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Elsevier
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AI Adoption in Nursing: Delivering Guidance Nurses Can Trust

9 de junio de 2026

Most healthcare organizations are already using AI in nursing but widespread adoption is still out of reach.

A HealthLeaders–Elsevier survey of 101 senior nursing leaders confirms that AI has arrived in clinical nursing — but broad adoption remains a work in progress. Most organizations are operating in pilot mode or working with just one or two tools, and none report widespread integration across nursing workflows.

That measured pace reflects a genuine challenge: for AI to earn a place at the bedside, it needs to do more than function. It needs to be trustworthy. With patient safety cited as the top concern about AI adoption by nearly half of respondents, nurse leaders aren't asking whether AI can work in nursing, they're asking whether it will work safely, reliably, and within the realities of how nurses actually practice.

The focus is shifting to the bedside

Small experiments and single-purpose tools have dominated early nursing AI adoption but the next wave of investment points in a clear direction. Survey respondents identified their top priority for the next 12–18 months, and the answer signals a meaningful shift in how organizations expect AI to support nurses. Documentation tools are part of the picture, but they're not the whole story.

The opportunity goes beyond reducing burden

Reducing documentation burden tops the list of desired outcomes for nursing AI investment but the survey reveals a more complex set of priorities underneath that headline finding. Nurse leaders are weighing workflow efficiency against workforce wellbeing, patient outcomes, and operational demands, often simultaneously. Understanding how those priorities stack up has real implications for which AI tools are worth pursuing.

Not all AI guidance is created equal

Patient safety is the number one concern about AI adoption among survey respondents, and it comes down to a fundamental question: where is the information coming from? The survey findings, paired with insights from Elsevier's Tim Morris, point to specific standards that separate AI tools nurses can rely on from those that introduce more risk than they resolve.

The gap between pilot and scale is where most organizations are stuck

Half of respondents report governance policies that limit AI use to clinically validated solutions. Another quarter are cautiously piloting approved tools. What the survey reveals is that governance alone isn't enough. There are specific integration and rollout factors that determine whether a promising pilot ever becomes standard practice.

Nurses must understand the value AI brings to remove doubt and enable them to make decisions with more confidence.
Portrait photo of Tim Morris

Tim Morris

Vice President, Global Nursing Solutions en Elsevier

AI in nursing is advancing fast and the decisions organizations make now will shape outcomes for years to come. Download the research brief to see what senior nursing leaders say about where the gaps are, where investment is heading, and what it takes to build a more confident, capable nursing workforce at your organization.

AI Adoption in Nursing - Delivering Guidance Nurses Can Trust

AI Adoption in Nursing - Delivering Guidance Nurses Can Trust

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