Here’s everything I learned at health tech’s two biggest conferences of the year

The health tech industry is undergoing a fundamental transformation as AI-powered automation shifts from a futuristic vision to an immediate necessity. After attending HIMSS 2025 and ViVE 2025, two of the industry’s most important gatherings, and having the opportunity to meet with dozens of friends and colleagues across the industry, I think a clear picture is emerging. Something stood out at this year’s events — I’ll call it a vibe shift.

A year ago, every panel, booth conversation, and executive roundtable seemed dominated by questions and hand-wringing over AI safety, effectiveness, and regulatory uncertainty. The theme could have been described as, “Is AI ready for prime time in healthcare?” This year, the narrative was completely different. The question is no longer, “are we sure that AI is safe enough to use?” Instead, the conversation has become, “how far and how fast can we go?”

As an example, as I showed health system executives examples of Notable’s AI Agents making phone calls, I heard more questions about “what else can we have this do?” than I did about “how can we take on the risk of an AI phone call?”

This shift reflects a rapidly maturing market as well as some very tough operational realities that healthcare delivery organizations face. AI in healthcare is no longer theoretical. It’s happening, it’s scaling, and I saw CIOs, CMIOs, and operational executives focused on execution, adoption, and maximizing impact.

1. AI-driven automation is no longer optional—it’s a strategic imperative

One theme was unmistakable across both conferences: economic pressures and workforce shortages are forcing health systems to turn to AI-driven automation at an unprecedented pace.

Major institutions, including large academic medical centers (AMCs), face massive budget cuts due to reduced federal funding, downward pressure on reimbursement, rising labor costs, and an inability to hire enough workers to meet demand. I heard several executives starting to compare this moment to early 2020, when the COVID pandemic broke out, and there was a rapid expansion and acceleration in telehealth and other digital health projects. Projects that had previously seemed too risky or unimportant flew forward overnight as macro circumstances completely upended the seemingly stable status quo. All health systems have stories about digital projects where they achieved “3 years in 3 weeks.”

The financial macro-trends are starting to drive the same shift with automation technologies. More and more care delivery organizations are seeing that they no longer have the option to solve every problem by hiring more staff. More staff in the call center, more staff to do chart abstractions, more staff to transcribe faxed documents, more staff doing coding and billing, and on and on. With millions of open administrative roles in the U.S., turnover rates nearing 30% for non-clinical roles, and looming massive margin pressures, health systems either cannot afford or cannot keep these roles filled, and they are rapidly realizing that they must automate wherever possible. I shared the stage at HIMSS with Brian Schuetz, Executive Director of MIT Health, where they have been able to realize Patient Service Representative labor efficiencies of more than 40%. 

Executives that I talked to were particularly focused on AI-powered workflows in:

• Contact Centers—automating inbound call handling for things like scheduling and prescription refills and outbound calls for things like closing care gaps, rescheduling appointments, and more
• Revenue Cycle Management—streamlining prior authorizations, coding compliance audits, HCC coding, payments, and patient financial assistance
• Chart Abstraction for Compliance & Quality—reducing the need for manual chart reviews across population health, inpatient nursing, compliance, and more
• Referrals & Fax Processing—eliminating inefficiencies in traditional referral workflows
• EHR In-Basket Management—helping providers handle message overload with AI-supported triage

The economic realities of healthcare in 2025 have removed much of the hesitation that previously slowed adoption. AI-powered automation is now seen as the only viable path forward for many institutions.

2. CIOs and CMIOs are leading AI-driven transformation

At both HIMSS and ViVE, the conversations were clear: CIOs and CMIOs see the future, understand AI’s potential, and are in the driver’s seat when it comes to AI strategy and platform selection.

CIOs are being tasked with solving systemic challenges created by disconnected point solutions. They want platform-based approaches that reduce IT costs, simplify integrations, and allow their internal teams to build, configure, and customize for their unique needs. They realize that AI is advancing rapidly which means that today’s prebuilt solution might be quickly out-of-date, and therefore the most effective options are flexible, configurable AI platforms, that pull in the latest LLMs, and that IT teams can use to automate workflows across the enterprise.

