Understanding Essential Hospitals’ Experiences with AI

As artificial intelligence (AI) applications emerge across the health care sector, hospitals are exploring how these technologies can improve care delivery, support their workforce, advance population health, and strengthen hospital operations. Implementing these technologies effectively and responsibly is particularly important for essential hospitals as they navigate the unique challenges of caring for underserved communities with limited resources.

Understanding Essential Hospitals' Experiences with AI is a series of issue briefs exploring how essential health systems are adopting and applying AI across a variety of domains. Drawing on insights from leaders across the field and an environmental scan of current and emerging practices, the series highlights different AI applications, early results, lessons learned, and the organizational strategies needed to successfully implement these technologies.

Together, the briefs illustrate that successful AI adoption requires more than selecting the right technology. Essential hospitals are pairing AI tools with strong governance, workflow redesign, staff support and engagement, data infrastructure, and evaluation and monitoring to ensure that innovation translates into meaningful improvements for their staff, patients, and communities.

The series includes:

Clinical Application Innovations

This brief examines how essential health systems use AI across clinical care, including diagnostic imaging, triage, clinical documentation, care coordination, treatment planning, and patient access. It explores the importance of workflow redesign, staff support, evaluation, and bias monitoring, particularly for predictive and patient-facing applications.

AI Applications for Population Health Improvement

This brief explores how essential hospitals use AI to identify patients and communities at elevated risk, prioritize limited resources, and support earlier intervention. Examples span preventive care, chronic disease and behavioral health, maternal health, patient experience, and social risk. The brief examines how strong data infrastructure and cross-sector partnerships are critical to translating predictions into meaningful action.

Coming Soon

• AI Applications in Revenue Cycle Management: This brief examines how essential health systems use AI throughout the revenue cycle to improve documentation and coding, strengthen utilization review, reduce denials, predict no-shows, and recover revenue. It highlights significant financial results and explores how hospitals can use AI to improve financial performance while retaining workforce capacity.

• Establishing Effective Governance: This brief explores the governance structures and considerations essential hospitals need to support successful and responsible AI adoption. It examines considerations including patient safety and trust, clinician well-being, data security, tool implementation and evaluation, and organizational accountability.

To explore additional resources regarding clinical adoption of AI, please explore our resource library. If interested in learning more about AI adoption at essential hospitals, association members are encouraged to join the AI interest group.