Healthcare organizations are investing in AI, but mostly in pieces.
While AI spending in healthcare nearly tripled to $1.4 billion in 2025, a typical health system coordinates dozens of distinct vendors for AI and automation solutions, ranging from ambient AI scribes to AI-driven prior authorization apps.
This “vendor sprawl” is causing more problems than it solves, as managing those point solutions strains IT resources. Also, using multiple vendors for AI and automation misses the point of AI and automation: elevating quality, improving patient experience, and streamlining efficiencies.
But while 62% want one comprehensive AI partner, only 13% have one, according to a recent industry report.
Fortunately, health leaders are now waking up to the fact that vendor sprawl is eroding the ROI they were promised. As new AI applications and use cases enter the marketplace, it’s important to reframe our approach to technology adoption, and reconsider our broader organizational goals.
The Rise and Fall of the Fragmented ‘Point Solution’ AI Approach
Over the last decade, the sheer number of healthcare information technology (IT) applications used across health systems has skyrocketed.
According to the 2026 College of Healthcare Information Management Executives (CHIME) leadership survey, more than 40% of healthcare organizations use 75+ healthcare operations applications. A separate recent study indicated health systems use an average of 18 different EHR vendors across affiliated locations, departments and acquired practices.
But while federal policy has long encouraged and incentivized hospitals and clinicians to adopt interoperable EHRs (through CMS's Promoting Interoperability program and ONC's certification requirements under the 21st Century Cures Act), no equivalent framework yet governs AI.
The HTI-1 final rule was a first step. It sets baseline transparency and risk-management standards for predictive tools built into ONC-certified health IT, such as the EHRs used by most U.S. hospitals and physicians. But those protections are narrow. They apply only to AI the EHR vendor builds into its own certified system, not to the standalone tools a hospital buys and bolts on separately.
In other words, the very point solutions hospitals are accumulating fall outside the one federal rule that governs health AI today, and even that rule covers transparency, not interoperability. There is still no mandate requiring AI tools to connect with one another or with the systems around them, and the rules are still evolving.
Understandably, the surge of AI point solutions can be credited to AI’s success in reducing serious problems. Physician burnout, for example, is measurably impacted by ambient AI scribes. But with every individual AI point solution adopted, the task of integration grows harder.
As many as 69% of senior health system technology leaders cite vendor management and integration as their top obstacle to executing AI solutions, with some organizations spending 26–50% of IT staff time on it, according to a 2026 industry survey of senior leadership at medium and large U.S. health systems. Moreover, only 4% report adequate resources to sustain that level of oversight.
A More Cohesive AI Approach
Whittling down a stack of siloed vendor solutions to just a handful that work together seamlessly is a tall order. But through a more holistic AI-implementation approach and deeper vendor scrutiny, it is possible.
Growing AI capabilities starts by choosing a care partner that sees the entire realm of possibilities. The big picture. Optimizing efficiencies from the moment a patient or care coordinator schedules their appointment to the moment their claim is processed, and throughout the care continuum.
Not every vendor can oversee multiple AI use cases. And for some health systems, taking a point-solution approach to test the waters might be OK for today.
But working with a vendor that understands the “big picture” and how multiple AI-fueled systems should work together will only grow more important over time.
Most healthcare organizations understand this. As the CHIME survey noted, 75% of health leaders say operating across multiple tools is central to the challenge of health systems modernization.
The right care partner understands the twists and turns of the healthcare regulatory climate and is always a step ahead with every specification, interoperability standard, and compliance requirement. That ideal partner understands how ambient AI tools can not only listen, but also leverage clinical evidence and ancillary data to ensure a clinician’s concerns are documented and substantiated. That same ideal partner understands the quality of the note is critical, but that other aspects of documentation and data exchange are equally important.
Moving away from point solutions isn’t always fun. It’s exciting to check out the next hot, new AI application with sexy curb appeal and the promise of solving a hospital’s biggest challenge.
Yet the right AI care partner offers something more sustainable: multiple tools that work well together, and cover the entire cycle of a patient encounter. That type of care partner can help hospitals steer away from a “point” approach to maximize outcomes and ROI.
For most organizations, simply adding more to the AI stack is not sustainable. Swapping out point solutions that aren’t working well together and investing in a smarter approach with the right AI vendor, who sees the full spectrum of care and wants to build AI to support it, is a better way forward.
The editorial staff had no role in this post's creation.