We keep saying AI will change everything in pharma.
Mostly, we talk about speed, efficiency, and better decisions.
But that is only part of the story.
In this video, Manuel Mitola, faculty member of CELforPharma's The AI for Pharma Marketing Course, explains why the role of pharma professionals is shifting from problem solving to problem explaining, and why this is key to unlocking AI’s full value.
🔍 What is the real impact of AI in pharma?
AI is often positioned as a tool that solves complex problems faster.
In reality, its effectiveness depends on something else: how clearly humans can define and communicate those problems.
This marks a fundamental shift in how work gets done in pharma organisations.
đź’ˇ From problem solving to problem explaining
Traditionally, professionals in pharma were valued for their ability to solve problems directly.
With AI, the value is shifting toward:
- Structuring complex questions
- Providing the right scientific and business context
- Translating challenges into clear, actionable prompts
The better the explanation, the more powerful the AI output.
🎯 Why this matters for pharma professionals
In a regulated, data-driven environment like pharma, precision and clarity are critical.
AI amplifies this reality.
Professionals who can clearly articulate problems will:
- Generate more accurate AI-driven insights
- Reduce errors and ambiguity
- Accelerate decision-making processes
This is not just a technical skill. It is a strategic capability.
⚙️ Practical takeaway: How to use AI more effectively
Before using any AI tool, take a step back and refine your input.
Ask yourself:
- Is the problem clearly defined?
- Have I included enough context?
- Would another expert understand this request immediately?
Improving how you explain the problem will directly improve the quality of the results.
Continue your learning from Manuel
If you’d like to learn more from Manuel, CELforPharma also offers a 2-day, hands-on course where you'll learn how to:
- Understand AI in pharma marketing: key terminology, applications, and limitations
- Optimise data management and organisational readiness for AI adoption
- Apply AI for strategic and tactical decision-making
- Enhance HCP engagement through AI-driven personalisation
- Boost productivity and streamline MLR processes with AI tools
The AI for Pharma Marketing Course
With Manuel Mitola
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