Governing the AI Leap in Commercial Pharma

Is pharma finally getting AI governance right?

After years of cautious experimentation, pharmaceutical companies are finding their rhythm with commercial AI—and the results are impressive.

Our latest research shows leading pharma firms are moving from pilots to systematic AI adoption in sales, marketing, and market access—driven by embedded governance. Novartis, for example, incorporates human oversight, expert validation, ongoing feedback loops, and dynamic model updates to ensure quality, accountability, and accuracy.

Here's what's working:

📈 Examples of ROI (or not)

• Significant increases in sales and marketing efficiency, especially via NLP-powered engagement tool

• AI tools are helping pharma companies improve gross-to-net forecasting through advanced data analytics

• Purpose-built tools are gaining traction faster than general solutions at the moment (one major pharma just canceled its Microsoft Copilot pilot due to poor ROI)

  
  

🏛️ Maturing Governance

• Formal AI governance frameworks with human oversight and transparency protocols established at firms like Merck

• Sales ops and medical affairs teams implementing localized governance protocols

• Vendor scorecards prioritizing explainability and commercial KPIs over flashy features

  
  

⚖️ Regulatory Reality

• FDA's 2025 guidance introduces 7-step credibility framework for commercial AI

• EMA mandating transparency reports for promotional tools

• EU AI Act classifies HCP-targeting AI as "high-risk"—human oversight required

  
  

The pattern is emerging: Companies are limiting the use of general-purpose AI tools (ChatGPT, Copilot) due to compliance risks, while embracing pharma-specific solutions that emphasize security, explainability, and measurable business impact.

The pharmas that are more successful in implementing commercial AI are governing this as a business capability now, and have grown beyond running a series of experiments. They're building internal expertise and creating feedback loops that continuously improve their processes.

What governance challenges is your organization facing with AI adoption? Are you seeing similar patterns in your industry?