The first wave of AI in health systems was ambient documentation — microphones in exam rooms, notes written by machines. That story has been told. The more interesting story is what’s coming next.
Across health systems of every size and type, executives described a second, more ambitious wave of AI deployment — one focused not on transcribing clinical encounters but on restructuring how care is scheduled, coordinated, discharged, and delivered. The throughline: AI as an operational redesign tool, not just a documentation shortcut.
At Ochsner Health in New Orleans, Executive Vice President and COO Timothy L. Riddell, MD, described the health system’s investment in what he called “agentic support” within its patient contact centers. The concept goes beyond chatbots: AI agents that can act autonomously to complete scheduling tasks, resolve access questions, and route patients to appropriate care — without human intervention at every step. Alongside that, Ochsner is deploying AI to manage appointment inventory and capacity in real time, ensuring that as patients search for available appointments, open slots are actually visible and bookable.
“We are using tools and technology to create consistency and greater standardization that will ultimately reduce administrative burdens and help physicians to focus on what they do best–care for patients. Technology is only part of the equation,” Dr. Riddell said. “The real transformation happens when we bring together our best clinical and operational minds to rethink how schedules are managed.”
Traditionally, physicians and clinicians have kept their schedules closely guarded to capture the best surgical times and retain control over their time. But at Ochsner Health, the clinical team decided to embrace the open inventory model as part of the shared vision for better care and patient experience.
“Physicians and clinicians are opening up their schedules, and the results are already making a difference in our access, experience and quality,” said Dr. Riddell.
That theme — AI enabling operational transformation rather than replacing it — emerged repeatedly. At Lehigh Valley Health Network, part of Jefferson Health, Vice Chair of Operations Shadi Jarjous, MD, described an AI-assisted discharge instruction tool built directly into the EHR. The goal isn’t to reduce documentation time for physicians, but to improve what patients actually receive at one of the most consequential moments in their care: the transition home. AI is being used to generate discharge instructions that are clearer, more consistent, and meaningfully personalized — reducing unwarranted variation in what patients are told and improving their likelihood of following through.
“Technology should amplify compassion, not replace it,” Dr. Jarjous said. “Through AI-assisted discharge, we are not simply improving documentation — we’re aspiring to set a new standard for how healthcare supports patients beyond hospital walls.”
At Children’s Nebraska, the AI deployment is even further afield from anything in a traditional EHR. The system opened its Behavioral Health and Wellness Center in January 2026, and is now building a clinical curriculum anchored in virtual reality augmented with artificial intelligence for pediatric behavioral healthcare. Using a $5.5 million grant from the James M. Cox Foundation, the team is developing VR therapy pathways designed to help young patients practice emotional regulation, build coping skills, and reduce anxiety — with AI shaping the therapeutic environment in real time based on patient response.
“By developing pathways for education using VR therapy to expand clinical support, our expert team will lead patients to practice emotional regulation and build coping skills and social skills to decrease stress and anxiety,” said Chanda Chacon, president and CEO of Children’s Nebraska in Omaha.
In mental health more broadly, People Incorporated Mental Health Services in Eagan, Minn., is deploying AI tools to reduce administrative burden for clinicians — but the implementation goes well beyond note generation. CFO Kellan Tittle described a system that offers real-time clinical decision support during sessions, smarter scheduling that accounts for caseload sustainability, and predictive insights designed to identify when clinicians are approaching burnout levels before it happens.
“We know there will be a learning curve as we look to have all clinicians adopt this model so training and communication will be critical,” said Mr. Tittle. “We feel the pros outweigh the cons and are very excited to learn and refine it as we continue to receive feedback.”
Predictive and decision-support tools also featured prominently at Beth Israel Deaconess Hospital–Needham (Mass.), where AI governance and integration strategy are being stood up to address workforce stabilization, cost control, regulatory burden, and cybersecurity risk simultaneously. President John Fogarty said addressing these issues while also avoiding cyberattacks and promoting health equity has been paramount.
“We believe the predictive automation assets AI can bring to the organization hold high potential to resolve many of these longstanding challenges and are now working to establish an appropriate governance structure and integration strategy to optimize this technology,” he said.
What’s emerging across these deployments is a more sophisticated theory of AI value in healthcare — one that has moved past “AI will write the note” to “AI will redesign the workflow.” Scheduling intelligence, predictive caseload management, personalized discharge communication, immersive therapeutic environments: these are operational bets, not technology experiments. The health systems making them are increasingly treating AI governance — how you decide what to deploy, how you train staff, how you measure outcomes — as a strategic capability in its own right.
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