Merck KGaA's AI Chief: Models Aren't the Advantage—Context and Trust Are

Merck KGaA's approach to A.I. reflects a maturing enterprise perspective that moves beyond the model-centric thinking of the early generative A.I. era. When ChatGPT sparked a global corporate rush in late 2022, Mehanna had already spent two years rebuilding the company's data and analytics backbone; his role was elevated to chief data and A.I. officer roughly eight months into the GPT era. That grounding in data infrastructure gave him a realistic view of what actually drives value at scale. His "pyramid" model—everyday tools at the base, embedded workflows in the middle, and product A.I. at the top—reflects a deliberate, phased approach rather than a reactive scramble. The shift from MyGPT to partnering with LangDock (a startup with $50,000 in annual recurring revenue at the time) underscores a calculated trade-off: rather than lock the company into a single vendor, Merck KGaA chose speed, sovereignty, and optionality. That choice is particularly significant for a 350-year-old company operating under strict European regulatory frameworks and strong labor-relations customs.

Mehanna's governance and ethics strategy further illustrates the gap between A.I. hype and enterprise reality. His comparison of guardrails to high-performance car brakes—essential to enable speed, not to slow it—reframes governance as enabler rather than brake. The Digital Ethics Advisory Panel's five-principle framework (autonomy, beneficence, non-maleficence, justice, transparency) and its emphasis on early risk identification before launch rather than post-hoc approval reflects hard-won experience managing large organizations through technological transitions. His earlier role at Mercedes-Benz (five years as chief data officer) clearly informed this philosophy. For Merck KGaA's 62,000 employees, the privacy protection (aggregate-level analysis only, no individual monitoring of the 12 million internally-generated prompts) demonstrates how to scale A.I. adoption while meeting both regulatory requirements and workforce expectations.