For years, artificial intelligence (AI) in healthcare felt like a future-facing concept. It was (and still is) the hot topic of every major health conference across the industry. But now, healthcare is entering a new phase of AI adoption.
Many leaders are moving beyond experimental ideas and pilot programs. Today, organizations are increasingly looking for ways to use AI to solve real business and operational challenges while supporting providers and improving the patient experience.
To better understand how the market is evolving, let’s take a closer look at the state of the AI market, where adoption and investment is happening, and how the technology is being applied across clinical, operational, and business functions.
State of the AI market
Let’s start by stating the obvious: Money is pouring into the AI market hand over fist. In 2024, the total investment in the global AI market grew to more than $252 billion, an increase of 25% from 2023, and a thirteenfold increase since 2014, according to a report by Quid and Stanford University.
And healthcare is becoming one of the largest drivers of that investment activity. A report published by The Business Research Company stated that, in 2026, the global healthcare AI market is valued at $31.97 billion. The market is projected to grow at a CAGR of 30.2% year-over-year to reach a staggering $91.85 billion by 2030.
That momentum is also driving significant investment in AI startups across the healthcare sector. Menlo Ventures reports that at least eight AI unicorns—startup companies valued at more than $1 billion—have been produced, focused on areas such as clinical documentation, payor operations, revenue cycle management, and operational efficiency.
Some of the industry’s biggest players are also placing bold bets on AI. Here are just a few of the major moves made in the last 18 months:
- Kaiser Permanente deployed Abridge’s ambient documentation solution across 40 hospitals and more than 600 medical offices, marking one of the largest rollouts of generative AI in healthcare history.
- Mayo Clinic announced plans to invest more than $1 billion into more than 200 AI-related projects over the next few years.
- SimonMed, one of the largest radiology groups in the U.S., is piloting solutions from more than 50 AI vendors across multiple workflows.
Several factors are fueling this wild growth. Healthcare organizations are managing increasingly large and complex volumes of data while simultaneously facing staffing shortages and clinician burnout, rising costs of care, and growing demand for more personalized care. What’s more, ubiquitous adoption of electronic health records (EHRs) and advances in medical imaging technology and early disease detection are creating new opportunities for AI-driven solutions.
Where is AI adoption most prominent?
Historically, healthcare has always lagged behind other industries when it comes to adopting emerging technologies. That notion is a thing of the past now. Today, healthcare is becoming America’s AI powerhouse. Menlo Ventures revealed that in just two years, healthcare went from 3% adoption of domain-specific AI tools to 22%. By contrast, it is the broader U.S. economy that is slow on the draw. Only 9% of companies across other sectors of the economy have implemented AI solutions, and most rely on general tools like ChatGPT.
AI adoption is now accelerating across nearly every corner of the healthcare industry, spanning providers, life sciences companies, payors, digital health organizations, and more. An AMA survey suggests that AI has quickly become part of everyday medical practice, and more than 80% of physicians use it to improve patient care.
NVIDIA’s State of AI in Healthcare report breaks down the top areas of AI adoption across the healthcare landscape.
Fig 1. Top areas of AI adoption across major segments of the healthcare industry. Data sourced from NVIDIA’s 2026 State of AI Healthcare and Life Sciences survey.
According to the survey, generative AI tools and large language models are currently the most widely adopted AI technologies in healthcare. The technology has a wide range of emerging uses in the healthcare landscape, from helping life sciences companies develop drugs and analyze clinical trials to summarizing notes and alleviating administrative burdens. AI-powered systems used to analyze data was the second most-used application, followed by agentic AI—a relative newcomer to the field.
However, adoption is not occurring evenly across every use case. A recent McKinsey report shows how healthcare leaders are deploying generative AI technology in their organizations.
Fig 2. Where generative AI is being implemented in key segments across the healthcare industry. Data sourced from McKinsey & Company.
From the chart, we can identify a few core areas across major types of healthcare organizations where generative AI is being implemented. Fifty-four percent of clinical care organizations prioritize clinical productivity, which includes acute and ambulatory provider operations, followed by applying AI to make administrative tasks more efficient (38%) and improving the patient engagement experience (32%). Payors also prioritize administrative efficiency (34%), followed by improving software infrastructure (30%) and patient engagement (24%). Unsurprisingly, a majority of healthcare services and technology companies leverage AI for software infrastructure most (52%), followed by administrative efficiency (50%), and a tie between patient engagement and clinical productivity (both 34% respectively).
This perspective is further supported by the Menlo Ventures report, which also investigated how healthcare providers are spending their AI budgets. We can see that a significant deal of money is being invested into AI solutions related to ambient documentation and medical coding and billing.
Fig 3. Where healthcare providers are spending money on AI. Data sourced from Menlo Ventures.
What’s most interesting about all these findings is that they reveal where healthcare organizations believe AI can deliver immediate and measurable ROI. From the data, it appears that investment is concentrating in areas tied directly to administrative friction, workforce strain, and streamlining complex workflows. Tasks like scheduling appointments, documenting patient interactions, and submitting claims are repetitive, time-intensive, and contribute to provider burnout.
It also suggests a narrative that healthcare leaders are not leveraging AI to replace clinicians. Instead, technologies that can help overextended staff work more efficiently and alleviate burdens are being prioritized. More importantly, it keeps physicians focused on where they are needed most—with patients.
The future of healthcare depends on more than just AI
Despite the rapid pace of AI adoption in healthcare, significant roadblocks still remain. Concerns around patient privacy, data security, regulations and governance, interoperability, and the accuracy (and believability) of AI chat bots continue to shape how leaders best use the emerging technology. Many organizations are also still working to determine how to measure ROI, integrate AI into existing workflows, and build trust among their staff and patients.
At the same time, AI alone will not guarantee success. Rather, success will hinge on knowing where AI adds the most value in your organization, and how you can use it to help your people do what they do best.
As investment in AI continues to accelerate, healthcare data will become even more important for guiding strategy, generating reliable insights, and driving measurable outcomes. After all, AI models are only as effective as the data supporting them.
Definitive Healthcare helps organizations across the healthcare ecosystem access the insights they need to better understand the market, identify opportunities, and make more informed decisions. Book a demo today to learn how we can help support your AI-driven strategies with trusted healthcare data and analytics.
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