AI, Interoperability, and the Road to Smarter Healthcare Operations: Takeaways from HIMSS 2026

Earlier this month, Infor™ attended HIMSS 2026, where a clear message emerged: healthcare organizations are prioritizing technologies that deliver real operational impact. While AI dominated the expo floor, conversations with attendees centered on practical use cases, solutions that are safer to implement, reduce administrative strain, and measurably support staff, patients, and financial performance. Across our sessions on FHIR and AI, these outcome-driven priorities consistently rose to the top. Here are a few key takeaways from the event.

1. Administrative burden remains healthcare’s real disease

Administrative friction, especially in prior authorization, revenue cycle, and coordination, continues to drain time and resources. The upcoming CMS prior authorization mandate heightens the urgency for automation and streamlined workflows. Looking for solutions to these longstanding administrative problems has the potential not only to ease staff frustrations but also to reduce costs and strengthen financial performance.

2. Successful AI adoption starts with identifying the problem you want to solve

Leaders emphasized that effective AI adoption begins with understanding the specific operational pain point an organization wants to address. For example, during a session about AI and healthcare operations, one panelist described facing rising patient volumes and fewer staff, prompting their team to focus first on how to support the people delivering care and make their day-to-day work easier.

3. Governance, risk, and data readiness are prerequisites for AI success

With the rise of generative AI, leaders stressed the importance of strong governance, often supported by multidisciplinary oversight boards and a human-in-the-loop model. Governance wasn’t a one time step but an ongoing review of risk, bias, and outcomes, anchored by solid data governance from ingestion onward. This structure ultimately determines whether AI delivers a safe and meaningful impact.

4. Interoperability has become the foundation for enterprise AI and automation

In addition to defining the problem, leaders emphasized that meaningful AI requires the right data and interoperability infrastructure beneath it. Several organizations began by strengthening data governance, standardizing data, and investing in data literacy to build trust before layering AI on top. With clean, connected data as a foundation, they were able to responsibly scale AI tools and embed them into daily workflows.

5. Health systems are becoming data and technology companies that deliver healthcare

A growing number of leaders described their organizations as evolving into data-driven technology companies with healthcare delivery layered on top. Those with strong data foundations and interoperability are better positioned to personalize care, support value-based models, identify population healthcare gaps and improve outcomes. Data quality and accessibility are emerging as core competitive differentiators.

To learn more about how Infor is helping health systems solve their biggest operational challenges, visit www.infor.com/healthcare.