In the continuing All Things Insights TMRE 2026 Speaker Spotlight Series, we asked the market research community: If you were told you could add one role to the market research team, what would it be?
Special thanks to the TMRE speakers who participated in our survey. We would also like to thank all the speakers attending TMRE 2026 this year. See you in October!
In the Mix: Research Quality, AI Leads & Human Understanding
If you were told you could add one role to the market research team, what would it be? Why?
“A senior person to help synthesize the data in real time which can help lead teams to ask critical business questions. Centralizing this function gives firms the thought leadership their client wants.” —Jacob Beniflah, Executive Director, Center for Multicultural Science
“An entry-level researcher to help support the day-to-day would be a dream.” —Raina Rusnak, Head of Consumer Insights, StarKist
“I would add a Research Quality & AI Governance Lead. Not a ‘prompt engineer’ in the narrow sense, and not simply an AI tools person. The role should sit between methodology, analytics, privacy, and business application. Their job would be to make sure that AI-enabled research is useful, valid, transparent, and not overclaimed.
The reason comes directly from the ARF/MSI generative AI work: AI is becoming part of insight work through hypothesis generation, open-end analysis, synthetic personas, product recommendations, and strategic interpretation. But the same work shows that AI outputs can be shaped by prompt framing, persona assumptions, model context, and subtle social cues. The recommendation from that work is clear: treat AI outputs as hypotheses, not findings; validate personas; compare models; test prompts; trace evidence; and keep calibrated human oversight.
This role would also fit broader measurement priorities. Marketers face growing complexity around metric definitions, incrementality, disclosure, comparability, and validation. That is not just a retail media/commerce issue; it is a research operations issue. Someone needs to ask: Are we measuring what we think we are measuring? Can results be compared? Where is modeling replacing deterministic evidence? What should be disclosed?
So the role I would add is someone responsible for methodological discipline in an AI-enabled research environment. They would create standards for when AI can be used, how outputs are checked, how prompts are documented, how synthetic research is validated, how privacy and transparency are handled, and how findings are communicated without overstating certainty.” —Tracy Adams, Sr. Director, Research & Insights, The ARF (Advertising Research Foundation)
“I would add a Human Understanding Architect. This role would sit at the intersection of research, AI, culture and business decision-making. Its job would be to design how human understanding flows through the organization, from existing knowledge and fresh research to Digital Twins, creative development and everyday marketing decisions.
The role would help teams decide which questions can be answered through AI search, knowledge bases or Twin Communities, and when they need to return to real people, fresh research or deeper cultural exploration. That judgment is becoming increasingly important as organizations adopt more AI tools.
The Human Understanding Architect would also protect quality. Digital Twins are only as strong as the human and cultural understanding behind them. Someone needs to ensure they are grounded in real data, refreshed over time and used transparently. They would help teams distinguish between what is known, what is inferred and what still needs to be validated.
Most importantly, this person would focus on adoption. They would help embed Twin Communities into real workflows, train teams to ask better questions and connect insight to strategy, creativity, and execution.
Many organizations already have strong researchers and capable technologists. What they often lack is someone who can connect those capabilities into a continuous decision system and make sure AI brings teams closer to people rather than further away.” —Niels Neudecker, Managing Director, North America, Human8
“I would add a ‘Market Friction Anthropologist.’ While traditional research teams are packed with data scientists who excel at tracking what numbers are moving, they are often entirely disconnected from the messy, unquantifiable human environments where those numbers originate. A Market Friction Anthropologist fills this critical blind spot by embedding themselves directly into the native habitats of your end-users—physically shadowing them at their desks, observing their unprompted workarounds, and mapping the unspoken behavioral workarounds that metrics can’t capture.
This role is indispensable because it targets ‘Zero-Input Data’—the friction points a customer is so used to dealing with that they forget to mention them in a survey or focus group. For example, a data dashboard might show that a user takes ten minutes to complete a workflow, but only an anthropologist sitting beside them will notice they are maintaining a separate, messy paper cheat-sheet taped to their monitor just to navigate the software interface.
By capturing these invisible behavioral workarounds and translating them into high-density information for your product and marketing teams, this role bridges the massive gap between data and human behavior. They transform market research from a lagging, spreadsheet-driven reporting function into a proactive, ethnographic engine that identifies entirely new category opportunities and de-risks product design long before a single survey is ever scripted.” —Patrick Ward, Director, Institutional Marketing, Vanguard
“Project manager! Having someone plan, coordinate, and keep the work running so the researchers can focus on what they do best: plan, build, field, analyze, and synthesize research.” —Emily Neville, Director, CX Research, Rocket
“A code breaker. A cultural lead. Not a trend analyst. Not another quant researcher. Someone who can decode why things mean what they mean before consumers can articulate it themselves.
Most research teams are great at capturing what people say and do. Far fewer can interpret the symbolic layer underneath: the codes, archetypes, and cultural narratives that make a brand feel right or wrong to a consumer who couldn’t explain it in an exit survey.
It could be a ‘forcing’ function for the rest of the team. When you have someone fluent in cultural codes sitting in the room, your briefs get sharper, your hypotheses get braver, and your insights stop living only in the data.” —Sofia Vazquez-Barrios, Director of Consumer Insights, North America, Fine Fragrance Experience, DSM-Firmenich
“If I could add one role, it would be an evidence strategist. Someone whose primary responsibility isn’t running research, but evaluating the quality of evidence across all the inputs an organization uses to make decisions.
Today’s marketing decisions draw from surveys, behavioral data, platform metrics, synthetic data, AI-generated insights, and a growing number of modeled signals. The challenge is no longer collecting data. It’s understanding what should be trusted, how different sources fit together, and where the uncertainty lies.
That’s a role I think every research organization will need. Someone who can assess evidence quality, challenge assumptions, communicate uncertainty, and help leaders make decisions they can defend. As AI becomes more capable, I believe those judgment-oriented roles will become more valuable than purely technical ones. That’s a shift MSI has been emphasizing as the profession evolves.” —Keith Smith, Managing Director, Marketing Science Institute
TMRE Session Spotlight: The New Skill Set
TMRE 2026 will be held in Denver on October 5-7, and will highlight the panel, “Faster Data, Human Edge: The New Skill Set of the AI-Era Researcher,” presented by Angela Kesselman, Sr. Manager, Brand Research & Insights, Indeed.
AI has transformed what’s possible in brand and marketing research: more data, more voices, faster than ever. But speed and volume don’t automatically produce insight. At Indeed, a company whose entire mission is built on understanding how work and skills are evolving, we’ve learned something counterintuitive firsthand: the more AI accelerates the data-gathering process, the more irreplaceable human judgment becomes at the interpretation stage. This isn’t a talk about whether AI will replace the insights professional; it’s about what the insights professional must become now that AI is in the room.
Click here for more TMRE 2026 registration information and the show agenda.
Video: “How Research Leaders Start Over with Stan Sthanunathan,” courtesy of Market Research Institute International.
