Most nurses say AI isn’t good enough to trust with patient care, survey finds

2026-07-07 · Source: Welcome to the Artificial Intelligence Incident Database · Field: Health & Wellbeing — Healthcare Systems & Policy, Medical Devices & Health Technology, Clinical Care & Medical Practice · Depth: Fundamental Awareness, short

Summary

A recent survey of over 2,200 nurses by Incredible Health reveals a significant increase in AI adoption among U.S. nurses, with 44 percent now using AI at work, up from 15 percent last year. Despite this rise, over 80 percent of respondents expressed distrust in AI's accuracy, stating it requires verification for patient care. Common applications include documenting patient interactions, drafting communications, and referencing clinical information. The survey also found that nearly half of AI-using nurses experienced no time savings, though 19 percent saved over an hour. Furthermore, with a U.S. shortage of 263,000 registered nurses, only 11 percent of those surveyed believe AI will meaningfully alleviate this issue within the next five years. The findings, based on Incredible Health's platform users, may not represent all nurses.

Key takeaway

For healthcare administrators evaluating AI integration, recognize that while AI adoption is increasing among nurses, significant trust issues persist regarding accuracy for patient care. You should prioritize AI solutions that incorporate robust verification mechanisms and demonstrate clear, measurable time savings to gain nurse confidence. Developers should focus on improving AI accuracy and transparency to address current skepticism and ensure clinical reliability.

Key insights

Nurses are adopting AI more, but largely distrust its accuracy for patient care and doubt its impact on staffing shortages.

Principles

• AI tools require human verification for critical tasks.
• User perception of AI utility varies widely.
• AI's impact on systemic shortages is doubted.

In practice

• Document patient interactions with AI.
• Draft patient emails and educational information.
• Look up drug or clinical references.

Topics

• Nursing AI Adoption
• Healthcare Staffing
• AI Trust
• Patient Care Technology
• Clinical AI Applications
• Incredible Health Survey

Best for: AI Product Manager, Product Manager, Entrepreneur, General Interest, Domain Expert, Policy Maker

Related on AIssential

• Indian clinicians trust AI more than global peers, but use it less at work - Business Standard — Indian clinicians show higher AI trust but lower adoption, despite better institutional support and less workplace pressure.
• Healthcare AI Has a Reliability Problem Nobody Talks About — Healthcare AI needs to assess prediction and explanation stability, not just accuracy, to ensure clinical trustworthiness.
• NYSNA Allege Montefiore Plans to Replace Some Nurses with AI Systems — The alleged replacement of experienced nurses with AI in healthcare raises critical concerns about patient safety, job security, and data privacy.
• Health-care AI is here. We don’t know if it actually helps patients. — Despite rapid AI adoption in healthcare, its impact on patient outcomes is largely unmeasured.
• Overcoming Skepticism and Driving AI Adoption - with Umesh Rustogi of Microsoft — Successful AI adoption in healthcare requires purpose-built tools, seamless integration, and continuous organizational change management.
• Users of social media and AI chatbots for health information are more likely to say they are convenient than accurate — Digital health information from social media and AI chatbots is valued for convenience and understandability, not accuracy.

See Counsel's argued verdicts on the open AI decisions leaders are weighing →

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Welcome to the Artificial Intelligence Incident Database.