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Discover how R&D organizations are using data, evidence and AI to make confident decisions, and what it will take to connect them.
R&D teams are confident in their evidence, yet it is often scattered, incomplete or hard to interpret. Meanwhile, AI is moving into everyday R&D workflows.
The Corporate R&D of the Future report draws on a global survey of R&D and R&D connected professionals. It shows how organizations use data, evidence and AI to make decisions, where the barriers lie, and what they expect from the next five years. Dive into the findings to see how views differ by region, organization size and seniority, and why connected data, trusted evidence and AI are set to define the future of R&D.
Confidence is strong. 84% say their teams can access the evidence they need, and 83% trust its quality.
But evidence is often incomplete. 45% say important decisions are made before all the evidence is available, and 63% say their organization has acted on evidence later found to be flawed.
Fragmentation is the top barrier. 38% say evidence is scattered across too many disconnected sources.
Adoption is widespread. 55% say their organization uses AI regularly in R&D, and a further 32% are piloting it.
But integration is lacking. 83% feel well prepared for AI, yet 72% say it is effectively integrated into R&D workflows.
Trust is essential. Willingness to use AI rises when it fits existing workflows (55%), complies with regulations (52%) and is trained for factual accuracy (51%).
Connection is an advantage. 93% say organizations that connect internal and external data will have a competitive edge.
AI will transform decisions. 88% say AI will fundamentally change how R&D decisions are made, and 88% say those who combine it with trusted evidence will outperform.
But scaling is hard. 38% expect implementing AI at scale to be a significant challenge.
Stuart Whayman, President of Corporate Markets at Elsevier, discusses the report's findings.
63% of organizations have made an important R&D decision on evidence later found to be flawed. Asked what would help most, respondents pointed to five changes:
Connect internal data with external scientific evidence
Capture and reuse organizational knowledge, including failed experiments
Strengthen trust in evidence and AI through governance and validation
Tailor AI to organizational knowledge and workflows
Turn data into actionable insights
Explore the full report for deeper insights by region, industry and organization size.
Access the survey questions and data results used in the report: Download the databookopens in new tab/window
Read the latest findings from the Corporate R&D of the Future report
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