From January 2026 through August 2026, our research team reviewed data from nine primary sources, including market research reports from Grand View Research and Fortune Business Insights, the FDA’s AI/ML-Enabled Medical Devices List, two Deloitte outlook surveys, and peer-reviewed clinical research published in JAMA, to understand the current size, growth trajectory, and real-world adoption of artificial intelligence across the healthcare industry.

How Big Is the AI in Healthcare Market?

The table below presents 2025 and 2026 market size figures, along with long-term growth forecasts, from the two largest published estimates of the global AI in healthcare market.

Global AI in Healthcare Market Size and Growth Forecast, 2025 to 2034

Research Firm	2025 Size	2026 Size	Long-Term Forecast	CAGR
Grand View Research	~$35 to 40B¹	~$50 to 55B¹	~$500 to 550B by 2033¹	~38 to 39%¹
Fortune Business Insights	~$35 to 40B²	~$55 to 60B²	~$1.0 to 1.1T by 2034²	~43 to 44%²

Note on methodology: figures above are rounded to the nearest $5B (and to the nearest percentage point for CAGR) for readability. Source reports publish more precise figures: Grand View Research cites $36.67B (2025) and $50.70B (2026); Fortune Business Insights cites $39.34B (2025), $56.01B (2026), and a 43.96% CAGR through 2034. See cited sources for exact values.

Key takeaways:

• Both major analyst firms agree the market is compounding at close to 40% a year, regardless of which absolute figure you use.
• The gap between the two firms’ long-term forecasts, $500B+ versus $1T+, shows how much “market size” depends on scope definitions, not just market reality; a nuance most coverage of this topic skips.
• Directionally, this is one of the fastest-compounding categories in healthcare technology, full stop.

Where AI in Healthcare Spending Is Concentrated

After seeing the overall market size, the next natural question is where that spending is actually happening. The table below breaks the market down by region.

Regional Breakdown of AI in Healthcare Spending

Region	2025 Revenue	2026 Projected Revenue	Regional Share	Key Growth Driver
North America	~$17B²	~$24 to 25B²	~44 to 54%²	Healthcare IT infrastructure, capital availability
Europe	~$11B²	~$15 to 16B²	~28%²	Clinical R&D, EHR standardization
Asia-Pacific	~$8B²	~$12B²	~21%²	Rapid adoption in China, India, Japan

Key takeaways:

• North America holds roughly half the global market, which matters for US-based multi-location operators benchmarking against “the market”: most of the spending they’re competing against is domestic.
• Asia-Pacific’s growth rate outpaces its current share, meaning the regional balance will likely shift over the next several years even if North America stays dominant in absolute terms.
• Europe’s growth is tied more to clinical and regulatory standardization than raw commercial adoption, a different growth driver than the other two regions.

What Kind of AI Is Driving the Growth

Market size and region only tell part of the story. This table breaks down what type of AI technology and application is actually driving the spending. This reflects the broader AI-in-healthcare category as a whole, not any single company’s product.

Market Segment Breakdown (What Kind of AI Is Actually Growing)

Segment Dimension	Leading Sub-Segment	Approximate Share
Component	Software solutions	~45%¹
Technology	Machine learning	~35%¹
Application	Robot-assisted surgery	~13 to 23%¹ (varies by year and source)
End-use	Pharmaceutical and biotechnology	~30%¹

Key takeaways:

• Software, not hardware or services, is where most of the spending is concentrated: this is a workflow and data story more than an equipment story.
• Robot-assisted surgery’s wide reported range, 13% to 23%+, reflects both real year-over-year growth and inconsistent category definitions across analyst firms.
• Pharma and biotech lead end-use spending, ahead of hospitals and provider organizations, a reminder that “AI in healthcare” is not primarily a clinical-care-delivery story yet.

Is Adoption Keeping Pace With the Forecasts?

Market size projections describe potential. Adoption data describes what is actually happening inside healthcare organizations today. The table below combines adoption rates, return on investment data, and regulatory clearance figures to answer that question.

Adoption Reality Check, ROI, and Regulatory Momentum

Metric	Finding
Organizations experimenting with or scaling generative AI	75%⁵
Organizations actually operating generative AI at scale	~22 to 30%⁶
Full enterprise-wide AI deployment	~2%⁶
Healthcare organizations using AI in some form	79%⁷
Reported ROI on AI investment	~$3 return per $1 invested, ~14-month payback⁷
Documentation time reduction from AI scribes, broad multi-site study	~10% (16 min/day); EHR time down ~3% (13 min/day)⁸
Documentation time savings, single large enterprise deployment	15,700+ hours saved over one year⁹
FDA-cleared AI/ML medical devices	1,451 cumulative through end of 2025; 295 cleared in 2025 alone⁴
Share of FDA clearances in radiology	~76%⁴

The data shows a real and widening gap between organizations experimenting with generative AI and those actually running it at scale. Three out of four organizations report experimenting with or attempting to scale generative AI, but only about a quarter report operating it at scale, and just 2% have deployed it enterprise-wide. This points to a market still dominated by pilots rather than full production use.

