In many enterprises, AI is still treated as a separate initiative. Teams experiment, tools get tested, and use cases are explored. But somewhere between experimentation and execution, momentum gets lost. According to Dikshit, this is because organisations struggle to translate AI activity into decisions that actually move business metrics.
That shift in thinking forms the backbone of the book. Instead of focusing on LLMs, platforms, or tools, AI-DAPT places the spotlight on leadership. It frames AI not as a technical upgrade, but as a leadership advantage waiting to be claimed by those who bring clarity, prioritisation, and consistency to how they use it.
The book introduces AI-DAPT as a five-part framework, but it does not read like a typical management playbook. The ideas are tied closely to real scenarios that leaders face. One of the recurring themes is prioritisation. Many organisations do not lack AI ideas. What they lack is the ability to decide which ones are worth pursuing.
Another area Dikshit focuses on is learning. In fast-changing environments, traditional training programmes often cannot keep up. The book suggests that learning needs to become part of everyday work rather than something that happens separately. Teams that adapt faster, he argues, are not necessarily working harder, but learning differently.
There is also a noticeable shift in how work is getting done inside organisations. As AI tools become more powerful and trust increases, leaders are no longer just experimenting with them, they are figuring out where they actually fit. Some tasks are easy to hand over to AI, some clearly still need human judgement, and then there’s a large middle ground that is still being figured out. The leaders who are moving ahead are not waiting for perfect conditions. They are building a structured approach to decide deliberately where AI belongs and where it does not.
Interestingly, one of the more grounded sections of the book talks about what remains uniquely human. As AI improves efficiency, qualities like empathy, creativity, purpose and stewardship start to matter more, not less. Dikshit makes the case that these are not soft skills in the traditional sense, but critical capabilities in an AI-driven environment.
The conversation around decision-making is evolving in a similar way. Even as companies start relying on AI for inputs, there is still hesitation when it comes to fully trusting those outputs. Questions around accountability don’t go away. If a decision goes wrong, who owns it? The book tackles this directly, building a structured model around clearer ownership and more accountable systems, especially as organisations try to move faster without losing control.
What works in favour of AI-DAPT is that it does not approach AI from a purely theoretical lens. Much of it is drawn from real enterprise settings, including the kind of large-scale transformation challenges seen in global companies and global capability centres.
As the conversation around AI matures, the focus is slowly moving away from what the technology can do to how it is being applied. In that context, Dikshit’s perspective feels timely.
The book does not position AI as a silver bullet. Instead, it suggests that the real difference will come from how leaders choose to use it. And for leaders and organisations trying to move beyond experimentation, AI-DAPT offers a structured path to do exactly that.
Published By : Satyaki Baidya
Published On: 21 April 2026 at 16:24 IST