The real hurdle to enterprise AI isn’t fixing productivity KPIs. It’s ‘unlearning’ old habits, experts say

At Fortune Brainstorm Tech, industry experts discussed why practices like measuring hours saved is the wrong KPI for the AI age.

When Amazon recently dismantled an internal AI leaderboard, it exposed a broader issue in corporate America’s AI rollout. The leaderboard tracked so-called tokenmaxxing, a trendy corporate phenomenon where employees maximize their consumption of AI processing power to prove they are utilizing the technology. But employees were gaming the system to inflate their productivity scores.

It was a prime example of a deeper problem: Companies are treating AI as a game of administrative speed rather than business transformation.

Speaking this week at Fortune Brainstorm Tech in Aspen, Colorado, a panel of industry experts argued that the future of work cannot merely be about layering expensive tools onto outdated processes. Instead, they said, enterprises must fundamentally rewire how their employees operate.

“The level of investment in the technology versus the human is woefully lopsided,” said China Widener, Deloitte’s vice chair of technology, media, and telecommunications. “For every dollar spent, only about seven cents is going to humans, and 93 cents is going to the technology.”

This imbalance explains why AI’s financial rewards so far remain concentrated at the companies with the most resources. Chris Bedi, chief customer officer and enterprise AI advisor at ServiceNow, said that roughly 90% of enterprise AI use cases focus strictly on internal productivity and cost management rather than driving top-line growth. Because most companies are playing defense, they are being left behind. A recent PwC study revealed that just 20% of companies are capturing nearly three-quarters of AI’s total economic value.

To break this cycle, Bedi urged leaders to move away from shallow “KPI conversations” that track minutes and hours saved, and focus instead on true organizational key results. Phil Wiser, former EVP and CTO at Paramount, suggested a structural fix: creating a centralized, “forward-deployed” engineering team that embeds within various corporate divisions to help them radically reimagine their specific business functions.

Wiser said younger generations also remain skeptical of AI in part because of the amount of AI slop they see every day. They wonder why they should they engage with this technology that doesn’t appear to improve their lives, he said, arguing that the industry has a messaging problem because it’s too centralized on corporate profit and losing the narrative on the human value of AI. 

Ultimately, the real hurdle to AI integration is psychological, the experts said. True transformation requires “unlearning,” Deloitte’s Widener said. Asking professionals to let go of workflows that have brought them success for twenty years is a big but necessary ask, she said. If executives fail to build trust and clearly communicate how AI augments human capability, they risk triggering widespread cultural pushback.

“If you have a trust problem,” Widener said, “you’re going to have a culture problem.”

More from the 25th annual Fortune Brainstorm Tech conference:

Anthropic’s Boris Cherny, creator of Claude Code, says there are days he manages tens of thousands of AI agents at once

The space economy’s next frontier is in ground infrastructure, Northwood Space CEO says

‘Not an Allbirds Moment’: Xbox’s new CEO says she is grounding the console in gaming roots not AI

This story was originally featured on Fortune.com