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While 92% of respondents plan to increase AI investment, early adopters have a big advantage across nearly all key metrics
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NEW YORK, May 18, 2026 (GLOBE NEWSWIRE) — Medidata, a Dassault Systèmes brand and leading provider of clinical trial solutions to the life sciences industry, today released its second annual report on the state of Artificial Intelligence (AI) in Clinical Trials©. The 2026 research reveals a pivotal shift from industry-wide deployment of experimental pilots toward a significant advantage for early adopters with the longest track record of operationalizing AI.
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The independent survey of 200 senior decision makers across pharmaceutical companies, biotech firms, and CROs, highlights that while the appetite for AI is near-universal, the ability to operationalize it varies widely. Most notably, 72.9% of “Early Adopters” are now seeing a reduction in clinical trial timelines. The survey was conducted for Medidata by the Everest Group, a leading independent global research and advisory firm.
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“By tracking these metrics annually, we are providing the life sciences industry with a consistent benchmark for AI maturity,” said Lisa Moneymaker, chief strategy officer at Medidata. “The 2026 data reveals that we have moved past the era of speculation. We are now seeing a clear performance gap between those who are scaling AI and those stalled by legacy infrastructure. Our goal with this ongoing research is to give the industry a longitudinal roadmap to help bridge that gap and turn AI’s potential into predictable clinical outcomes.”
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Key Findings:
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- Early Adopters Set the Pace: 72.9% of respondents with more than 18 months of AI experience report a reduction in clinical trial timelines. Additionally, a similar 67.5% of respondents are seeing a reduction in protocol deviations.
- Unprecedented Investment: 92% of respondents plan to increase AI spend, while only 1% expect a decrease.
- Ambitious Expectations: 82% of those surveyed expect a 2–3X return on investment (ROI), with nearly two-thirds (63%) expecting to achieve their ROI within 12-24 months.
- From Automation to Prediction: Over the next 3 years, respondents say they will prioritize protocol and operational simulation (31%) and digital twins to model patient, site, and trial outcomes (26.5%).
- Scaling Challenges Remain: Integration complexity (79.5% of respondents), model accuracy (77.5%), and weak data foundations (75%) remain top barriers.
- Trust Above All: More than 63% of respondents rate data trust and regulatory compliance as critically important; 64.5% require legal and compliance review; 63% mandate human oversight.
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An Industry-Wide Benchmark
The 2026 report establishes a critical baseline for how the life sciences sector evolves in the face of rapid technological change. By providing brand-agnostic insights into the hurdles and successes of the entire ecosystem, Medidata continues to serve as a thought leader in defining what “excellence” looks like in the age of AI-driven medicine.
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“The industry is clearly moving past the experimentation phase of AI in clinical development. Investments are rising, and expectations are becoming more grounded. Incremental improvements are evident, but enterprise-wide transformation will require stronger data foundations, integrated and close-knit environments, and verification at scale,” said Chunky Satija, Partner, Everest Group. “At the same time, early adopters are beginning to demonstrate how sustained investment and deeper integration can translate into broader operational gains, particularly as use cases mature beyond initial pilots. Organizations that take a long-term, execution-focused approach will be best positioned to convert early momentum into durable, enterprise-level impact.”
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