Artificial intelligence in Life Sciences commercial teams

In recent searches for commercial and marketing roles in pharmaceuticals, medical devices and consumer health, one question keeps coming up in profile-definition meetings: which part of this job will a language model do in two years. The honest answer is that a part will, and that part is fairly clear. What is not clear is what profile is needed to lead the rest.

What changes first in commercial work

Four fronts concentrate the change already under way in the region.

• Promotional and medical content: drafts of materials, adaptation by segment and by country, and preparation of medical-legal review. The team moves from writing to reviewing and approving.
• Omnichannel orchestration: which message each physician receives, through which channel and when, with rules a system proposes and a person decides.
• Field force: assistants that prepare the visit, summarise the account and record the interaction, so the representative spends the time on the conversation.
• Market intelligence: reading prescriptions, tenders and coverage at a speed that used to require a team of analysts.

What does not change

The relationship with the physician, the pharmacy, the payer and the hospital account remains people's work, and in Life Sciences it is regulated. Promotional compliance, pharmacovigilance and the traceability of every claim do not admit a system that is "roughly" right. That is why the profiles adding most value today are not those who know about artificial intelligence, but those who can decide with it without losing regulatory judgement.

What to look for in the next profile

When we define a product manager, commercial manager or marketing director role for this sector, we add four capabilities to the success profile that were not there before.

• Data fluency: reading a dashboard, questioning a model and knowing when an automated recommendation makes no clinical or commercial sense.
• Operating assistants: having used AI tools in real work, with concrete examples of what they delegated and what they reviewed.
• Applied regulatory judgement: understanding which content can be generated, what must go through review and how to document it.
• Team design: deciding which functions are automated, which are outsourced and which are kept, without losing the people who sustain the relationship.

How we assess it

In the competency interview we ask for real cases: a campaign or a launch where the person used an AI system, what they decided, what they corrected and what would have gone wrong without their review. In the simulation we present a launch scenario with automatically generated material and deliberate errors, to observe judgement before speed. And in the references we ask one thing: whether that person's team adopted new tools without losing compliance discipline.

None of this requires a technology profile. It requires a commercial leader who understands that part of their function has become the supervision of systems, and who remains accountable for what those systems say.