As artificial intelligence transforms everyday work, organizations face a question that deserves more attention: how will professionals develop the experience and judgment they need to become effective leaders?
The Work That Taught Us How to Work
Think back to the early years of your career.
You probably spent countless hours preparing reports, researching unfamiliar subjects, reviewing information or trying to solve problems you had never encountered before.
Some of that work was repetitive. Some of it was frustrating. And looking back, you might wonder whether all those hours were really necessary.
But you were learning more than how to complete a task.
You were discovering how to recognize patterns, question assumptions, deal with uncertainty and understand why certain decisions worked while others didn’t.
Much of that learning came from the people around you. A manager who challenged your reasoning. A colleague who explained something you hadn’t considered. Someone more experienced who shared a mistake they had made years earlier.
These moments rarely appeared in a formal development plan. They were simply part of working, making mistakes, asking questions and gradually becoming better at what you did.
Today, artificial intelligence is changing how many of those activities are performed.
And that raises an interesting question: if technology increasingly handles the tasks through which professionals used to learn, how will we develop the next generation of leaders?
When AI Changes the Learning Experience
There’s no question that AI brings enormous opportunities.
It can help us research unfamiliar topics, analyze information, prepare documents and explore possible solutions in a fraction of the time these activities once required.
For organizations, that’s an attractive proposition. Less time spent on repetitive tasks means more time potentially available for work that requires creativity, collaboration and judgment.
But there’s something worth considering.
Some of the tasks we’re now asking AI to perform were also helping people develop professionally.
Take a junior consultant preparing an analysis for a client.
The real value of that assignment was never just the presentation delivered at the end. It was also the process of deciding which information mattered, identifying inconsistencies, understanding the client’s situation and learning how to defend a recommendation.
Today, AI can help produce a convincing first draft in seconds.
That’s useful, of course. But what if the consultant accepts the result without really understanding how the conclusions were reached?
The problem isn’t the technology. It’s the possibility of losing learning opportunities without even noticing.
According to the World Economic Forum’s Future of Jobs Report 2025, employers expect 39% of workers’ existing skill sets to change or become outdated between 2025 and 2030.
That transformation reflects several forces, not AI alone. Still, it gives organizations a good reason to reconsider how people acquire and develop professional capabilities.
After all, becoming more efficient at completing work and becoming more capable of doing it are not necessarily the same thing.
Information Is Not the Same as Judgment
We have more access to information than any previous generation of professionals.
Need an explanation? A recommendation? A summary of a complex subject? AI can provide one almost instantly.
But getting an answer and knowing what to do with it are two different things.
Professional judgment involves understanding the context behind a problem, recognizing what might be missing, weighing alternatives and making decisions when there isn’t an obvious right answer.
It also means knowing when to challenge a recommendation, even when it sounds perfectly reasonable.
A 2025 study by researchers from Microsoft and Carnegie Mellon University explored how knowledge workers perceive their own critical thinking when using generative AI.
The researchers found that greater confidence in AI was associated with less reported critical-thinking effort. They also observed that AI-assisted work can shift the nature of critical thinking toward activities such as verifying information and integrating results.
This doesn’t mean AI is making professionals less capable of thinking critically. The study doesn’t establish that.
But it does raise an important question about the habits we’re developing as we rely more heavily on these tools.
Are we using AI to strengthen our thinking, or are we sometimes allowing it to do the thinking for us?
The distinction matters, particularly for professionals who are still building the experience needed to make complex decisions.
What Experience Can Teach That Answers Alone Cannot
Imagine a young manager preparing for a difficult conversation with someone on their team.
They ask an AI tool for guidance and receive a thoughtful response: how to structure the conversation, which questions to ask and how to approach the situation constructively.
That’s a good starting point.
Now imagine that same manager talking with an experienced leader who has dealt with similar situations.
The conversation might take an unexpected direction.
The experienced leader could describe a time when their own approach failed. They might explain how a seemingly minor detail changed the outcome, or ask a question that helps the manager see the situation differently.
Perhaps they’ll even challenge the manager’s assumptions about what’s really causing the problem.
This is one of the things that makes learning from experience so valuable.
It’s not simply about receiving advice. It’s about gaining perspective.
Of course, experience doesn’t guarantee wisdom. What worked in one organization or at one point in someone’s career may not work in another situation.
