What drives trust in AI for nurses? Five markers that matter

According to Elsevier's Clinician of the Future 2026 report just 42% of nurses believe AI tools are trustworthy, and they have been clear about what would change that. 

Why it matters: Nurses are under pressure. Some 61% are seeing more patients than a year ago, and 43% find it hard to keep up with medical advances. AI could help, but only if nurses trust it enough to use it.  

Trust is the barrier 

Nurses are optimistic about AI overall. Eighty percent say it will not replace clinicians but will become a critical assistant within 5 - 10 years. Yet nurses use AI less than doctors do (41% versus 57%), and only half say their institutions provide good access to AI tools (51%) or training (46%). 

Many are filling the gap themselves. Among nurses who use AI, around 40% turn to generalist tools for patient education and 34% for medical research. These tools do not always produce reliable answers, and nurses are left to judge the risk alone. 

What nurses say builds trust 

Asked what would improve their trust in AI, nurses gave five answers, all closely grouped: 

• Easy to use (65%)  Clear, well-structured outputs that fit a busy shift. A tool that demands time to decode is a tool that gets abandoned. 

• Comprehensive (62%) Answers that draw on multiple sources, not just one. Nurses want the full picture, not a single view of the evidence. 

• Transparent (61%). Citations that show where an answer came from. Visible sources let nurses check the answer rather than take it on trust. 

• Safe (60%). Confidence that the tool will not cause harm. When decisions affect patients directly, reliability is non-negotiable. 

• Quality sources (60%). Peer-reviewed content behind every response. Authority comes from the evidence base, not the interface. 

The list aligns with expectations for any good clinical resource. They want the same standards they apply to any clinical resource: know the source, check the evidence, then act. 

Why these markers matter 

A nurse who can see the source can verify the answer in seconds. A nurse who cannot must either take it on faith or start searching again, which defeats the purpose. 

The data bears this out. Nurses who use clinical-specific tools rate them more highly than generalist tools on authority, with 58% calling them good against 44%. Trust follows provenance. 

There is also a patient-safety argument. Nurses spend far more time with patients than doctors do. In one ICU study, patients received 86% of their care time from nurses. When nurses are the main point of contact, the quality of what they rely on shapes the quality of care.  

Where ClinicalKey Nursing AI fits 

ClinicalKey Nursing AI is Elsevier's bedside-ready assistant, designed around these markers. Nurses ask questions in natural language and get concise answers grounded in Elsevier's nursing books, journals, Clinical Skills and guidelines.  

Every response includes citations with direct links to full text, so nurses can verify the information or explore further. Clinicians continuously review and evaluate the tool to help keep responses accurate and aligned with evolving practice. 

The result is less time searching and more time with patients. It stays within nursing scope, covering assessments, interventions, monitoring and procedures. It supports clinical judgment and does not replace it.  

The bottom line 

Trust in AI is earned through evidence, transparency and fit with real workflows. Organisations that build on those foundations will give nurses tools they will use.