How Henkel Embeds AI Strategy Across R&D, Supply Chain, and Finance

What does it look like when a 150-year-old industrial giant actually builds AI into its bones — not as a side project, but as a core operating system? That's exactly what Henkel is doing, and the results offer a compelling blueprint for any business serious about operational AI.

Key Takeaways

• AI is woven into the value chain: Henkel applies AI across R&D (accelerating formulation and ingredient testing), supply chain (improving demand forecasting and reducing volatility), and finance (enabling faster, smarter decision-making).
• Scalable data architecture is the foundation: Rather than launching AI experiments in isolation, Henkel built a unified data architecture that allows AI to scale across business functions with operational consistency.
• Business complexity drives AI adoption: Serving both B2B and B2C markets across global supply chains, Henkel uses AI to manage the inherent complexity of a highly diversified portfolio — not just for efficiency, but for resilience.

Henkel's model challenges the common assumption that legacy companies are slow to adopt AI. When AI strategy is integrated at the leadership level and supported by the right data infrastructure, transformation is not only possible — it becomes a competitive necessity.

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