By Crispin Beale, Worldwide CEO of IDX and Chief Executive of the Insight250
For much of my career, the challenge for businesses has been getting their message heard. Today, we face a different question: who is actually telling our story, and increasingly, it isn't actually us. When someone asks an AI assistant about an organization, its reputation or its expertise, the response is often drawn from sources that an organization may not have ever even seen. Some will be accurate, others will be outdated or misleading, and the problem is that the person asking the question may never look beyond that initial answer.
This has significant implications for how businesses communicate and build trust. It also raises important questions for the insights industry about evidence, accuracy and the continued importance of human judgement. I've often spoken about bringing artificial intelligence and human intelligence together, something I call AI:HI. AI offers extraordinary capabilities in processing information and identifying patterns at scale, but human intelligence remains essential for understanding context, challenging assumptions and deciding what information actually means. As AI becomes more influential in shaping perceptions, getting that combination right will only become more important.
Evidence matters more than volume
One recurring theme in my conversations with leaders throughout the recent Insight250 interview series is that more data doesn't necessarily lead to better decisions. Instead, what matters is our ability to interpret it, understand its limitations, and turn it into meaningful insight, and the same principle applies to communications. AI has made it easier than ever to produce content, but more information doesn't automatically create credibility. As the volume grows, demonstrating that something is accurate, original and supported by evidence becomes increasingly valuable. For organisations, this means thinking beyond what they want to say about themselves. They need to consider what evidence supports those claims, where it can be found and whether it will stand up to scrutiny.
For our industry, this should be familiar territory. Establishing what is true, understanding why it matters and communicating it responsibly is fundamental to what we do.
AI is changing how opinions are formed
Research published by Pew Research Center in 2025 found that Google users were less likely to click traditional search results when an AI-generated summary appeared. Just 8% of visits featuring an AI summary resulted in a click, compared with 15% when no summary was shown. If people increasingly form opinions from AI-generated answers rather than original sources, organisations need to understand how they are represented within those answers. Are the facts correct? Is important context missing? Is genuine expertise being recognised? And which sources are influencing the response?
What AI says about a business isn't determined solely by what that business publishes. Independent research, expert commentary and credible third-party sources all contribute. However, businesses cannot simply publish their preferred narrative and assume it will be repeated - they need to earn credibility through providing evidence that others can trust.
We’re already starting to see AI agents supporting with purchasing decisions, comparing potential partners and assessing credentials, and so for research businesses, demonstrable expertise, transparent methodologies and professional standards could increasingly influence whether they are considered in the first place.
Synthetic data needs human validation
There is also a clear parallel with one of the biggest developments in our own industry: synthetic data and AI-generated research participants. I've written previously about the opportunities these technologies offer, from exploring hypotheses to accelerating early-stage research - the potential is considerable. In fact, Qualtrics' 2026 Market Research Trends report found that 45% of researchers who had adopted synthetic data regarded it as their most reliable source, which is a striking finding that certainly deserves a degree of scrutiny.
Synthetic data can be useful without perfectly representing human behavior, but we must distinguish between a plausible response and an authentic one. AI models learn from existing information and reproduce patterns/ likely responses, but they cannot reliably anticipate every unexpected human reaction or emerging behavior.
Yet those surprises are often where the most valuable insights emerge. A participant challenges our assumptions, or a behavioural pattern that contradicts what consumers claim to believe. An unexpected finding changes the direction of a project.
These aren't inconvenient anomalies. They're often precisely why research is commissioned. Our industry therefore needs consistent standards for validating synthetic insights against real human evidence, alongside transparency about where AI-generated data has been used and its limitations.
Trust still depends on people
For all the technological change, trust remains fundamentally human. The 2026 Edelman Trust Barometer found that 78% of employees trust their own employer to do what is right, compared with 64% of the general population who trust business more broadly. It's a reminder that trust is often strongest in the organisations and relationships people know firsthand.
People value knowledgeable, accountable voices, whether it's independent researchers, industry experts, employees or customers who are speaking from experience. This is particularly relevant to insights, where professional reputation, methodological integrity and independent thinking have always mattered. We should encourage researchers to explain their work, contribute to wider conversations and challenge unsupported claims. We need to create cultures where people feel confident questioning AI-generated answers rather than accepting them because they sound convincing. This sense of accountability is also key in light of the new EU AI Act coming into force, where transparency is legally required for certain AI-generated content.
Where should our industry focus?
I believe there are four immediate priorities:
- Understand how AI represents your organisation. Test the questions clients and stakeholders might ask, examine the responses, and identify inaccuracies.
- Make evidence accessible. Support claims with original research, transparent methodologies and independent validation rather than simply producing more content.
- Set standards for AI-generated insight. Synthetic data and AI-supported analysis need appropriate validation, disclosure and human oversight.
- Invest in human intelligence. Critical thinking, behavioural understanding and professional judgement will become increasingly valuable as AI takes on more analytical work.
I've long advocated greater emphasis on formal education and professional development in market research, and that case is now stronger than ever.
Getting the story right
We cannot control every answer AI generates about us, nor should that be our objective, but what we can do is ensure the information available is accurate, credible and supported by evidence.
This is where the AI:HI balance really comes into play. Artificial intelligence can offer powerful new ways to process information, and human intelligence provides the curiosity, judgement and accountability needed to make sense of it.
Our profession's greatest contribution has never been simply collecting data - it's been about understanding people, challenging assumptions and helping organizations make better decisions, and in a world where AI can produce a convincing answer in seconds, that responsibility matters more than ever.
About the Author
Crispin Beale - Chief Executive, Insight250, Senior Strategic Advisor, mTab; Worldwide CEO, IDX
Crispin is a marketing, data, and customer experience expert. Crispin spent over a decade on the Executive Management Board of Chime Communications as CEO of leading brands such as Opinion Leader, Brand Democracy, Facts International, and Watermelon. Before this, Crispin held senior marketing and insight roles at BT, Royal Mail Group, and Dixons. Crispin originally qualified as a chartered accountant and moved into management consultancy with Coopers & Lybrand (PwC). Crispin has been a Fellow, Board Director (and Chairman) of the MRS for nearly 20 years and UK ESOMAR Representative for over 10 years. Crispin is currently a Senior Strategic Advisor at mTab as well as worldwide CEO at IDX.