Research from the IBM Institute for Business Value confirms what many healthcare leaders already sense: AI has moved from pilot project to strategic priority.
In partnership with Oxford Economics, the IBV surveyed 102 healthcare executives from worldwide organizations averaging $5 billion in annual revenue. Their findings offer one of the clearest pictures yet of where AI is actually delivering value in healthcare today, and where the biggest opportunities still lie.
The headline figures are striking: 77% of healthcare leaders say AI is already delivering a measurable competitive advantage, and 69% expect it to meaningfully boost financial performance over the next three years. That’s not tentative experimentation; it’s an industry betting on AI as core strategy.
The macro case for that bet is significant, too. Broader AI adoption in the US alone could cut healthcare spending by somewhere between $200 billion and $360 billion a year, largely through better efficiency, more accurate diagnoses, and smarter allocation of resources.
Where AI Is Actually Being Used Today
Adoption is accelerating fast across both clinical and administrative use cases. Some of the most telling stats from the IBV survey:
- Inpatient monitoring (wearable health tracking) is projected to jump from 18% adoption today to 37% by 2028. Those numbers make this the most mature use case in the report, with 39% of executives indicating they’ve already fully implemented or are actively rolling out inpatient monitoring systems that flag early warning signs for patient health issues.
- Population risk stratification (predictive analytics for disease outbreaks) shows the steepest relative growth, meanwhile, from just 5% to 35%.
- Diagnostics (AI-assisted analysis of X-rays, MRIs, and CT scans) similarly climbs from 7% to 33%.
- Multidisciplinary care coordination via virtual health assistants, meanwhile, rises from 7% to 26%.
- Overall AI adoption across healthcare organizations is expected to grow from 20% to 58% by 2028. That’s nearly triple its current value.
- Agentic AI systems that can act autonomously within workflows, are projected to grow from 20% to 47% over the same period.
Workforce Shortfalls and Payer-Provider Relationships Are Top Drivers of AI Urgency
Underneath this enthusiasm and eagerness to adopt mature AI capabilities, however, is a hard structural problem: the World Health Organization projects a global shortfall of 18 million healthcare workers by 2030.
That gap is a major reason executives are leaning on automation not just for clinical tools, but for administrative relief. One-third (34%) of executives expect AI to help most by coordinating multidisciplinary teams across departments and hospitals, effectively acting as connective tissue in stretched organizations.
Even as diagnostic AI draws most of the public attention, 67% of healthcare leaders say their biggest opportunity is actually in payer-provider coordination and claims integrity—the unglamorous, paperwork-heavy processes continuing to consume enormous time and manual effort.
Today, 34% of executives are already applying AI to revenue and budget cycle management. Every hour AI saves on claims processing or discharge paperwork is an hour clinicians can redirect to patients.
Two Numbers Worth Watching: Security and Skills
Trust and readiness, meanwhile, remain the biggest gating factors. 53% of executives name patient data protection and cybersecurity as their greatest implementation challenge: an important reminder that AI ambition, ethics, and governance need to scale together.
Another 54% worry their own workforce doesn’t yet have the AI proficiency needed to fully capture the value on the table. Technology adoption is only half the equation; organizational readiness is just as important.
With a keen eye on these limiting factors, the IBV’s guidance for leaders comes down to just two moves: one, to build strong governance before scaling, with clear data policies, model transparency, and cross-functional buy-in; and two, to design AI to work with clinicians rather than around them, pairing automation’s speed with the judgment only people provide.
The most useful framing in the research, however, may actually be this: AI in healthcare isn’t about replacing the clinician-patient relationship. It’s about clearing away everything currently standing between them.
The Leap From Healthcare AI Insights to a Measurable Action Plan
The data is clear: healthcare organizations that pair AI ambition with strong data foundations and governance are the ones capturing real value, whether that’s in inpatient monitoring, claims integrity, or workforce coordination. Turning that opportunity into results is the real challenge, and takes both the right technology partners and the right data strategy.
Hakkoda, an IBM company, helps healthcare organizations achieve the data and AI maturity needed to move from pilot to production, and we have built repeatable frameworks for doing it securely, at scale, and with measurable outcomes.
Combined with IBM Consulting’s research investments and deep healthcare industry expertise, we help clients design technology roadmaps that address today’s urgent needs while preparing for what’s next.
Let’s talk today to identify where AI can create the most value for your organization and how we can help productionalize that value faster.
