Broken Trust Cuts Employee Motivation by More Than Half, Deloitte Warns

One distrusted factor cuts employee motivation from 82% to 37% — a drop of more than half. That's the core finding Simona Spelman, leader of Deloitte's U.S. Human Capital Practice, shared after appearing at Fortune's Most Powerful Women Summit in Santa Barbara, Calif., last week.

Deloitte breaks trust into four pillars: reliability, transparency, capability, and humanity. The arithmetic gets brutal fast. A second distrusted factor drops motivation to 28%. Distrust all four, and only 7% of employees stay motivated to give their best.

Flip it around and the upside is even bigger: 96% of employees who trust their leader on all four factors are motivated to work. So trust isn't a nice-to-have on the culture deck — it's the swing variable between a 7% and a 96% engaged workforce.

"Getting the right balance of those four things is really what measures trust," Spelman said. She added that trust sounds like a "soft" word, but it can galvanize or drag on momentum as companies push forward.

Why AI makes this harder right now

Companies are warning employees not to blindly trust anything — even corporate emails, which fraudsters may use to socially engineer staff. Trust is harder to build and maintain in that environment.

AI raises the stakes further, particularly after some layoffs have been blamed on replacing employees with AI. Spelman said maintaining balance among the four pillars will be an evolving measurement challenge as companies press deeper into the technology.

"So think about that," Spelman advised the summit audience.

The leader-employee gap is already wide. Jennifer McCollum, president and CEO of Catalyst, the gender equity and workplace inclusion nonprofit, said 68% of leaders claim they have reskill plans in place — but only 34% of employees believe their organizations make AI training open to everyone.

"Our intentions are good, but we can really get it wrong," McCollum said. Periods of massive transformation offer "a huge opportunity to either engender trust or really screw it up," she added.

Catalyst's research, published in its Convergent Leader report, found:

• Only one-third of employees believe leadership teams act with integrity during business disruption.
• Just 16% said leaders remained confident and supportive during AI-driven change.

Employees are watching how leaders carry themselves through the transition, McCollum said.

The double bind for women

McCollum flagged a hidden cost for women specifically. Forthcoming Catalyst research will show that when women use AI at work, their credibility gets questioned — but when they don't use AI, their capabilities get questioned. That double bind will keep shifting as new generations enter the workforce, she said.

Where the money is going wrong

Spelman cited a statistic that frames the problem in dollars: about 93% of AI investment goes to the technology itself, while 7% goes to the human side.

"You can sit here and say, 'yes, we're invested,'" she said. "But if you're only spending 7% on what the impact is to the work, the workforce, or the workplace, you're really missing the mark."

That 93-to-7 split matters because the technology itself will stop being a differentiator. As AI and knowledge become democratized, what will set companies apart is "investment in the people, in the human capital," said Francesca Cornelli, dean of Northwestern University's Kellogg School of Management.

Framing matters as much as funding. When a leader announces a new tool will simplify processes, employees hear an inadvertent message. "All they hear is, 'you won't need me anymore,'" Cornelli said.

People buy in when AI is framed as a way for everyone to help the company improve — but only if the investment is real. "If you just use words, people will see through it," she said.

What does this change for executives?

Spelman's answer: as technology spreads, competitive advantage shifts to "enduring human capabilities like empathy, curiosity, and judgment." Companies still allocating 7 cents of every AI dollar to the workforce should expect the trust numbers — and the motivation numbers that follow them — to keep sliding.