Many pharma companies chase advanced AI without solving the foundational challenge of data integration. With only 10% of firms having unified data, true personalization is impossible until a central data platform is established to break down the typical 100+ data silos.

Companies run numerous disconnected AI pilots in R&D, commercial, and other silos, each with its own metrics. This fragmented approach prevents enterprise-wide impact and disconnects AI investment from C-suite goals like share price or revenue growth. The core problem is strategic, not technical.

Many firms are stuck in "pilot purgatory," launching numerous small, siloed AI tests. While individually successful, these experiments fail to integrate into the broader business system, creating an illusion of progress without delivering strategic, enterprise-level value.

Many pharma companies have breakthrough AI results in isolated functions, or "pockets of excellence." However, the ultimate competitive advantage will go to the company that first connects these disparate successes into a single, integrated, enterprise-wide AI capability, thereby creating compounded value across the organization.

Large pharma companies are discovering that implementing AI to solve one part of the drug development workflow, like target discovery, creates new bottlenecks downstream. The subsequent, non-optimized stages become overwhelmed, highlighting the need for a holistic, fully choreographed approach to AI adoption across the entire R&D pipeline.

Many pharma companies allow various departments to run numerous, disconnected AI pilots without a central strategy. This lack of strategic alignment means most pilots fail to move beyond the proof-of-concept stage, with 85% yielding no measurable return on investment.

Rather than allowing siloed AI experiments, Boehringer Ingelheim uses a centralized "AI innovation team." This overarching function supports the entire enterprise, pilots ideas to "fail fast or scale up," ensures compliance, and builds economies of scale.

Long-term competitive advantage will belong not to firms with the best algorithms, but to those that build the most intelligent organizations *around* AI. The key is developing the ability to absorb, direct, and compound AI's power in service of coherent strategic goals.

Pharma companies engaging in 'pilotitis'—running random, unscalable AI projects—are destined to fall behind. Sustainable competitive advantage comes from integrating AI across the entire value chain and connecting it to core business outcomes, not from isolated experiments.