AI Use Cases in CPG: Best Practices for Measurable Value
Experienced CPG leaders rarely struggle to generate an AI backlog. The harder task is converting promising models into repeatable decisions across categories, markets, customers, and plants. AI Use Cases in CPG frequently stall between a successful pilot and scaled adoption because the model was built apart from the commercial or supply workflow it was meant to improve. Other initiatives reach production but generate little value because planners ignore the recommendation, customer teams cannot explain it, or finance cannot isolate the benefit from distribution, pricing, and market movement. The most effective portfolios of AI Use Cases in CPG are managed as changes to decision systems, not a collection of technical assets. That distinction affects sponsorship, data design, validation, controls, and value tracking. A demand model belongs inside demand-plan reconciliation. A promotion model belongs inside TPM and TPO. A formulation assistant belongs inside the governed stage-gate proce...