What Esomar Congress 2026 Told Us About the Future of Research

Rep Data Team · September 10, 2026 · 4 min read

At Esomar Congress 2026, conversations about the future of research covered everything from data quality and fraud prevention to AI and neuroscience. While the topics varied, many reflected how quickly the research process is changing and what that means for the people responsible for delivering reliable insights.

Researchers are working faster, using more technology and navigating increasingly complex data environments, making it even more important to understand where data comes from, how its quality is assessed and where technology can improve the research process without losing the judgment and accountability researchers bring to the work.

Three themes stood out to us.

1. As research gets faster and more automated, quality becomes more, not less, important

In "Do Clients See Data Quality The Same Way We Do?", Ray Poynter of Esomar

PSC, Anita Watkins of Insights Association, Vinay Ahuja of P&G and Jennifer Hubber of Campari shared findings from the Global Data Quality (GDQ) initiative showing how responsibility for research quality is increasingly shared across the research ecosystem.

Among the clients surveyed, 80% conduct research monthly and 84% field at least some surveys in-house. Only 9 of 173 respondents said they rely fully on providers for quality, while approximately 76% view quality as either the buyer’s responsibility or something buyers and suppliers share.

That shared responsibility extends to how quality is assessed. A separate session on fraud prevention discussed using different approaches depending on the level of risk, with passive and pre-screening signals identifying more obvious fraud and more intensive measures such as ID validation reserved for respondents who warrant additional scrutiny.

Research Rep Data presented at Congress reinforced the value of using multiple approaches. Across 11,778 respondents and eight quality signals, the different checks rarely flagged the same people, with each identifying potential quality issues that others missed.

As research becomes faster and more complex, protecting quality requires multiple layers of defense and shared responsibility throughout the research process.

2. Trust is increasingly about transparency, not just detection

The GDQ findings also revealed a significant confidence gap. Among respondents, 45% said they had stopped using a supplier because of poor quality, yet only 33% were confident that poor-quality respondents are removed before data is delivered.

Researchers want greater visibility into where sample comes from, how respondents are screened and cleaned and which methods are being used to detect fraud. The work underway through the GDQ initiative and ISO standards can help establish clearer and more consistent expectations around those practices.

For research suppliers, doing the work behind the scenes is no longer enough. Buyers taking greater responsibility for quality need the information to understand how their data was sourced, evaluated and protected.

3. AI is changing the research workflow, but human judgment remains central

AI was a major part of the conversation at Congress, including Moran Cerf’s keynote, "Three Ideas from Neuroscience That Will Change the Next Decade." Cerf noted that while AI tools have become mainstream, fully autonomous agents have not. People still want control, even as AI takes on more pieces of creative and analytical work.

For researchers, that could mean spending less time executing individual tasks and more time directing the process, evaluating outputs and deciding what the findings mean. Cerf also raised a more complicated issue for the industry, showing how the act of asking people to recall and explain their decisions can itself influence memory and preferences.

As technology takes on a larger role in research, researchers will need to make careful decisions about what to automate, how to interpret what technology produces and how the research process itself may affect the people being studied.

What does this mean for the future of research?

The changes discussed at Congress point toward research that will be faster and more automated, but also place greater demands on the people and companies responsible for it. Researchers will need to know where their data comes from, understand how its quality is being protected and make informed decisions about where technology belongs in the process.

The bar for research is getting higher, and speed and automation are only part of it. The future will also depend on transparency, quality and the human judgment needed to make the right decisions throughout the research process.