Global Corporate R&D of the Future report reveals a paradox at the heart of R&D decisions: confidence in data is high, but gaps in quality and connection persist

NEW YORK, Nov. 12, 2026 /PRNewswire/ -- R&D teams are confident in their evidence, yet report making decisions based on flawed or incomplete data, according to Elsevier's Corporate R&D of the Future report, a global survey of more than 1,000 R&D leaders, managers and researchers at R&D-led corporations.

More than three quarters (76%) of respondents are confident in the quality of their data. Yet 63% of those who answered say their organization has at some point made an important R&D decision using data or evidence later found to be inaccurate, incomplete or outdated. About half (51%) say their organization has had to make an important R&D decision before all the evidence was in.

The survey findings show AI is moving into R&D decision-making, but expectations are running ahead of use: 81% expect AI to fundamentally transform how R&D decisions are made over the next five years, yet under half (47%) say it is used regularly in their organization's R&D function today.

Stuart Whayman, President, Corporate Markets at Elsevier, commented, "Confidence is not the same as accuracy. R&D teams are under pressure to decide faster, and often before all the evidence is in. Confidence keeps them moving, but it can't make up for evidence that is incomplete, outdated or unreliable. AI will raise the stakes, because it will amplify whatever evidence it is given, good or bad. The advantage will go to the organizations that can bring their evidence together and trace and verify what sits behind their decisions."

Key findings

The report looks at how R&D teams use data and evidence to make decisions, where that evidence comes from, how well it is connected, and how AI is being applied and trusted.

• Access is not enough. 78% have access to the third-party evidence they need, yet more than half (56%) of those still report at least one barrier. Across all respondents, the top barriers are scattered sources (42%), slow finding and synthesis (32%) and not knowing what evidence exists (30%).
• Respondents in APAC (90%) are most likely to have access to third-party evidence, compared to 73% in North America and 77% in Europe.
• AI is common, but not yet routine. 47% say AI is used regularly in their organization's R&D, and a further 40% say it is being piloted. Personally, most respondents use AI across a range of R&D activities, led by data analysis (71%), literature search (70%), and competitive intelligence (70%).
• Trusted evidence is seen as the AI advantage. 86% believe organizations that combine AI with trusted, high-quality evidence will outperform those that do not.
• Compliance, ease of use and accuracy are among the top factors that would increase willingness to use AI. 55% select AI that complies with laws and regulations, 54% AI that is easy to use and integrates with workflows, and 54% AI trained for factual accuracy and safety.
• Compliance is a bigger draw in Europe. Among all respondents, 64% in Europe say they would be more willing to use AI if it complies with laws and regulations.
• Scaling AI divides opinion. 48% say implementing AI at scale will be a significant challenge. The priorities selected most often for the next five years are building AI skills across the organization (65%), turning data and evidence into actionable insights (62%), and tailoring AI to organizational knowledge and workflows (59%).
• Scaling is seen as a challenge more in North America. Among all respondents, 56% in North America say implementing AI at scale will be a significant challenge, against 50% in Europe and 34% in APAC.
• General-purpose tools lead for literature search. Of those answering, 48% use general-purpose AI tools such as ChatGPT or Copilot for literature search, against 23% who use specialist scientific AI tools. For data analysis and modeling, specialist tools are the most common choice.

Elsevier's research also reveals regional differences in how R&D leaders and managers view their evidence and AI:

Bases (R&D leaders and managers): North America n=183, Europe n=234, APAC n=275. Don't know answers are excluded, so bases vary slightly by question. South America (n=34) and the Middle East & Africa (n=33) are not shown because of small samples.

The full Corporate R&D of the Future report, which also compares views by region, organization size and role and sets out recommendations for R&D organizations, is available at www.elsevier.com/insights/corporate-r-and-d-of-the-future.   

About the survey

Corporate R&D of the Future is based on an online survey, conducted by email invitation between August and October 2026, of 1,038 R&D leaders, managers and researchers at R&D-led corporations in 55 countries across North America, South America, Europe, the Middle East and Africa, and Asia Pacific. Responses are weighted. Figures may not sum up because of rounding. Full methodology is in the report appendix. Figures on flawed decisions exclude respondents who answered don't know or preferred not to say.

About Elsevier

Elsevier is a global leader in advanced information and decision support. For over a century, we have been helping advance science and healthcare to advance human progress. We support academic and corporate research communities, doctors, nurses, future healthcare professionals, and educators across 170 countries in their vital work. We help impact makers achieve better outcomes with research and clinical-grade solutions built on the world's leading evidence-based scientific and medical content, precision AI, and expert human assessment. We champion inclusion and sustainability, working with the communities that we serve. The Elsevier Foundation supports research and health partnerships around the world.

Elsevier is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. For more information, visit www.elsevier.com and follow us on social media @elsevierconnect.

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