That’s why the most useful developmental conversations aren’t necessarily the ones in which an experienced professional provides all the answers.
Sometimes, the greatest contribution is helping someone ask better questions.
Experience becomes especially valuable when it helps another person develop their own ability to think, decide and act.
The Growing Relevance of Professional Mentoring
This is where Professional Mentoring becomes particularly relevant.
At Collective Brains, we define Professional Mentoring as the practice of supporting the development of professionals by bringing relevant knowledge, perspective and real-world experience into a purposeful developmental relationship.
A mentor can share experiences that help someone understand a challenge differently. They can offer perspectives that aren’t immediately obvious, question assumptions and encourage reflection before decisions are made.
But effective mentoring also requires knowing when not to offer an answer.
There are moments when sharing a personal experience is exactly what someone needs. At other times, a thoughtful question or simply listening can be far more valuable.
In a world where information and recommendations are increasingly available on demand, these human conversations take on a different kind of importance.
They create space to explore the reasoning behind decisions, consider their consequences and learn from situations that don’t have simple answers.
Organizations also have an opportunity here.
Think about the experience accumulated by professionals who have spent years navigating complex projects, difficult decisions and organizational change.
How much of that knowledge is actually being passed on to others?
And how much disappears when experienced professionals move on or retire?
Professional Mentoring offers a way to make that exchange more intentional.
That doesn’t mean every experienced professional will naturally become a good mentor. Helping someone else develop requires skills of its own, including empathy, communication, thoughtful questioning and the ability to create a relationship built on trust.
These are among the principles that guide the Collective Brains approach to developing professional mentors.
Developing Future Leaders With Intention
AI will continue to change how we work.
Some responsibilities will disappear, others will evolve and entirely new opportunities will emerge.
Organizations will naturally focus on what the technology can do for productivity and performance. They should.
But there’s another question worth bringing into those conversations:
How are we making sure people continue to develop while the work itself is changing?
The answer will probably involve several approaches.
Rethinking early-career assignments. Creating more opportunities for feedback. Encouraging people to question AI-generated recommendations rather than simply accept them. Giving professionals room to make decisions, reflect on outcomes and learn from mistakes.
And making better use of the experience already available within organizations.
AI can be part of that learning process, too. It can help people explore ideas, practice conversations and consider alternatives they might otherwise overlook.
There’s no reason to treat technology and human development as competing priorities.
The challenge is to make sure they reinforce one another.
Professional Mentoring can contribute by connecting experienced professionals with those who are still developing their own judgment, confidence and perspective.
Because tomorrow’s leaders will need more than the ability to work with intelligent systems.
They’ll need to understand people, navigate uncertainty, challenge assumptions and take responsibility for decisions that don’t come with straightforward answers.
As AI changes how work gets done, organizations need to think just as carefully about how their people grow.
Perhaps the most important question isn’t what AI will allow us to do faster, but what we still need to learn how to do well.
Frequently Asked Questions
- How is artificial intelligence changing professional development?
AI is changing how professionals access information, complete tasks and solve problems. While it can make learning and everyday work more efficient, it may also change some of the hands-on experiences through which people traditionally developed their skills. Organizations need to consider how employees will continue building critical thinking, professional judgment and decision-making capabilities as AI becomes part of their work.
- Why is professional judgment important in an AI-driven workplace?
AI can generate useful information and recommendations, but professionals still need to evaluate whether those recommendations make sense in a particular situation. Professional judgment involves understanding context, recognizing risks, weighing alternatives and making responsible decisions, especially when the right answer isn’t immediately clear.
- What role can Professional Mentoring play in the age of AI?
Professional Mentoring gives people opportunities to learn from the experiences and perspectives of others. Through meaningful conversations, relevant examples and thoughtful questions, mentors can help professionals reflect on challenges, consider different approaches and strengthen their ability to make independent decisions. This makes mentoring a valuable complement to AI-supported learning.
- Can AI replace professional mentors?
AI can support professional development by providing information, helping people explore ideas and offering opportunities to practice different scenarios. But Professional Mentoring also involves a human relationship built on trust, experience, context and dialogue. Rather than viewing AI and mentoring as substitutes, organizations can benefit from understanding how each contributes to professional growth.
