Why Simulation, not Synthetic, Will Define What's Next
First Written for the MRS Industry Report 2026
Twelve months ago, I wrote about the emerging landscape of AI for better insights – not just AI for greater efficiency. Since then, the direction of travel has become unmistakable. New models are emerging that don’t just streamline research, but deliver genuinely better insight. Many fall under “synthetic data” or “synthetic insights” – phrases I dislike, because to me they imply poor quality. And the current synthetic landscape comprises propositions which range from the dubious to the exceptional.
Crucially, these new approaches are attracting new business start-ups. And those new entrants are, in turn, attracting private equity money, backing AI-led models and accelerating the rate of change across the industry.
This influx of new methods, new players and new investment will undoubtedly challenge the established order. But it can also be argued to be a breath of fresh air – a new, if disruptive, energy for our industry.
The Industry’s Killer Opportunity
AI is only ever as good as the data it is trained on. Rubbish in, but still (dangerously compelling) rubbish out. Our industry, for more than 70 years, has been the established purveyor of human truth. That gives us something no other sector can claim: the ability to provide the grounding that high quality AI depends upon. This is a unique industry advantage, and we are all sitting on top of a killer opportunity!
But staying on that word “killer”, I believe there will be only three types of businesses in the next few years ahead: the failures, the survivors and the thrivers. We each know which bucket we want to be in. Thriving requires acting now, with urgency, to make AI our ally rather than our adversary.
Synthetic Data Becomes Part of the Landscape
As AI moves beyond efficiency, synthetic approaches have become far more visible across the insights landscape. We’re seeing AI moderated qual open up new ways to gather depth at scale. Alongside this, adoption of synthetic panels, synthetic datasets, digital twins and AI personas is accelerating – useful when traditional fieldwork is too slow, impractical or places too much burden on respondents.
Because respondent burden is part of the problem. Sample quality remains one of the industry’s biggest challenges. People drop out not because they’re “bad respondents,” but because many surveys – even methodologically sound ones – are too onerous. Synthetic solutions help ease that pressure: they reduce the need to put real humans through bad experiences to run rigorous research. It won’t solve the crisis alone, but it helps.
All of this sits within a landscape that is still the Wild West. Quality varies wildly. These methods expand the ways we can model people and behaviour, but none of them are magic. Many are difficult to audit and often amplify the weaknesses of the data they rely on.
This is where our industry remains essential. We bring the cultural understanding, nuance and judgement needed to ensure these systems reflect people rather than approximate them.
Why Synthetic Personas Stand Out
Among the growing synthetic approaches, AI personas and simulations have emerged, in my view, as the most promising. Not generic, assumption led profiles, but “silk end” models built from real human data, cultural understanding and curated contextual insight – designed to help organisations explore “what if?” scenarios with confidence.
The important point is not the terminology. It’s the craft, and the graft.
Intelligent personas and simulations are not synthetic respondents rebadged; they are validated, auditable models anchored in human truth. When built well, they support a wide range of insight needs, from audience understanding to innovation workflows. Enterprise-grade simulations cannot be bought off the shelf; the devil is in the detail – in the quality of the data and the specialist craft required to build, validate and continually refine them.
Verve Vero’s Big Bet
As agencies, we must choose our bets if we want to thrive. At Verve, we are being bold – for better or worse – and going all in on Intelligent Personas and Simulations. I see them becoming as integral to the new AI-powered insights model as surveys were to the old.
We envision a future where specialists like Verve Vero build and maintain proprietary simulations, used directly with clients as well as in partnership with agencies. In the partner model, agencies bring their consultancy skills to create game-changing insight with clients, while the AI build, execution and investment risk sits with the simulation specialist.
A good example of this is our partnership with CACI to build simulations for the 12 Fresco and 22 Acorn segments – a true collaboration where CACI bring industry currency data and we enrich and animate it. This is a complementary model, not a competitive one, and a sign of the new shape of collaboration our industry needs.
Where We Go From Here
AI hasn’t removed the need to understand people; it has made that need sharper and more urgent. It has raised the bar for what good now looks like. The rise of simulations makes the quality of the human data that fuels them more important, with deep qual and robust quant becoming critical foundations rather than optional inputs. We are the custodians of the human truth which AI depends on, and with that comes responsibility - and opportunity.
Last year was about recognising that. This year must be about acting on it. The debate is over. The task now is to build an insight ecosystem that is faster, braver and more reflective of real people - powered by AI, anchored in reality, and driven by us all as leaders of our new industry.