Reckitt AI for revenue growth — enterprise case study

McKinsey’s case study on Reckitt — the global consumer health and hygiene company behind brands like Lysol, Durex, and Enfamil — provides one of the clearer examples of AI delivering measurable business results in a traditional industry.

What Reckitt did

The company deployed AI across three pillars of revenue growth management: pricing optimization, promotional effectiveness, and assortment planning. Rather than building AI in isolation from existing business processes, Reckitt embedded AI-driven insights directly into the workflows of commercial teams who make pricing and promotion decisions daily.

The approach centered on augmenting human decision-making rather than automating it. AI models analyzed historical pricing data, competitive dynamics, and consumer behavior to generate recommendations. Commercial teams reviewed these recommendations alongside their market knowledge, accepted or modified them, and executed through existing channels.

Why this matters for product managers

The Reckitt case illustrates a pattern increasingly common in enterprise AI: the most successful deployments are those that fit into existing workflows rather than requiring users to adopt new tools or processes. The AI operates behind the scenes, surfacing through recommendations and alerts within systems people already use.

For PMs, the case also demonstrates how to measure AI value. Reckitt tracked specific revenue metrics — margin improvement, promotional ROI, assortment optimization — that directly tied AI outputs to business outcomes. This measurement discipline is what separates AI projects that get continued investment from those that get cut after a pilot.

Limitations

McKinsey case studies are written with the consulting firm’s perspective and the client’s approval. The challenges, failed experiments, and organizational resistance that likely accompanied the transformation receive less attention than the outcomes.

Who should read this

PMs in CPG, retail, or any industry where AI augments commercial decision-making. Also valuable for PMs who need to build the business case for AI investment by showing concrete revenue impact from comparable organizations.