Transformational Thinkers with Sara Sheehan
Sep 29, 2026 · 20 min · 8 segments
AI investment and adoption are accelerating, yet many organizations are struggling to translate that investment into measurable business results. In this episode of *Transformational Thinkers with…
Sara SheehanHost
Worldwide AI spending will hit two point five nine trillion dollars in twenty twenty-six, a forty-seven percent jump from the year before.

Eighty-eight percent of organizations now use AI in at least one business function, up from seventy-eight percent just a year earlier.

By every measure of investment and adoption, AI has already won, and yet the technology is advancing faster than the humans responsible for deploying it.

The mere money organizations pour into AI, the less certain they are that it is paying off.

MIT's widely cited twenty twenty-five study of enterprise generative AI found that ninety-five percent of organizations saw no measurable return on their investment, not because the models were weak, but because the tools were bolted on to workflows that never learned, adapted, or integrated the way the business actually operates.


Leaders who understand that distinction and act on it will separate themselves from the majority of organizations still chasing a technology fix for what is fundamentally a people problem.

Worldwide AI spending will hit two point five nine trillion dollars in twenty twenty-six, a forty-seven percent jump from the year before.

Eighty-eight percent of organizations now use AI in at least one business function, up from seventy-eight percent just a year earlier.

By every measure of investment and adoption, AI has already won, and yet the technology is advancing faster than the humans responsible for deploying it.

The mere money organizations pour into AI, the less certain they are that it is paying off.

MIT's widely cited twenty twenty-five study of enterprise generative AI found that ninety-five percent of organizations saw no measurable return on their investment, not because the models were weak, but because the tools were bolted on to workflows that never learned, adapted, or integrated the way the business actually operates.


Leaders who understand that distinction and act on it will separate themselves from the majority of organizations still chasing a technology fix for what is fundamentally a people problem.
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