PHARMA L&D LEADERS MUST PRIORITISE DECISION MAKING ALONGSIDE AI SKILLS

Imagine if your employees could spot a bad AI answer before it became a business risk.

That ability is quickly becoming one of the most valuable workplace skills in many industries, including the pharmaceutical industry.

This week, the BBC reported warnings from the Royal Observatory Greenwich that overreliance on instant AI answers could weaken “the habits of questioning and evaluation that underpin knowledge, expertise and innovation.”

For Learning and Development leaders, this changes the AI conversation completely. The focus is no longer just about helping people use AI tools. It is about helping people make better decisions while using them.

Pharma L&D Leaders Must Prioritise Decision Making Alongside AI Skills

Many organisations have spent the last two years investing in AI capability. There has been huge growth in AI awareness training, blended learning programmes and eLearning designed to improve adoption.

But AI capability alone is not enough.

Employees also need strong decision making and critical thinking skills so they can evaluate outputs properly, recognise risk and apply human judgement when it matters most.

This is particularly important in pharma, where mistakes can directly affect patient safety, compliance and public trust.

Interestingly, some of the most effective AI users are not treating AI as an answer machine. They are using it as a thinking partner.

The BBC article references LinkedIn co-founder Reid Hoffman, who suggested people should ask AI questions like: “What’s wrong with my idea?”

That approach is powerful because it encourages employees to challenge assumptions instead of blindly accepting outputs.

How Learning And Development Can Help

Strong decision makers are not created through information-heavy training alone. People develop judgement through practice, reflection and realistic experiences.

This is where modern instructional design and corporate training solutions become critical.

Instead of simply testing knowledge recall, organisations should create interactive eLearning experiences that place learners in ambiguous, high-pressure situations where they must evaluate evidence, identify risks and justify decisions.

For example, employees could work through realistic compliance scenarios, medical information challenges or AI-generated summaries containing subtle inaccuracies. The goal is not simply to teach people how AI works. The goal is to teach people when to question it.

This is where custom eLearning content can create real business value. Organisations that strengthen decision making often improve innovation, reduce compliance risk and build greater operational resilience.

The Next Evolution Of AI Learning

As AI becomes more common, technology itself will become less of a competitive advantage.

Human judgement will become the differentiator.

The organisations that succeed will not necessarily be the ones using the most AI. They will be the ones developing employees who can think critically, evaluate information carefully and make smart decisions alongside AI tools.

For pharma Learning and Development leaders, that represents a huge opportunity - building workforces capable of thinking clearly in an AI-driven world.

FAQs

Why should pharma organisations focus on decision making skills?

Because AI can provide inaccurate or misleading information. Employees need strong judgement skills to identify risks and make safe, informed decisions.

What role does Learning and Development play in AI adoption?

Learning and Development helps employees use AI effectively by building critical thinking, ethical reasoning and practical decision-making skills alongside technical AI capability.

How can interactive eLearning improve critical thinking?

Interactive eLearning allows learners to practise evaluating evidence, solving problems and making decisions in realistic workplace situations.

What are the risks of relying too heavily on AI?

Overreliance on AI can lead to poor decision making, reduced critical thinking, compliance failures and increased organisational risk.

What should modern AI training programmes include?

Modern programmes should combine AI literacy with scenario-based learning, critical thinking exercises and learning impact evaluation focused on behavioural change.