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AI Has An Outcomes Problem. Here’s Why Nobody Can Solve It Alone.
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Gary Drenik, Contributor

· 1 min read

World NewsForbes: Innovation

AI Has An Outcomes Problem. Here’s Why Nobody Can Solve It Alone.

For the last three years, companies have raced to adopt AI but now the adoption conversation is changing. Instead of measuring adoption success through seats, licenses, and tokens, smart business leaders are asking how it can drive value. Microsoft has committed billions of dollars and thousands of engineers to guarantee business results from AI, and Amazon Web Services has pledged roughly a billion more to embed engineers inside customer operations and prove the return. The message has shifted from “use more AI” to “here is how it’s providing value,” a compelling pitch that rests on a claim most buyers currently have no reliable way of evaluating.

The gap between the promise and the proof is already apparent. MIT’s 2025 State of AI in Business study found that roughly 95% of enterprise generative-AI pilots have generated no measurable impact on the bottom line.

The reason has less to do with measurement than with what AI has become. In the old model, better software made people more productive. Today, AI is taking over large parts of the job itself, from a salesperson’s account research to a support team’s ticket queue. That changes the management question. Companies are no longer just deciding whether a tool paid off. They are deciding which work belongs to people and which belongs to AI.

Few executives have watched this pattern from as many vantage points as Lexi Reese. At Google, she helped build the programmatic advertising platform that scaled only once independent measurement existed. As COO of Gusto, she ran the payroll and HR systems small businesses use to manage their people. Today she is founder and CEO of Lanai, a Palo Alto-based company building a management system for AI-performed work.

“The winning companies won’t be the ones using AI the most,” Reese said. “They’ll be the ones that get exceptionally good at allocating work across humans and machines. That is going to show up in revenue per employee, operating margin and ultimately growth.”

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This story was published by Forbes: Innovation and written by Gary Drenik, Contributor. SyncAI.news shows a preview; the complete article is on the publisher's site.

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