Properly Leveraging AI to Empower Nurses and Reduce Burnout Takes Careful Study & Deep Engagement

As health systems seek solutions to workforce challenges, AI is emerging as a tool to ease the burden on nurses. At Penn Medicine, AI-driven innovations are being explored to streamline workflows, improve documentation, and reduce clinician burnout. Anna Schoenbaum, DNP, MS, RN, VP of Applications, Digital Health & Predictive Health at Penn Medicine, highlighted the role of AI in enhancing nursing workflows.

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“There can be a tendency to focus AI advancements on physicians, but nurses also need support,” Schoenbaum said. “Burnout remains a major issue, and we must ensure technology is helping rather than adding to the burden.”

AI Solutions for Nursing Workflows

A key initiative at Penn Medicine involves developing an AI Toolkit for healthcare professionals. This resource provides foundational knowledge on AI, best practices for implementation, and real-world examples of AI-driven solutions in nursing. It also includes an innovation scoring impact guide, helping health system leaders assess the feasibility and effectiveness of new technologies.

One promising technology is ambient listening, which has already shown success in reducing documentation burdens for physicians. Schoenbaum believes it could help nurses as well, though its implementation presents unique challenges. “Nursing workflows are continuous rather than episodic, so we must carefully assess how and where ambient technology fits,” she explained.

Beyond ambient listening, the AI Toolkit also introduces the “Five Rights of AI,” a structured framework for evaluating AI solutions. This model helps leaders determine whether a technology aligns with their specific needs. “You have to start by asking the right questions,” Schoenbaum noted. “What is the problem you’re trying to solve? What outcome are you hoping to achieve?”

Other key considerations include the right competency, ensuring the necessary expertise is in place; the right data, verifying that AI solutions are trained on quality, unbiased datasets; and the right safeguards, ensuring compliance with HIPAA and other regulations.

Identifying Pain Points Through Observation

Understanding the daily challenges nurses face is critical to designing effective AI solutions. Schoenbaum emphasized the importance of direct observation, such as IT leaders conducting “listening tours” or shadowing clinicians. “You can’t assume users will report every struggle they encounter,” she said. “By observing firsthand, IT teams can identify inefficiencies, troubleshoot issues, and uncover opportunities for improvement.”

She shared an example from a visit to a clinic where ambient AI technology was being piloted. While observing a provider’s workflow, she discovered that a key feature was not being used due to a technical issue with system imaging. Addressing this problem immediately improved the workflow, reinforcing the value of hands-on engagement.

Schoenbaum also recalled her experience during the COVID-19 pandemic, when IT professionals at Penn Medicine volunteered as greeters in a busy ambulatory center. “Just standing at the entrance, helping patients navigate the facility, gave me an entirely new perspective,” she said. “It showed me the magnitude of the patient experience and how small technology tweaks—like pre-visit navigation messages—can make a significant difference.”

The Role of Governance and Communication

Effective AI implementation requires strong governance and clear communication between IT and clinical staff. Schoenbaum noted that some clinicians may not proactively report workflow issues, leaving their frustrations unresolved. “We need multiple feedback channels, from governance committees to frontline discussions, to ensure we’re addressing real problems with the right solutions,” she said.