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EY's Dan Diasio Says AI Productivity Gains Are Not Yet Reliably Turning Into Financial Returns

November 5, 2026 at 15:02 EST

Sales & Business

Jessica Lessin, Editor-in-Chief of The Information, sat down with Dan Diasio, EY Global AI Leader and Consulting CTO, to examine why productivity gains from artificial intelligence are not automatically showing up as financial returns for businesses, and what would need to change for that to happen.

Interview · EY Global AI Leader

Faster work is not the same as higher returns

AI tools are making employees faster, but speed does not automatically become revenue, lower costs, or profit. The real question is how companies convert productivity into measurable financial results.

From productivity to financial return

01 · Capability

Individual tasks get faster and output rises.

→

02 · Redeployment

Time saved is redirected into new work, not just absorbed.

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03 · Redesign

Processes, incentives, and management structures change.

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04 · Financial return

Revenue, cost, and profit become measurable.

What the gains look like

Employees are working faster and producing more with AI tools. This improvement is real at the individual level and is the basis of the enterprise case for AI.

Why it does not always show up

Time saved on tasks does not become output or savings if workflows, budgets, and headcount decisions stay the same. Attribution to AI is often contested, and returns can take a long time.

The takeaway

The next phase of AI adoption may depend as much on operational redesign as on model performance.

Deploy AI inside redesigned workflows.

Measure outcomes, not just speed.

Reorganize incentives and management.

Based on the published framing of the discussion; specific recommendations from the full conversation are not detailed here.

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