The Next Wave of AI Adoption Is Taking Shape
As part of a recent strategic planning activity at Environics, we spoke with a number of clients about AI, covering a range of questions. When you think about AI and your business intelligence needs, what are your fears? What are your hopes? How do you see the research you do changing in the coming years? How do you see your relationships with research companies changing? What do you think you will expect of research companies in the future?
We’ve done a lot of work over the years on the adoption of innovation – looking at why some individuals and organizations tend to embrace innovations right away, and what happens next. We’ve found that if you really want to understand the implications of a new innovation, early adopters are not the group you tend to learn the most from. They’re often too driven by novelty itself to offer reliable insight into the meaning of a given change. It’s the next group of adopters you really need to listen to. They are open to new ideas and not afraid of change. But they aren’t attracted to shiny things. They’re attracted to real, meaningful innovation. Once they see a clear path to the benefits of a change, they’ll put in the time to adopt a new tool or approach in a serious way. They make great partners for working collaboratively on innovation.
We learned several things from these pragmatic clients.
First, we heard that people are tired of hype and demos on tools. They are looking for meaningful guidance to help them navigate the coming challenges. Most of the clients we spoke with are actively exploring AI, but very few feel they have everything figured out. Some are building internal tools and connecting AI to their knowledge systems. Others are proceeding cautiously, taking seriously the constraints imposed by governance, privacy concerns, and organizational policies instead of sidestepping them for the sake of speed. They are looking for trusted partners who can help them understand where AI adds value, where caution is warranted, and how to integrate AI thoughtfully into decision-making.
We also heard that clients want partners to help them do the things that were once out of reach. Saving money and time are attractive benefits, but they are not the whole story. Increasingly, clients are using AI to search across large collections of reports, synthesize information from multiple sources, and surface knowledge that would previously have been difficult to access. As AI’s potential comes into clearer view, they’re imagining research as something more dynamic and interactive than a static report. The opportunity with these clients is not simply to do existing work faster; it’s to help them answer questions that were previously too difficult, too time-consuming, or too expensive to tackle.
Above all, we heard that clients want to use AI to enhance their human teams’ ability to see insights and act on them. Many are already using AI tools to summarize reports, generate recommendations, and explore findings. Yet there was a remarkably consistent message: AI does not replace expertise. Clients still want help understanding what findings mean, what actions they should take, what risks they should consider, and what questions they may not be asking. They are skeptical of AI deliverables that lack appropriate human oversight and are concerned about managing the risks of overreliance on automated outputs.
We’re excited about working with clients to move forward on things we only dreamed about previously. Our recent conversations reinforced something important: while the tools are changing rapidly, the need for thoughtful judgment, context, and human understanding remains as strong as ever.
The goal is to enable human potential, not replace it.