CMIOs deeply understand the nuances of clinical workflow pain points, and also have a long history of being able to translate their deep insights into building and configuring custom workflows. They did this for many years with the EHR, which gave them configurability to solve operational challenges, and they are now seeing the opportunity for AI tools that allow them to build and refine solutions.

For example, Brian Schuetz of MIT Health shared on stage what he built using Notable. Like many organizations, he has clinicians auditing 5 notes each quarter for each provider to assess competency and quality. This is a very small sample size and very labor intensive process. To supplement this process, he used Notable’s Flow Builder to automate this chart audit process and is now able to also do it at scale across all provider notes.

Empowering IT teams and Informaticists with an AI-driven toolset they can configure and use to solve operational problems represents a major opportunity for health tech companies that provide configurable automation solutions rather than rigid point solutions that do just one thing.

3. Large health sstems are looking for AI platforms—not a point solution for every problem

One clear pattern at HIMSS and ViVE was a rejection of narrow, single-use AI tools in favor of enterprise-wide AI platforms that can automate many workflows, across any service line or operational area.

CIOs struggle with managing the overhead and the cost of point solutions. CIOs have described to me the challenge with every service line choosing its own point solution for similar goals—for example, Cardiology, Oncology, and Orthopedics each choosing different vendors for collection of patient-reported outcomes. 

These organizations are looking for AI platforms to handle multiple use cases across the entire enterprise. They don’t want to build everything from scratch on top of an LLM like GPT 4o, but they also don’t want to be locked into a solution that just does one thing. They are looking for something in between: a configurable, extensible platform, leveraging the newest and best LLMs, that supports out of the box use cases as well as customization and adaptability across new use cases.

4. How mature AI platforms will win—and why others will fall behind

Walking around the exhibit halls at both HIMSS and ViVE, you could not help be overwhelmed by the vast number of companies pitching AI products or using the term “Agents.” The question is no longer whether health systems will use AI—but which types of platforms will gain lasting traction. The companies best positioned to win in the coming years will be the ones that:

1. Provide a broad set of AI capabilities, not just a single use case

Health systems are realizing that point solutions create the same vendor fragmentation challenges they have been trying to solve. The most successful AI platforms will provide multiple AI agents that work seamlessly together—covering everything from contact center automation to chart summarization, revenue cycle management, and prior authorizations.

2. Demonstrate mature integrations with existing IT infrastructure

Health systems are already deeply invested in core systems like EHRs, CRMs, and call center infrastructure. They don’t want to replace these systems, and they don’t want to spend resources trying to train users to change their workflows. They want AI that is integrated into existing systems and existing user workflows, enabling much more rapid adoption. Solutions that understand deeply the existing workflows of providers, nurses, care teams, and staff, and how they use existing systems of record, will be much better positioned to see rapid adoption. 

3. Offer configurability

While health systems do want solutions that they can trust to deliver significant financial ROI, they don’t want to stop there. They also want AI platforms that can continue to deliver value by allowing them to extend to new use cases through configuration. The platforms that succeed will include:

• No-code / low-code AI builder tools so CIOs and CMIOs can implement custom automations
• Enterprise-grade integrations that connect with EHRs, CRMs, and APIs to a third-party ecosystem of services and content
• Security and governance controls that they can trust for enterprise-ready access controls, testing, change control, and more

Final takeaways

My takeaway from HIMSS 2025 and ViVE 2025 is this: The AI debate in healthcare has shifted from “can we afford the risks?” to “how can we afford to maintain the status quo?”

Healthcare executives are no longer hesitating. They see the acute needs amidst financial and labor headwinds, and they are actively searching for AI platforms that can automate workflows enterprise-wide. Companies that deliver broad, configurable automation platforms—not just single-use products—will lead this next wave of digital transformation in healthcare.

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