Key takeaways:

• There’s a real and widening gap between “experimenting with AI” (75%) and “operating it at scale” (22 to 30%): most organizations are still in pilot mode, not production.
• Documentation-time savings claims vary widely by scope. A rigorous multi-site trial shows modest (~10%) gains, while a single well-executed enterprise rollout can report much larger cumulative hours saved. Both are true; they’re measuring different things.
• Regulatory clearance is accelerating fast, with 295 devices cleared in 2025 alone, and remains heavily concentrated in radiology, so most of the “proof” of AI’s clinical value so far comes from one specialty.

What’s Next: Agentic AI in Healthcare

One more question naturally follows: where is this market heading next? The table below covers agentic AI, systems that can carry out multi-step tasks rather than simply respond to a single request.

Agentic AI in Healthcare

Metric	2026	2034	CAGR
Agentic AI in healthcare market size	~$1.8B³	~$19 to 20B³	~35%³

Key takeaways:

• Agentic AI is still a small fraction of the broader AI-in-healthcare market today, but it’s forecast to grow roughly tenfold within a decade.
• This is the segment to watch for multi-location operators thinking beyond single-task automation toward AI that can carry out multi-step workflows end to end.

What This Means for Multi-Location Healthcare Operators

Taken together, the data points to a market that is growing quickly in total size while still working through the gap between pilot programs and full-scale deployment. For multi-location healthcare organizations, the practical takeaway is less about the size of the market and more about where AI is already proving out: patient interaction data, documentation workflows, and increasingly, systems capable of acting on that data directly. Understanding what happened during a patient interaction, and using that information to inform what happens next, is one of the more immediately actionable applications of this broader trend, and it is an area where results can be measured directly rather than estimated from a market forecast.

Patient Prism’s Revenue Activation System applies this same principle to patient inquiries across every touchpoint. Healthcare networks using Patient Prism typically see 15-30% same-store appointment volume growth within 90 days, depending on adoption. Get a demo to see how it works for your organization.

References

1. Grand View Research. Artificial Intelligence In Healthcare Market Report, 2026–2033. grandviewresearch.com/industry-analysis/artificial-intelligence-ai-healthcare-market
2. Fortune Business Insights. Artificial Intelligence in Healthcare Market Size, Share, Growth Report, 2034. fortunebusinessinsights.com/industry-reports/artificial-intelligence-in-healthcare-market-100534
3. Fortune Business Insights. Agentic AI in Healthcare Market Size, Share, Forecast [2034]. fortunebusinessinsights.com/agentic-ai-in-healthcare-market-115702
4. U.S. Food and Drug Administration. “Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices.” fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices. Database last updated March 2026; cumulative figures cross-verified via MedTech Dive’s May 2026 database pull.
5. Deloitte. “Unpacking AI in Healthcare: Insights from the Health Innovation Conference (HIC) 2024 Breakfast Seminar.” deloitte.com/au/en/Industries/health-human-services/blogs/unpacking-ai-in-healthcare.html. States that 75% of leading healthcare providers are experimenting with data and AI solutions, per Deloitte’s State of Generative AI in the Enterprise survey series (Wave 3, Q3 2024).
6. Deloitte. “2026 Global Health Care Outlook.” deloitte.com/us/en/insights/industry/health-care/life-sciences-and-health-care-industry-outlooks/2026-global-health-care-outlook.html. Published December 2025, based on a survey of 180 C-suite health system executives conducted August to September 2025.
7. Microsoft. “Microsoft makes the promise of AI in healthcare real through new collaborations with healthcare organizations and partners.” Microsoft, March 11, 2024. blogs.microsoft.com/blog/2024/03/11/microsoft-makes-the-promise-of-ai-in-healthcare-real-through-new-collaborations-with-healthcare-organizations-and-partners/. Both figures (79% adoption, $3.20 ROI per $1 invested, 14-month payback) are stated directly on this page and sourced in its footnotes to IDC InfoBrief #US51364223 (Nov. 2023) and IDC Business Value of AI Survey #US51331223 (Nov. 2023), both commissioned by Microsoft.
8. Rotenstein, L., et al. Changes in Clinician Time Expenditure and Visit Quantity With Adoption of Artificial Intelligence-Powered Scribes: A Multisite Study. JAMA, 2026.
9. American Medical Association. AI Scribes Save 15,000 Hours, and Restore the Human Side of Medicine. https://www.ama-assn.org/practice-management/digital-health/ai-scribes-save-15000-hours-and-restore-human-side-medicine