By 2036, healthcare IT will likely be unlike anything we see today — not because of a single breakthrough technology, but because of how deeply digital tools are embedded into care delivery.
Across health systems, chief medical and nursing informatics leaders describe a future shaped by ambient intelligence, predictive analytics and automation. But beneath the vision, a consistent theme emerges: the biggest risk isn’t falling behind on innovation — it’s failing to get the fundamentals right.
For many leaders, the near-term reality is far more grounded than the industry narrative.
Marc Benoy, BSN, RN, CNIO at Akron, Ohio-based Summa Health, expects the next several years to focus less on transformation and more on stabilization.
“Between now and roughly 2031, healthcare IT must stay focused on stabilization, validation and the careful introduction of emerging capabilities,” he said.
Despite the rapid rise of AI, he argues its ability to deliver enterprise-level value is still limited by persistent issues: fragmented workflows, inconsistent data quality and unclear return on investment. Until those are addressed, many technologies will remain in controlled or early-scale deployments.
That groundwork, he said, is what enables the longer-term vision: a “hospital without borders,” where care is coordinated across settings through predictive analytics and centralized command centers, extending far beyond traditional facilities.
Still, others are already imagining what that mature state could look like.
Jason La Marca, MD, CMIO at Los Angeles-based Mission Community Hospital, sees a future where documentation disappears into the background entirely.
Ambient and conversational AI, he said, will eliminate keyboard time, while the EHR evolves into a behind-the-scenes data orchestration layer rather than a user-facing system. AI agents will continuously engage patients — managing medications, monitoring symptoms and proactively guiding them to care — while revenue cycle operations become fully automated and real-time.
In that environment, predictive analytics won’t just support decisions, but drive them.
But whether those capabilities succeed will depend on how well they are implemented in practice.
Usman Akhtar, MD, CMIO at Virginia Hospital Center in Arlington, said the defining shift won’t be the tools themselves, but how seamlessly they fit into clinical workflows.
“Healthcare IT will feel much more embedded in care rather than sitting off to the side as another layer of work,” he said.
Ambient documentation, decision support and patient-facing AI may dominate the landscape, but the real differentiator will be clinician trust. At his organization, that means testing technologies in live workflows and building the governance needed to scale them responsibly.
That emphasis on trust and usability is echoed across leaders, particularly as AI becomes more pervasive.
Tampa, Fla.-based Moffitt Cancer Center CNIO Marc Perkins-Carrillo, MSN, RN, expects AI to reshape not just workflows, but the skill sets required to lead them.
Future success, he said, will require expertise in generative AI, clinical context and governance — and organizations must start building those capabilities now. As adoption accelerates, maintaining human oversight will remain essential.
“Trust but validate” will be critical, he said, ensuring AI outputs are continuously reviewed and aligned with patient safety.
Yet others argue the most important investment isn’t in any specific technology at all.
C. Becket Mahnke, MD, CMIO at Wenatchee, Wash.-based Confluence Health, said the pace of change makes predicting specific tools less useful than preparing clinicians to adapt.
“The winning bet is not on any specific technology but on clinician capacity to learn,” he said.
At Confluence Health, AI tools are being deployed not just for immediate clinical value, but to build long-term capabilities — training clinicians to define tasks clearly, evaluate outputs and adjust as technologies evolve.
Looking further ahead, some leaders expect the transformation to extend beyond software entirely.
K. Nadeem Ahmed, MD, CMIO at The Valley Health System in Paramus, N.J., anticipates a growing role for robotics in direct patient care, expanding beyond surgical use into more autonomous, AI-enabled clinical support.
Leaders widely agree that AI, automation and predictive analytics will shape the future of healthcare IT. But the organizations that benefit most won’t be those that adopt the most tools — they’ll be the ones that solve for interoperability, data integrity, workflow design and clinician trust first.
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