Eli Lilly
Delivered AI Foundation for Eli Lilly. Quantitative effect metrics have not been collected, and we do not infer them here.
Client
Eli Lilly is a multinational pharmaceutical company, and a client of the AI business transformation line — the relevant services being AI advisory and selection, and agent delivery.
The problem
For large pharmaceutical companies the bottleneck in AI adoption is rarely the model; it is the foundations. Data sits in separate business systems, compliance requirements are strict, and departments running independent pilots duplicate each other. A reusable base layer has to exist before individual applications are worth rolling out.
What we did
Delivered AI Foundation, a base capability layer for enterprise AI.
Limits of this case
- Foundation projects do not produce business metrics directly. Their value shows up in the build speed and reuse rate of the applications that follow, so judging them on short-term ROI produces misleading conclusions.
- Pharmaceutical compliance constraints — data privacy, content review, traceability — are considerably tighter than in most industries, and the design does not transfer directly to other sectors.
Service behind it
AI advisory and technology selection · All client cases