Is Your Insights Team Ready for Agentic Marketing?

"Insights experts will play a crucial role in the agentic future but only if your technology and processes are right," says Peter Aschmoneit, CEO & Co-Founder at quantilope

I spent years as a Marketing Director believing that great marketing was a craft. I learned all the principles, combining data with creativity. Over time, I built the knowledge and intuition that helped me make decisions that ensured brands grew rather than stalled.

That experience shaped how I think about marketing. It’s the reason I can clearly see that what's coming next is not an incremental change, it's a full reassembly of how marketing work gets done.

The process is already underway and AI agents are already here. They are not in every marketing department yet but they are capable of doing great marketing work and helping brands grow very effectively.

For those still getting familiar with them, let’s be clear: an agent is not a chatbot. It's not a dashboard. It's an AI-powered system that works towards a defined goal. Just like a person does but without needing a human to initiate every step. It reasons. It plans. It takes decisions independently, whatever the complexity.

Here's a concrete picture of what that looks like in practice.

Meet a modern Brand Manager. Could be in CPG, pharma, retail, the category doesn't matter. The Brand Manager now has a marketing agent as a partner. That agent is scanning market data, identifying a trend being picked up by a smaller competitor, drafting a concept, running a P&L, checking how it fits the marketing calendar, and benchmarking the whole thing against brand guidelines. All on its own. Then it hands a fully developed brief to Research & Development. The Brand Manager didn't ask it to do any of that. It just did it.

If that sounds far-fetched. Consider what Roy Amara from the Stanford Research Institute already said in 1978: “We tend to overestimate the effect of a technology in the short run and underestimate it in the long run.”

The short-term noise around agents has been loud. The long-term shift will be louder but part of the problem at many brands is that 70% of marketers have been prioritizing Generative AI for back-end efficiencies (like automation and cost-saving) rather than effectiveness (powering growth), according to research from the World Federation of Advertisers (WFA).

Nevertheless, there are brands showing ambition in this area. Beauty giant L’Oréal is applying AI across its direct-to-consumer (DTC) channels and loyalty programs, using agents to analyse purchase patterns to trigger email campaigns with personalized recommendations and replenishment reminders at the exact moment they expect that a consumer is likely to need supplies.

CPG giant Pepsi, for example, is re-engineering its business to become "agentic AI-first" by the end of this year (2026). The ambition is to connect its entire supply chain with sales and marketing via autonomous AI agents that can automate, personalize and optimize commercial operations at scale.

There Are Things Agents Can’t Do

Agents are fast, systematic, and tireless. But they have no intuition. They have no lived experience. They cannot feel what a consumer feels or understand why a cultural moment changes everything overnight. In the end, they are machines, sophisticated ones, but machines nevertheless.

That's not a limitation to dismiss. It's the central strategic question for every insights team. If agents are making decisions without being fed the right consumer understanding, they will optimize for the wrong things. They'll find patterns in data, but patterns without meaning. Correlations without empathy. Briefs without humanity. The agent doesn't know what people feel. A big part of your AI job description is to make sure it does.

This isn't about whether AI will replace researchers. That's the wrong question. The right question is: will your insights function be fast enough and connected enough to actually inform the decisions agents are making?

Three things need to change:

First, the technology stack has to work. Agents make decisions at machine speed. If your insights aren't structured and accessible in a way that agents can actually consume, you're not in the loop. This is a big obstacle to overcome, reflected in McKinsey research that shows only 27% of marketing leaders feel their organizations are well-prepared for AI integration. The barrier for insights is to make sure that great research doesn’t live in a PowerPoint presentation but is readable by an agent.

Second, the speed of consumer understanding has to match the speed of agent work. Insights delivered two weeks after a decision was made aren't insights, they're history. The challenge isn't just producing consumer understanding. It's producing it at the pace these systems move. The future is constantly updated data that reflects what’s happening now. Research by the WFA reveals that 94% of insights leaders agree that AI enables faster, real-time insights and quicker decision-making.

Third, someone has to own quality control. Statistics can support almost any conclusion if you look for long enough. Qualitative data can confirm any hypothesis if you frame it right. Without human oversight grounded in evidence-based brand growth principles, agents will make decisions that feel data-driven but aren't actually sound. That role belongs to insights teams – or it belongs to no one.

Your Role Needs to Be Redesigned

Your title may not change and your organizational chart might look exactly the same from the outside. But the work underneath is being rebuilt for the AI age.

Executional tasks will increasingly move to AI. That's already happening. What moves in the opposite direction – what becomes more important, not less – is your leadership, your judgment. The ability to teach an agent what it needs to know to make a decision that actually drives brand growth.

The direction of travel is much more leadership and much less execution.

The bottom line is that every decision, whether made by a human or an agent, must be backed by consumer science. Insights teams need to make the shift from service department to digital growth engine on the back of faster consumer understanding, technology that feeds the systems your organization is building, and the quality controls that keep decision-making human.

Success means no gut feeling and no pattern-matching without empathy.

The agent is already in the room. The question every Insights leader should ask is: who's teaching it.