The Economic Times’ Future of Knowledge Work Summit 2026 will take place in Mumbai on 19 November 2026. PwC’s 29th Annual Global CEO Survey showed 66% of Indian CEOs worry about keeping pace with AI. Leaders must now rethink old habits and learn to work with technology while keeping their judgement.
Synopsis
AI is changing the information available to executives, the pace of decision-making and the skills required to lead large organisations. For senior leaders, adapting means questioning established management habits, becoming more comfortable with experimentation and learning to work with technology without surrendering judgement.
A senior executive who has spent decades making decisions may be accustomed to being the person with the answers. Artificial intelligence complicates that position. Information that once took a team days to assemble can now be produced in minutes, while an unfamiliar problem may demand a response before experience offers a clear precedent.
The change puts a different kind of pressure on leadership. Executives must decide when to trust an AI-generated recommendation, when to challenge it, and when to rely on the knowledge of people closer to the problem. Authority still matters, but the ability to question an established way of working matters more.
The issue will be explored at The Economic Times’ Future of Knowledge Work Summit 2026 in Mumbai on 19 November 2026. The discussion will examine how senior leaders can adapt their own working habits as AI changes how organisations make decisions and distribute responsibility.
The habits that served leaders may need revisiting
The pressure is visible in the findings of PwC’s 29th Annual Global CEO Survey. Among Indian CEOs surveyed, 66% said they were more concerned about keeping pace with technology and AI than they had been in the previous year. The figure was higher than the 42% recorded among CEOs globally. The survey included nearly 50 Indian respondents, so the findings offer a snapshot of executive sentiment rather than a comprehensive measure of all Indian businesses.
Keeping pace requires more than approving technology budgets. Leaders who are accustomed to centralising decisions may need to give teams greater room to experiment. Those who rely heavily on established performance measures may have to reconsider how they evaluate work when AI changes the time and effort a task requires. And executives who expect their own experience to provide the final answer may need to make space for evidence that challenges their assumptions.
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Tata Steel CEO and Managing Director T. V. Narendran offered a telling example in PwC’s survey, describing the company’s use of reverse mentoring, in which younger employees help senior leaders understand AI. The approach recognises a simple reality: expertise in running a large business does not automatically translate into fluency with every new technology. Leaders sometimes need to learn from the people they manage.
From being the expert to asking better questions
Unlearning does not mean abandoning experience. It simply means recognising where experience remains useful and where it can narrow the choices a leader considers. AI can help executives examine scenarios, test assumptions and access information more quickly, but its recommendations still require context and scrutiny.
The leadership challenge also extends to the workforce. Employees need clarity about how AI will affect their responsibilities, what decisions they can make independently and where accountability remains human. Leaders who introduce new tools without addressing these questions risk creating uncertainty across teams, even when the technology itself works well.
The corner office has traditionally been associated with authority and certainty. In an AI-enabled workplace, effective leadership may depend more on intellectual curiosity, openness to challenge and a willingness to revise established practices. The executives best placed to guide their organisations through the change will be those who can learn alongside their teams, question their own assumptions and take responsibility for decisions that technology can inform, but cannot own.
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