How can L&D prepare managers to lead AI adoption?

AI adoption puts a new set of demands on managers.

They are expected to understand enough about AI to guide their teams, create space for experimentation, manage new risks, and connect AI use to business outcomes. At the same time, they are already managing performance, reorganizations, competing priorities, and change fatigue.

For Marlene De Koning, Director of (Gen)AI & Innovation and Workforce Transformation at PwC; Anna Svitak, Learning Advisor Safety at Shell; and Milica Sapic, Senior Enablement Architect, GTM at Personio, this makes one thing clear: preparing managers for AI requires more than adding an AI module to the leadership curriculum.

The real question is: what does it mean to be ready to lead AI adoption?

Manager readiness needs to be redefined

Traditional manager development often focuses on leadership, communication, performance and people management. AI adds another layer: managers need to understand how technology changes the work their teams do.

Marlene De Koning explained:

“A manager does not necessarily need to be the most technical AI expert, but they need to be able to translate the business ambition from the organization to what is then needed from technology and what is needed from the people within their organization.” 

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This means manager readiness starts with understanding the intended business outcome. Managers need to identify which tasks, decisions and responsibilities are changing and then help their teams adapt.

Managers need to lead by example

Employees are more likely to adopt new ways of working when they can see how those behaviours fit into everyday work.

For managers, this means experimenting themselves, talking openly about what works and what does not, and making AI part of regular team conversations rather than treating it as a separate project.

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The manager does not need to have every answer. Their role is to help the team understand the change, provide direction and create the conditions for learning.

Psychological safety needs to be part of AI adoption

AI can change how employees see their work. People may have concerns about new expectations, changing responsibilities or making mistakes while experimenting.

That makes psychological safety an important part of manager enablement.

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For managers, psychological safety is closely connected to whether employees feel able to ask questions, raise concerns and experiment.

Marlene De Koning also explained:

“You can really address it on a team level and make sure that there's more clarity around the communication of what is expected and how people also can speak up.”

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This makes clarity particularly important. Employees need to understand what is expected of them and where they have room to test new approaches.

Managers need to be ready for difficult conversations

AI adoption can raise uncomfortable questions. Employees may wonder whether their responsibilities will change, whether certain tasks will disappear or whether their existing skills will still be relevant.

Managers are often the people employees turn to when these questions arise.

The panel also highlighted the need for managers to navigate change fatigue, uncertainty and courageous conversations as AI changes the way teams work. 

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This means manager development needs to include more than AI knowledge. Managers also need communication and leadership skills that help them support people through change.

Managers are carrying a lot already

AI adoption does not happen in isolation. Managers are already dealing with multiple priorities, organisational changes and competing demands.

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Rather than adding AI as another separate responsibility, managers can integrate it into existing routines such as stand-ups, reflections and one to ones. These moments can become opportunities to discuss what teams are learning, where AI is creating efficiencies and what challenges are emerging. 

This makes adoption more practical. AI does not have to become another project on a manager's list. It can become part of how managers already lead their teams.

Managers need spaces to learn from each other

Formal training is only one part of manager enablement.

As teams experiment with AI, managers will encounter different challenges and discover different approaches. Creating spaces where they can share these experiences can help turn individual experimentation into organisational learning.

Milica Sapic highlighted the value of forums where managers can share best practices, discuss challenges and reflect on efficiencies. 

This type of peer learning is particularly relevant because AI is changing quickly. Managers are not learning a finished system; they are learning how to work with technology that continues to evolve.

AI needs both direction and experimentation

AI adoption cannot be entirely top-down or entirely bottom-up.

Leadership needs to provide direction, strategic priorities and guardrails, while employees need room to experiment with how AI can improve their actual work.

Milica Sapic described this balance:

“Leadership sets the vision and the guardrails, and then employees need room to experiment.” 

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She also highlighted the importance of creating spaces where experimentation can happen before organisations try to scale new approaches. 

This gives managers a practical role. They need to communicate the organisation's direction while creating enough space for teams to discover how AI can actually improve their workflows.

Everyone is becoming a manager of AI

One of the most interesting ideas from the discussion was that AI changes management responsibilities beyond formal managers.

Marlene De Koning explained:

“All of your people are becoming managers for a bit.” 

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Employees increasingly delegate tasks to AI, review outputs and decide whether the result is good enough to use.

In that sense, AI introduces a form of management responsibility at every level. Employees need to exercise judgment, assess quality and take responsibility for the final outcome.

Murielle Bolsius connected this directly to the human side of AI adoption, highlighting the importance of critical thinking, judgment and human connection when working with AI. 

This is why manager enablement and workforce enablement increasingly overlap. 

Ultimately, preparing managers for AI adoption is not about turning them into AI experts. It is about giving them the confidence, skills and support to guide their teams through change. By combining AI understanding with experimentation, clear communication, psychological safety and peer learning, L&D can help managers turn AI from a new technology into a practical part of how their teams work.