Something shifted in the last year. AI stopped being a conversation research organizations were having about the future and became one they're having about the here and now: policy, tools, daily workflows, and who's responsible when something goes wrong.
To find out more, we asked over 400 research professionals from both academic and corporate backgrounds to share their perspectives.
The result is The State Of AI In Research 2026: A Look At How Researchers & Organizations Are Adopting AI, our first benchmark report built entirely on original survey data collected from the research community. No synthesized external stats or analyst projections. Just what your peers are currently doing, and where the gaps exist.
Knowing Where Everyone Else Stands
There's a specific kind of pressure that comes from not knowing how your organization stacks up. Not knowing whether you're ahead or behind, spending too much or too little, moving too slowly on governance, while peers have already sorted it out.
That uncertainty is expensive. It leads to over-investing in things that don't need immediate attention or under-investing in those that do. A benchmark can change the calculations. When you know what's normal across your peer group, you can make sharper calls about where to focus.
This report gives you that reference point.
What You'll Walk Away With
The findings cover the full picture of AI adoption in research: how often people use AI tools day-to-day, where organizational strategy and infrastructure are lagging behind individual momentum, which tools have taken hold across research teams, and which tasks AI is being applied to now and over the next six months. 52% of respondents always verify AI outputs before using them, and the report explores what that verification culture looks like at the organizational level, where the picture gets more complicated.
The report also highlights what influences organizations to adopt AI and where the research community expects AI to deliver its biggest value in 2026, along with what resources teams say they need most to get there.
Beyond the findings themselves, the report includes three reflections on what these shifts may mean for research organizations right now. The intent isn’t to prescribe a single approach, but to provide a clearer read on the dynamics shaping the field so you can make informed decisions about your own path.
The Signal Is Already There
This is not a wait-and-see moment. The numbers bear that out. 87% of respondents use AI tools at least weekly. At the same time, 71% are operating without a formal AI strategy, and more than half have no process for evaluating whether their AI implementations are working. This doesn’t indicate resistance. It's a sign that adoption is moving faster than the systems needed to support it.
If those conversations are already happening on your team, this report will make them more focused. If they aren't yet, it will tell you why they should be.
The State Of AI In Research 2026 is available now, free to download. We built it for the research community because benchmarks only work when the data is shared. Download it, see where you stand, and decide what comes next.
