Seventy percent of healthcare payers and providers are actively implementing generative AI technologies, moving beyond experimental use cases into enterprise-wide deployment.
That’s according to the Healthcare AI Adoption Index, a recent report from Bessemer Venture Partners, Amazon Web Services, and Bain & Company, which finds that AI is increasingly embedded in both clinical and administrative functions.
This momentum is being driven by significant investments in technology infrastructure as organizations look to enhance patient care, streamline processes and improve outcomes.
Nearly three-quarters of healthcare organizations surveyed said they have increased their IT spending over the past year, with a strong expectation that these investments will continue to rise.
Among biopharma executives, 60% have set near-term return on investment (ROI) targets for AI initiatives, highlighting a focus on measurable, value-driven outcomes.
The report also reveals that 65% of healthcare leaders are currently piloting or scaling AI projects across their organizations.
Within biopharma, 74% of respondents have already implemented AI in research and development processes, particularly for drug discovery and clinical trial optimization.
On the provider side, 58% are using AI for administrative tasks, such as medical coding, billing and scheduling, while 44% are deploying AI for clinical decision support and imaging analysis.
The report indicated regulatory acceptance of AI is also accelerating, with the number of FDA-approved AI/ML-enabled medical devices surging 30 since 2014.
The report noted this acceleration suggests a shift from pilot projects to commercially viable and clinically trusted solutions.
Despite these advances, challenges remain, with around 47% of healthcare leaders citing data quality and integration issues as major barriers to AI adoption and 39% expressing concerns about regulatory compliance and data privacy.
Talent shortages are also a worry: 42% of respondents indicated a need for skilled personnel to manage and scale AI systems effectively.
Despite the challenges, there is broad optimism over AI, with 81% of healthcare executives believing AI would significantly improve patient outcomes within the next five years, and 78% said they expect AI to drive cost efficiencies across their organizations.
The report notes that the most successful adopters of AI are those taking a strategic, enterprise-level approach – moving beyond isolated use cases to build comprehensive AI roadmaps aligned with business goals.
“This wave of AI adoption has been driven by ‘test and learn’ urgency, with boards and CEOs pushing teams to discover possible use cases,” the report stated. “Mid-to-large providers are the exception, as they are early adopters with more resources to bring AI into production.”
Earlier this month, Chicago-based health system Rush launched ambient AI system-wide after a pilot showed 74% of clinicians felt less burnout, 95% wanted to keep using it, and providers used 25 non-English languages, including Spanish, in 35% of visits in one month.
Meanwhile, Manipal Hospitals has cut pharmacy order times to under five minutes and reduced nurse handoffs by 78% using Google’s GenAI, which now powers its ePharmacy platform and cloud-based workflow systems.
IBM and Google recently launched AI initiatives to enhance enterprise intelligence and surface clinical data at the point of care, while a separate partnership aims to improve social determinants of health programs and outcomes across the healthcare ecosystem.
Nathan Eddy is a healthcare and technology freelancer based in Berlin.
Email the writer: [email protected]