It's been a few weeks since my recap of the banking panel at this year's CRIC Conference, but another session that day is still on my mind, and its lessons remain too relevant to leave out. At "Adapting to Disruption: A Client Dialogue," senior customer insight and marketing leaders from TD Bank Group, Samsung Electronics Canada, Keurig Dr Pepper Canada, and Diageo Canada came together to talk through how their organizations are adapting to AI in market research.
Banking, consumer electronics, packaged goods, and beverage alcohol don't share a customer, a category, or a regulatory environment. But these four organizations do share a set of expectations for the market research agencies and suppliers they work with, and AI is rewriting those expectations faster than anything else. As client-side teams get more comfortable using AI themselves, the bar for what an outside partner needs to bring keeps rising.
At Phase 5, we do this kind of work with our own clients every day, so a lot of what came up on this panel matched conversations we're already having. Here's what stood out to me, and what it means for how research partners should be using AI.
The Takeaway in Short:
Agencies become strategic partners, not vendors, by using AI in market research to handle busywork, connecting data instead of just delivering it, knowing which questions still need a human answer, and letting clients measure their work by decisions changed rather than reports delivered. That's what four client-side leaders said they want from research partners at the CRIC Conference 2026, and AI alone doesn't earn a market research agency that seat.Client-side teams are moving away from isolated studies and disconnected data sources, combining behavioral, transactional, and CRM data with brand tracking and traditional research into one view of the customer.
That approach mirrors how people actually behave, as nobody makes a decision through one channel or one data point. Rather, their choices get shaped by needs, habits, and emotions.
For agencies, this changes what the job actually is. The old model was to collect information and hand it back. The panelists described wanting earlier signals instead, spotting risks and opportunities before a tracker shows a decline or a segmentation study finally wraps months later.
A market research agency that only delivers a study now competes with client teams who can pull that same signal internally. But an agency that helps connect a study to the behavioral, transactional, and social data a client already has is doing something a client’s customer insights team usually can't do on its own.
AI lets agencies spend less time on tactical work and more time on strategy, which is where the real value to clients sits. The panelists at this session talked about using AI to summarize data, code open-ended responses, spot early trends, and make existing t research easier to search and query. This builds on a larger industry conversation around AI in market research, where speed matters but experience and judgment still carry the work.
Speed alone doesn't make an agency more valuable to a client. What makes the difference is what a market research agency does with the time AI buys back: digging into what the data actually means and showing up with a point of view, not just a faster version of the same report.
Governance is where agencies can go beyond policy compliance to build real trust with clients. One of the strongest themes at the CRIC Conference was that client-side teams need clear rules for when AI is the right tool in market research and when it isn't, along with a process for validating what it produces.
A partner who can explain exactly how an AI-assisted finding was generated and where confidence is lower builds a kind of trust a black-box deliverable never will. The panel reinforced a theme we've seen across the industry: AI plus human judgment is still key to stronger customer insight work. Regulated and sensitive categories raise the stakes on this the most. In financial services, alcoholic beverages, and consumer technology, a research decision can carry real reputational risk.
Panelists also drew a clear line between using AI or synthetic data for lower-risk exploration and using it as the basis for a major investment decision. That discussion also connects to Phase 5's recent thinking on synthetic personas, especially the need to know what to trust and what to avoid.
Market research agencies that treat governance, and the limits of synthetic data, as part of the deliverable rather than an afterthought are doing the work clients are actually asking for.
Knowing which tool fits a decision is its own kind of expertise, and it's what separates a strategic agency from a vendor. Sometimes that means a survey instead of a summarization tool, and other times it means a deep study instead of a fast signal.
Behavioral and transactional data can show what people did, but it can't always explain why a behavior is growing, what need it meets, or what emotion drives a choice. Those questions still need a human conversation, and, frankly, market research agencies that recognize the difference are more valuable than ones that don't.
Panelists at this session pointed to motivations, cultural context, and category meaning as places where primary research keeps its edge over AI-generated signals. Being able to say "this customer insight needs a conversation, not a query" is what earns an agency a seat at the strategy table.
Client-side leaders want market research agencies to act as thought partners, not tool vendors. Panelists were direct: they don't want partners who lead with a tool, a platform, or a predefined methodology. They want partners who understand the business context first, ask better questions, and challenge assumptions rather than just execute a brief.
That standard extends to how success gets measured. Customer insights teams historically ran a study and handed back findings; panelists described that model shifting toward advising, judged less by the number of reports produced and more by whether the work shaped a decision, changed a strategy, or helped the business spot a risk or opportunity sooner. A report that sits unread isn't a success just because it shipped on time.
AI and new data systems in market research are pushing this further, toward longer-term collaboration built around capability building and decision support rather than one-off projects. For agencies willing to invest there, it's a real opportunity to become harder to replace.
Four client-side leaders from completely different categories at this CRIC Conference 2026 session described the same shift in what they expect from outside partners, and that consistency, not any single AI use case, is what made the panel valuable.
Every agency has access to AI now, so it’s no longer a differentiator in market research. What separates a strategic partner from a service provider today is what a market research agency does with the time AI gives back, and the judgment it applies to what AI can't answer.
That's the kind of partner we aim to be for our own clients. Contact us to talk about what that could look like for your organization.
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