What does it really take to move enterprise AI from impressive demos to decisions that show up in quarterly results?
One year into his role as Global Managing Partner at IBM Consulting, Neil Dhar sits at the intersection of strategy, capital allocation, and technology execution. Leading the firm’s Americas business and a team of close to 100,000 consultants, he has a front-row view into how large organizations are reassessing their AI investments.
From global healthcare leaders like Medtronic to luxury retail brands such as Neiman Marcus, the conversation has shifted. Early proofs of concept helped executives understand what was possible. Now the focus is firmly on proof of value and on whether AI can drive growth, competitiveness, and measurable return.
In this episode, I speak with Neil Dhar about what has changed in the boardroom over the past year and why ROI has become the central question.
Drawing on more than three decades in finance and private equity, including senior leadership roles at PwC, Neil explains why AI is increasingly being treated as a capital allocation decision rather than a technology experiment.
Every dollar invested has to earn its place, whether through productivity gains, operational improvement, or new revenue opportunities. Vanity projects no longer survive scrutiny, especially when boards and investors expect results on a much shorter timeline.
We also explore how IBM is applying these same principles internally. Neil shares how the company has identified hundreds of workflows across the business, prioritized those with the strongest economic impact, and used AI and automation to drive large-scale productivity gains. The result is a potential $4.5 billion in annual run rate savings by 2025, with those gains being reinvested into innovation, people, and future growth.
It is a candid look at what happens when AI strategy, leadership accountability, and disciplined execution come together inside a global organization.
If you are a business leader trying to separate real value from hype, or someone wrestling with how to justify AI spend beyond experimentation, this conversation offers a grounded perspective on what enterprise AI looks like when it is treated as a business decision rather than a technology trend.
Are you ready to rethink how AI earns its place inside your organization, and what proof of value really means in 2026?
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