Laying the Groundwork for AI in Markets Research: Postcard from Unbundling Uncovered

Last week, I was thrilled to attend the Unbundling Uncovered Conference hosted by Substantive Research in New York City. The panelists were brilliant, offering an exciting strategic vision centered on AI, automation, and new approaches to delivering research. Their insights made the direction of travel unmistakably clear, and I’m grateful for the opportunity to learn from their perspectives.

In parallel, conversations throughout the conference revealed a common theme: an undercurrent of skepticism among those working in research day to day. Many firms are contending with legacy systems, fragmented data, strict governance, limited budgets, and competing internal priorities. Layered on top are the internal sensitivities that come with introducing technologies that may reshape long-standing roles and workflows. Combined, these factors make even low-tech improvements difficult to implement.

AI and predictive automation are undoubtedly the future—but the road to get there is long. And, in many cases, the foundational infrastructure simply isn’t in place.

It is important to recognize that if we expect advanced automation and predictive analytics to deliver real results, we must first invest in the laying the groundwork for AI in markets research :

• High-quality, accessible data assets

• End-to-end capture of activity and engagement

• Integrated data ecosystems consolidating disparate sources

• Intelligent metadata frameworks for effective classification

• Sophisticated client segmentation aligned with commercial goals

• Decision-making tools that empower teams, even if not yet AI-powered

  
  

These may not be the flashiest initiatives, but they are the ones that enable the future and drive measurable gains in market and wallet share along the way.

There is clear alignment on where the industry should be headed. Now the real question is how we build the path there, brick by brick.

KTB