Hospitals Are Investing in AI. Clinicians Say Burnout Is Still Their Biggest Problem

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Hospitals are investing in artificial intelligence and automation to improve efficiency, but the central question remains whether those tools are actually reducing clinicians’ burnout.

According to the fifth annual Compass Survey from healthcare technology company symplr, 46% of clinicians identified burnout and staffing challenges as the greatest operational threat facing their organizations. Among hospital executives, however, financial pressure topped the list, cited by 65% of C-suite and vice president respondents.

The divide highlights a disconnect between hospital leadership priorities and the challenges clinicians face on the front lines, even as healthcare organizations accelerate AI adoption.

For nurses, the findings raise an important question: Are hospitals investing in technology that actually makes their jobs easier?

Why Technology Isn’t Solving Burnout

The 2026 Compass Survey, conducted in partnership with the College of Healthcare Information Management Executives (CHIME), found that healthcare professionals spend an average of 86 minutes daily on administrative tasks they believe AI could reduce or potentially eliminate.

Despite growing investments in technology, many fundamental hospital operations remain manual. Depending on the process, 40% to 46% of respondents reported that activities such as workforce scheduling, credentialing, onboarding, and safety performance management were still handled entirely manually.

Ali Morin, MSN, RN, NI-BC, chief nursing informatics officer at symplr, says introducing technology without addressing underlying workflow problems can actually make clinicians’ jobs more difficult.

“Technology alone does not reduce burnout. Poorly designed workflows and fragmented systems can move the work around and increase the burden, while excessive requirements add to it,” Morin told Nurse Approved.

Morin, a board-certified informatics nurse with more than 20 years of healthcare IT experience, says hospitals frequently invest in technology before identifying the specific clinical problems they want to solve.

“The next step is redesigning care delivery and administrative processes around the clinician and patient experience, then aligning technology to support that model,” she says.

The survey also found that burnout and staffing challenges have remained clinicians’ leading operational concern since 2023, despite continued efforts to modernize healthcare operations.

Are Nurses Being Left Out of AI Decisions?

One of the biggest challenges, according to Morin, is that nurses often have limited influence over the technology decisions that directly affect their work.

“Nurses are the largest group of healthcare professionals and are among those closest to patient care. However, nurses remain vastly underrepresented in many AI and technology decisions,” she says.

Morin believes hospitals need to involve nurses much earlier in the process, rather than seeking their input only after a system has been selected.

That involvement should begin when organizations identify operational problems and develop requests for proposals from technology vendors. Nurses should also participate in evaluating potential solutions, implementing new systems, training, and assessing their effectiveness.

Without that input, hospitals risk introducing tools that fail to address the administrative burdens nurses encounter during their shifts.

“Our industry hasn’t properly valued their influence in the design process, but nurses are often the group that will make or break whether technology makes a meaningful impact,” Morin says.

AI Adoption Is Moving Faster Than Training and Oversight

The survey also identified gaps in how healthcare organizations are preparing employees for AI.

Only 26% of respondents reported that their organizations had comprehensive AI policies that were actively enforced.

More concerning, 51% of clinicians said they were unsure whether their organizations had an AI policy at all. By comparison, just 3% of executive respondents expressed the same uncertainty.

The findings do not establish whether those clinicians personally use AI, but they raise questions about how effectively hospitals communicate policies governing emerging technologies.

“When clinicians can’t say whether a policy exists, that gap is a serious concern in its own right,” Morin says.

She believes nurses need clear guidance about appropriate AI use, patient privacy, documentation practices, and accountability.

As AI becomes more integrated into healthcare, Morin says those policies should be incorporated into nursing practice protocols alongside established patient safety procedures.

The survey also suggests that hospitals may be prioritizing AI deployment over workforce preparation.

While 27% of respondents identified AI deployment as their organization’s primary strategy for addressing operational challenges, just 3% cited staff development and change management.

Additionally, 21% reported that their organizations had deployed AI without establishing metrics to evaluate its performance.

For nursing leaders, those findings underscore the importance of ensuring that staff education, clinical oversight, and performance measurement keep pace with technology adoption.

How Can Hospitals Tell Whether AI Is Helping Nurses?

Morin says hospitals should evaluate AI investments based on whether they meaningfully reduce administrative work and give nurses more time for patient care.

That requires looking beyond whether AI has automated a task.

“Hospitals should measure the time AI returns to patient care,” she says. “It’s also important to evaluate where the work goes after AI touches it, because a task that moves somewhere else in the workflow still counts as a burden.”

She recommends that healthcare organizations track clinician satisfaction and retention alongside operational performance measures.

She says chief nursing officers and nurse managers also need to take a more active role in AI governance, ensuring nurses participate in selecting, evaluating, and implementing new systems.

Morin, who has helped develop digital transformation competencies for nurse leaders through the American Organization for Nursing Leadership (AONL), emphasizes that AI education must extend across all levels of nursing leadership.

Technology should support clinical judgment, she says, rather than replace it.

Giving Nurses a Greater Voice

For hospitals looking to improve their approach, Morin recommends establishing formal feedback mechanisms that allow clinicians to evaluate technology before organizations expand its use.

Nurses should have opportunities to identify problems, assess whether new systems solve them, and recommend changes when technology creates extra work.

Her advice is straightforward: Before expanding an AI solution, hospital leaders should ask nurses what administrative burdens or tasks the technology actually eliminated.

“The best innovations start with addressing workflow problems that caregivers identify themselves,” Morin says.

For healthcare organizations investing heavily in AI, the findings suggest that technological progress alone may not reduce clinicians’ burnout or improve the work environment.

Whether those investments ultimately help address burnout may depend on how much influence nurses have over technology decisions—and whether hospitals act on their input.

About the survey: The fifth annual symplr Compass Survey was conducted online from June 1 through July 17, 2026, in partnership with CHIME. It included 146 respondents from clinical, IT, and operational roles at U.S. hospitals and health systems. Approximately 30% worked in clinical roles, although the survey did not distinguish nurses from other clinicians. The sample was not weighted, and the findings should not be interpreted as nationally representative.