Last week I joined an interactive panel at the 16th Global Commercial & Sales Force Excellence Summit in Berlin, chaired by Stefan Turnwald, with peers from pharma and AI. The theme was AI and new trends in commercial models. One can expect a panel like this to be about tools, but it became a conversation about leadership, ownership and how we measure success.

My main message was simple: most of us use AI to run today’s model faster. To change the model, we have to change how we decide, who owns what, and how we measure.

The questions we discussed

Is AI changing the commercial model, or just making it more efficient?
Mostly efficiency, for now. There is a simple test: if you removed AI tomorrow, would your org chart, your KPIs and your customer journey look the same? If the answer is yes, the model hasn’t changed. We have put a faster engine into the same car.

Where will the biggest shift happen?
First in sales roles and channel strategy, as preparation and planning move to AI and decisions about who to see, and when, move from people to systems. Then in customer engagement, as doctors and patients increasingly ask AI before they ask us. Slowest, but biggest, in revenue models, where tendering and pricing are the early signals.

How do we turn AI investment into real value?
Start with the decision you want to improve, then choose the tool. Measure in three layers: are people using it, did the way we work change, and did the business or the patient benefit? Most companies stop at the first layer. And saved time is not value until we know where the freed time went.

What should we stop, start and rethink?
Stop counting activity as success, and stop running pilots that never scale. Start deciding clearly what an agent decides and what a human approves, and build governance in from day one. Rethink roles and career paths, and the idea that one design works in every market.

Where the real work is

McKinsey’s research this summer gives a useful frame. In their survey, 70% of employees said they feel ready for AI, but only 27% of leaders believe their organisation is. Organisational readiness explained almost twice as much of the value gap as personal readiness. Based on my experience and what I have seen, that matches reality: the bottleneck is rarely the tool, and rarely the people. It is leadership and collaboration across functions.

Thank you to KP-Morgan Group for hosting, to Stefan for chairing, and to my fellow panelists and everyone in the room for a great discussion.

Source: McKinsey Quarterly, “From adoption to impact: Three horizons of AI transformation”, July 2026.