Should Trust Be Your New AI Performance Metric?

In our pilot study, one variable moved faster than any other—trust. After just four sessions of structured team coaching, the “trust gap” between coached and uncoached teams wasn’t small.

It was a 41-point swing.

In this study, “trust” meant trust in AI: the confidence employees had that their new system would genuinely help them do better work. What’s fascinating is how closely that mirrors team trust behaviors: when people feel anchored in mutual reliability, their trust in each other — and their performance — rise together.

Same people. Same AI tools. The difference? How they related to one another.

When trust rose, confidence followed (+28 points), and performance indicators began to shift as coached teams saved 27 more hours per year per person. 

These aren’t “soft” metrics. Across hundreds of meta-analyses, trust and engagement consistently predict output:

 → +23 % profitability

 → +18 % sales productivity

 → −81 % absenteeism

Trust is the earliest signal of capability. Before productivity shows up in a spreadsheet, it increases when people feel confident to experiment, share, and learn together.

Training transfers information; coaching transforms relationships. And when teams feel safe, they try, adapt, and perform.

See the full pilot results 👉 Hidden Factor Makes AI Adoption Work

What if trust is the seed for successful AI adoption?