Only 17 percent of nurses reject AI outright. The other 83 percent aren't asking whether AI belongs in healthcare. They're asking whether it can be trusted.

M7 Health surveyed 258 nurses across more than 100 hospitals to find out. The results point to a clear pattern: nurses trust AI as an input, not an authority. They want visibility, not automation. And whether a tool earns their trust has less to do with the technology itself and more to do with how it's rolled out.

That distinction matters right now. Nearly half of nurses who lived through an AI rollout describe some form of implementation failure. Only one in four say it was well supported from start to finish. Meanwhile, 61 percent report no AI tools live in their hospital at all, and bedside RNs, the group whose buy-in determines whether adoption actually sticks, have the least exposure of any role.

In this whitepaper, we break down what 258 nurses told us about AI, trust, and workforce operations, and what it means for how health systems should build and roll out technology going forward.

Inside you'll find:

• Survey data showing 60 percent of nurses report moderate or higher trust in AI recommendations, and what the other 40 percent are actually objecting to
• Why trust in AI falls with tenure, even as every experience band rates technology's overall impact net positive
• Nurses' own ranking of what would improve their work life most: staffing and scheduling flexibility outranked pay and safer environments
• Implementation data showing why nearly half of AI rollouts fail nurses, and what separates the rollouts that earn trust from the ones that don't
• A blueprint for what trustworthy healthcare AI looks like: transparent, overridable, and built to inform decisions rather than replace them

Download the whitepaper to see what nurses need from AI to actually trust it, and what that means for how you implement it.