Most organizations assume AI adoption stalls because of weak communication, insufficient training, or tools that aren't accurate enough. An original survey of 523 professionals across healthcare, finance and insurance, and manufacturing and operations tested that assumption directly, and the data points elsewhere.
When five possible explanations, change management, technical quality, incentives and culture, regulatory confidence, and psychological trust, are tested against each other simultaneously, psychological trust wins decisively. It predicts actual usage and continued adoption roughly twice as strongly as the next-closest category, and more than ten times as strongly as change management, the lever most organizations reach for first.
That gap isn't a rounding error. It means the categories organizations typically invest in to drive AI adoption aren't the ones moving the needle, and the one that is, trust in the tool itself, is usually the last thing addressed, if it's addressed at all.
Most organizations assume AI adoption stalls because of weak communication, insufficient training, or tools that aren't accurate enough. An original survey of 523 professionals across healthcare, finance and insurance, and manufacturing and operations tested that assumption directly, and the data points elsewhere.
When five possible explanations, change management, technical quality, incentives and culture, regulatory confidence, and psychological trust, are tested against each other simultaneously, psychological trust wins decisively. It predicts actual usage and continued adoption roughly twice as strongly as the next-closest category, and more than ten times as strongly as change management, the lever most organizations reach for first.
That gap isn't a rounding error. It means the categories organizations typically invest in to drive AI adoption aren't the ones moving the needle, and the one that is, trust in the tool itself, is usually the last thing addressed, if it's addressed at all.
