AI in Clinical Trials Poised for Rapid Growth with a 22.6% CAGR Forecast
“According to BCC Research, AI is speeding up clinical development with smarter recruitment, better analytics, and real-time decision support across global trials.”
Boston, Jan. 21, 2026 (GLOBE NEWSWIRE) -- Artificial intelligence (AI) is rapidly transforming how clinical trials are designed, conducted and monitored, bringing automation, predictive insights and real-time decision support into every phase of research. According to BCC Research, Global Artificial Intelligence (AI) in Clinical Trials Market, the global market for AI in clinical trials was valued at $2 billion in 2024 and is projected to increase from $2.4 billion in 2025 to $6.5 billion by the end of 2030, growing at a compound annual growth rate (CAGR) of 22.6% from 2025 through 2030.
Why is this report relevant at this time?
AI adoption in clinical trials is accelerating as sponsors face increasing pressure to shorten development timelines, manage costs, and overcome recruitment challenges. Advances in natural language processing (NLP), predictive analytics, and data integration are becoming more practical, enabling large-scale, real-world application. At the same time, evolving regulations and global competition for trial participants are pushing organizations to modernize trial operations and embrace digital transformation.
This report provides a comprehensive look at how AI is addressing these challenges and outlines the key trends, emerging technologies, and market opportunities that are shaping the future of clinical research.
Investors / and the finance angle
For investors, AI in clinical trials represents a high-growth digital health opportunity. With a 22.6% CAGR and strong demand from pharmaceutical and biotech companies, CROs, and research and academic institutes, the market is positioned for rapid expansion. The report helps financial decision-makers understand where value is created (software vs. services, cloud vs. hybrid, key regions) and how AI can reduce time, cost and risk in drug development.
According to the author of the report, “AI is moving from pilot use to becoming a core enabler of faster, smarter and more efficient clinical trials. Stakeholders who understand this shift early will be better positioned for future growth.”
Report Synopsis
| Report Metric | Details |
| Base year considered | 2024 |
| Forecast period considered | 2025-2030 |
| Base year market size | $2 billion |
| Market size forecast | $6.5 billion |
| Growth rate | CAGR of 22.6% for the forecast period of 2025-2030 |
| Segments covered | Component, Phase, Deployment Mode, Therapeutic Area, End User |
| Regions covered | North America, Europe, Asia-Pacific, South America, Middle East and Africa |
| Countries covered | U.S., Canada, Mexico, U.K., Italy, France, Germany, Spain, Switzerland, Denmark, Belgium, the Netherlands, Sweden, Russia, China, India, Japan, South Korea, Australia, New Zealand, Singapore, Malaysia, Thailand, Indonesia, Brazil, Argentina, Colombia, Paraguay, Peru |
| Market drivers |
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Additional Insights
- Up to 50% reduction in patient recruitment time: AI-driven patient matching and outreach tools can cut recruitment timelines by as much as half, addressing one of the most critical bottlenecks in drug development.
- Over 30% improvement in predicting trial outcomes: AI-based analytics can improve the accuracy of predicting trial outcomes by more than 30%, enabling earlier identification of potential failures and smarter go/no-go decisions.
Emerging Technologies
- Machine Learning for Predictive Analytics and Stratification: Helps identify ideal patient groups, forecast trial outcomes, and reduce risks earlier in the development process.
- NLP for Extracting Insights from Unstructured Data: Analyzes clinical notes, medical records, and reports to uncover insights that would otherwise require extensive manual review.
- Decentralized and Virtual Trial Platforms: Enable remote participation, improving patient access and reducing site-based delays, especially in hard-to-reach populations.
- Cloud-based AI Platforms: Provide scalable, secure infrastructure for processing large clinical datasets, supporting faster analysis and smoother collaboration across trial sites.
Market leaders include:
- AICURE
- CONCERTAI
- DNANEXUS INC.
- INSILICO MEDICINE
- INTELLIGENCIA AI
- IQVIA
- MEDIDATA
- MERATIVE
- NVIDIA CORP.
- PHESI
- SAAMA
- TEMPUS
- TRINETX LLC
- TRIOMICS
- UNLEARN.AI INC
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About BCC Research
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