A key thread running through the discussion was the distinction between data, information, and insight. 

Namita Mediratta, global insights head, Deos, at Unilever, described AI as a “once-in-a-lifetime opportunity” for the insight sector, but only if it is used with intention. AI doesn’t replace the value of research, but it can help elevate the work of insight professionals by freeing them from some of the work that has historically slowed them down. 

AI has given organizations more information, faster information, and better structured information than ever before. But that doesn’t automatically create better decisions. In fact, it can make the role of insight more distinctive. 

When organizations are surrounded by more data than they know what to do with, the value of insight lies in knowing what matters, what is reliable, what is changing, and what should be acted on. 

That’s where insight becomes more important, not less. The sector can’t define its value only through data collection, platforms, tools, or technology. The real value is in helping organizations make sense of what is happening and make better decisions as a result. 

James Sallows, head of marketing effectiveness at the LEGO Group, made a similar point during the panel, arguing that the industry needs to find its “sweet spot” with AI and show that it is part of what the sector does, not an alternative to it. 

“What we deliver isn’t data or platforms or tech – what we deliver is insight,” he said. 

AI may change the way research is done, but it doesn’t remove the need for judgment, context, rigor, and consumer understanding. If anything, it makes those things more visible.

The industry is not moving through this change at one speed. 

When it comes to AI, “there is a real spectrum of engagement, understanding, and use of these tools,” said James Turner during the panel. 

Some organizations are already experimenting with advanced AI workflows. Others are still trying to understand which tools they are allowed to use, how to use them safely, and how to bring them into existing business processes. Many sit somewhere in the middle: interested in the opportunity, under pressure to move faster, but still rightly focused on questions around trust, governance, quality, and adoption. 

That’s why the future of insight can’t be built only around the most advanced users. The industry also has to support the teams that are still building confidence, capability, and permission to use these tools well.  

James also pointed to the role of governing bodies and the partnership between clients and suppliers in helping set the agenda. If AI is going to play a bigger role in insight, the industry needs clear expectations around quality, transparency, and responsible use. 

AI is only one part of a wider shift.  

Ruva Mankola, senior consultant at PA Consulting, noted that the industry has faced major shifts before, from self-serve platforms to big data and now AI. Each wave created anxiety about the future of research, but each also opened up new opportunities for the sector to evolve. 

MRS’s Business of Evidence 2026 review, while showing the scale and importance of the research and evidence sector, also highlighted the pressures facing it. Rob Marshall-Keeys, principal consultant at PA Consulting, described the industry as being at an “inflexion point”, with 83% of respondents citing tightening budgets, 78% pointing to cost pressures and commoditization of approaches, and 72% raising job displacement linked to AI or automation. 

Those figures clearly show the tension the industry is working through. On one hand, research is more embedded in strategic decision-making than it has been before, with 81% of research buyers believing insights lead to more confident decision-making within their organizations, while 87% agree research findings are an important strategic input driving key business and policy decisions. 

On the other hand, insight teams and partners are being asked to do more, move faster, and show value more clearly linked to decisions. 

While the sector has adapted before, the expectation now is sharper. That creates a challenge for traditional ways of working. If research is too slow, too disconnected, or too focused on outputs rather than decisions, it becomes harder to prove its value in the business. 

The question now is how the industry strengthens that role in a market where the speed, volume, and complexity of information are all increasing. 

The value of insight is not just in producing information. It’s in creating a clearer, more reliable connection between the real world and the decisions organizations need to make. 

That means understanding what consumers are noticing, thinking, feeling, and doing as markets move. It means giving businesses a way to track change with enough consistency to trust the data, and enough speed to act while the information is still useful. 

AI and automation can help with that, but only if they are built around the right purpose. Speed matters, but speed without confidence does not create better decisions. More data matters, but only if organizations can understand what it means and what to do next. 

The role of insight is not to flood organizations with more data, but to help them see what matters. That’s why the conversation around AI shouldn’t be framed only around efficiency. Cost and speed matter, especially in a pressured market, but they’re not the whole story. The bigger opportunity is to make insight more embedded in the way organizations make decisions.  That means insight that is connected, timely, comparable, and grounded in quality.  

Last week’s discussion was an important reminder of the scale of the UK research and evidence sector. A market contributing £18.74bn in GVA each year is not a small support function. It’s a meaningful part of the UK economy and an important part of how organizations, brands, and policymakers understand the world around them. 

But with that scale comes responsibility. 

The industry needs to be confident about its value, but also honest about what needs to change. It needs to embrace new tools without reducing insight to automation, move faster without weakening trust, and help organizations turn data into decisions. 

AI is changing the research industry, but it’s also revealing why insight matters. In a world where information is easier to produce than ever, the value of research lies in knowing what to trust, what to question, and what to do next. 

For Delineate, that’s where the future of insight is heading: closer to consumers, closer to decisions, and more connected to the moments that matter.