Category Management Can Benefit From ‘Collaborative AI’

When new technologies like agentic artificial intelligence emerge, retailers and brands look inward first: How can AI agents improve my demand forecasting? How can it automate marketing copy?

However, there’s another level of agentic AI to think about — consumer goods brands and retailers supporting one another through shared intelligence (i.e., collaborative AI).

Of course, most companies like to keep things close to the vest, especially data and strategy, but agentic AI can be a collaboration tool when managed through proper governance. Brands and retailers can bring two insights-driven, agentic-fueled businesses to the table that support each other’s goals.

Retailers Need Support Balancing Assortments

To start from the retailer’s perspective, a common challenge they have is managing large assortments. There’s a constant push and pull between prioritizing high-margin SKUs on one end while protecting category volume and product diversity on the other.

Traditional methods of quarterly reviews and gut-feel category changes aren’t the most effective ways to enhance assortments and planograms. AI agents can provide category managers real-time insights on store-level decisions. An agent can monitor performance signals across the assortment, pricing changes and promotional activity, and it can recommend action or even take action when guided by the manager.

With visible, live category data available for category managers to work from, AI agents can quickly identify which SKUs are over-represented relative to margin targets and surface tradeoffs in changes. Retailers benefit by working faster and more precisely.

But there are still a lot of decisions to be made. CPGs that have their own agentic AI intelligence layers looking at product performance by stores, regions, consumer demographics and more can come to a retailer and help them get an even sharper picture. Retailers, in turn, can go to a brand partner they know has AI intelligence to confirm insights or have agents directly collaborate on new product or promotional opportunities.

Brands Can Be Proactive

For CPGs, rather than be reactive to a retailer’s needs, agentic AI allows for them to read market signals and be more proactive and collaborative.

For example, a snack brand selling across grocery, mass and convenience stores doesn’t face a single assortment challenge; it faces dozens of them, differentiated by banner, store format and local market needs. A brand-side assortment intelligence agent can analyze what each retail partner is trying to accomplish and suggest specific recommendations. The brand can highlight flavor SKUs being overdistributed against local demand for a specific banner or identify pack sizes that better meet specific consumer profiles that a retailer wants to reach.

CPGs aren’t using agents to circumvent retailer decision-making; they're using them to add more intelligence to the conversation. The goal is for brands and retailers to collaborate and get more precise, real-time insights so they can take action more effectively.

Governance is the Prerequisite to Collaboration

Brands and retailers can’t effectively collaborate if they don’t have a data and agent foundation they can trust. Before a brand targets a specific retailer with agentic intelligence, the underlying data must be governed. Product attributes need to be accurate and consistent. Promotional terms should be clean. Historical performance must be mapped correctly to the right accounts and channels.

Agentic AI accentuates whatever data it works from. A weak foundation can create mistakes and shatter a relationship between a brand and retailer.

CPGs and retailers have always needed one another. Agentic intelligence, however, can build a stronger partnership, enabling the two parties to operate continuously, across more variables and at a level of specificity that wasn’t thinkable before. Agentic AI supports teams to make quicker decisions in dynamic, collaborative environments, enhancing localization and developing more mutually productive trading relationships.

Lori Schafer is CEO of Digital Wave Technology, an AI-native enterprise platform company helping retailers, consumer brands, and health and wellness organizations operationalize agentic AI at scale.