Editorial
White Paper
The Future of Leadership Development: AI-Driven Manager Enablement
There’s a growing concern that AI is eroding our skills.
If AI can write, code, summarize and analyze, what happens to the people who used to do those things? Do we become less capable over time? Less sharp? More dependent?
Those concerns aren’t unfounded. When work is automated, certain skills atrophy. People practice them less and rely on tools more.
At the same time, we're recognizing that as AI takes over execution, our deeply human skills — creativity, empathy, judgment — will become even more important.
An interesting dynamic is emerging from all of this: In many cases, people may actively strengthen human skills as a result of working with AI. For learning and development (L&D) and HR professionals, that creates a real opportunity to shift skill development into the flow of everyday work.
Work Shifts Lead to Skill Shifts
A recent episode of The Daily raised an important point: Programmers aren’t spending as much time writing code line by line. Instead, they’re describing what they want, guiding AI tools and evaluating what comes back. Some noted that their work with AI has improved their communications more broadly, in emails, chats and live conversations.
The same dynamic is reshaping how leaders direct work. Leaders can be vague when speaking with employees, leaving their direct reports to fill in the gaps in their half-formed thoughts. AI makes that less likely. If a prompt is unclear, the output reflects it immediately and when expectations aren’t well-defined, the result will often miss the mark.
AI is exposing something that goes unnoticed in human collaboration: much of our work has relied on others compensating for unclear thinking.
Because working with AI requires clearer instructions, it has the potential to change how people think about directing work altogether. AI users are learning to clarify what a good result looks like, upfront and also to be explicit regarding constraints. These two leadership skills are getting practiced regularly by those who lean heavily on AI tools, even those who aren’t yet leaders.
Uncertainty is also being handled differently. Rather than moving forward with incomplete direction, AI users are learning to build in the expectation that AI should ask questions, one at a time, before work begins. This small shift can directly translate to better alignment when working with others.
This dynamic may also change the process of giving feedback. Vague reactions aren’t useful when refining AI output. Instead, AI users are learning to be more precise in sharing what specifically needs refinement. Over time, repeated practice has the potential to build a more disciplined approach to feedback, one that is clearer, more actionable and easier to apply.
Mindset Matters
The above examples are just the tip of the iceberg of where AI can offer growth. But there is a wrinkle in how much development can occur. A Microsoft Research and Carnegie Mellon survey of 319 knowledge workers found that people with the most trust in AI tended to think the least critically. But people who brought their domain expertise to the interaction, stayed skeptical, cross-referenced outputs and applied judgment, showed the opposite pattern. Their engagement with AI actively strengthened their critical reasoning.
In another example, an MIT Media Lab study found that students who used AI to write essays produced polished work but showed lower brain activity, weaker memory recall and less ownership of their ideas. Many people drew the conclusion that AI decays your thinking.
But a different interpretation is that using AI as a ghostwriter can make you a more passive thinker. Whereas using AI as a thought partner may return a different result entirely.
This makes considering the active role of the AI users important. When they are passively accepting output, they’re unlikely to develop new skills, but when actively directing and evaluating that output, they’re more likely to practice and develop communication, collaboration and leadership skills.
The Development Nobody Is Shaping
All of this points to an opportunity that organizations haven’t captured. Employees are practicing high-value human skills every day when they clarify expectations, structure problems, evaluate outputs and refine their thinking. But this is happening informally, unevenly and without recognition.
L&D can use these interactions with AI as a method of developing skillsets beyond AI adoption and efficiency.
Instead of treating AI as separate from development, it can be viewed as a built-in practice environment for human skills. Google's recent AI experiment, Vantage, offers a model for what this looks like in practice. Rather than simply assessing what students know, it pairs them with a team of AI agents on real tasks and observes their approach. The skill-building is built into the work itself, not layered on top of it. Corporate L&D doesn't need to wait for a formal product to apply the same logic.
The goal for corporate training departments should be to help learners use their everyday AI interactions more intentionally to practice the human skills that drive better work. The research is clear that passive engagement with AI output produces passive thinkers. What L&D can do is design habits and workflows that cultivate the opposite: employees who treat AI as something to interrogate rather than accept.
That might look less like new training programs and more like small structural shifts. Encourage employees to compare and critique outputs rather than accept them. Ask them to reflect on their prompts to identify what worked. The final focus is on how they can apply their learnings in AI to interactions with employees and co-workers.
Part of this is giving these emerging skills clear names: The ability to translate intent into clear direction. The ability to evaluate and refine outputs. The ability to operate iteratively and with judgment.
These aren’t new skills. But AI is making them more relevant for all employees in a way that’s hard to ignore. Getting ahead of this means recognizing that the training environment has changed and L&D must deliberately build for that environment.
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The Real Opportunity
AI is often framed as a threat to human capability but in many ways, it’s doing the opposite. By removing friction and exposing weak thinking, it’s pushing people to operate with more precision, more structure and more intention.
When L&D recognizes this, they get closer than ever to learning in the flow of work. Because AI is already one of the most scalable practice environments we’ve ever had. The question is when training professionals will start leveraging it.
Editor's Note: Where else has the need for critical thinking in relation to AI come up?
- In AI We Trust. Or Not. The Next Frontier of Work — Don't trust the AI — trust the systems you build around it. Like pilots and doctors, confidence comes from training, checklists and knowing when to stop.
- The Cognitive Economics of AI — AI promised to free up our time, but it's making us busier than ever. Here's why protecting time to think is a leadership imperative.
- 5 Questions Every Leader Should Ask Before Building AI Solutions — AI isn’t the enemy — or the magic fix. Most failures come from leaders skipping the hard questions. Here are 5 that separate hype from real impact.
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