Why R&D Waste Persists Despite Widespread AI Adoption

A new report finds that more than a third of organizations waste 25 to 40 percent of their R&D budget on projects that never reach market, and nearly half of teams estimate over $1 million in wasted investment per project killed during development or testing. The report, which examines R&D waste amid widespread AI adoption, says most organizations apply AI to execution tasks like data analysis and modeling rather than decision support, leaving the gap unclosed. Respondents indicated that better access to intelligence has the greatest value at early ideation and feasibility stages, before significant investment is committed.

This report examines R&D waste and how AI adoption has outpaced the intelligence needed to make consequential decisions well. What Attendees will Learn - Where R&D budget is lost. More than a third of organizations spend 25 to 40 percent of their R&D budget on projects that never reach market. - Why projects fail late. Almost half of teams estimate over one million dollars in wasted investment for each project killed during development or testing. - Why AI adoption has not closed the gap. Most organizations apply AI to execution tasks such as data analysis and modeling rather than to decision support. - Where intelligence matters most. Respondents say better access to intelligence has the greatest value at early ideation and feasibility before significant investment is committed.