There’s a growing fear that artificial intelligence will soon replace human talent. While it’s undeniable that AI will impact the labor market, as with any disruptive technology, a closer look reveals a different—and far more empowering—future.
Rather than displacing highly skilled professionals, AI is setting the stage for knowledge workers to transition from individual contributors into high-leverage managers, directing teams of AI agents that can execute tasks with breathtaking efficiency. Rather than consign the expertise and creativity of humans into irrelevance, AI will make it all the more essential, as humans direct and guide AI agents toward the ideal outcome.
AI as High-Performing Team Members
Today’s AI systems are already demonstrating mastery in tasks ranging from data analysis and report generation to complex decision-making in finance, legal research, and the creative industries. In many of the sectors mentioned, this capability emerged only in the past few years, as generative AI became a viable and mature tool for businesses.
Agentic AI is the next logical step, wherein AI isn’t a tool that assists a human worker but one that acts alongside them with a degree of autonomy. In effect, digital agents are becoming the new breed of employees: competent, consistent, and ever-improving, with the ability to work around the clock and to ingest vast quantities of data in a matter of seconds.
You can understand the fear this provokes. AI agents have the ability—at least, in their realm of operations—to be faster, better, and cheaper than humans. But even the best talent needs a manager. And managers with the most high-flying players on their team are the most effective in the organization. The future belongs to professionals who channel AI’s capabilities into results that are exponentially better than what any one person could achieve alone.
Leading AI Through Technical Management
This begs the question: What does it mean to be a manager of AI agents?
The truth is that effective management has always required a dual set of skills, whether we’re talking about people or, indeed, AI systems. On one hand, there’s people management—the art and science of understanding human behavior, motivation, and emotions. Although AI lacks that emotional depth, effective collaboration with AI agents requires certain soft skills, like the ability to set expectations and provide clear, unambiguous instruction.
On the other hand, management also means organizing, delegating, and ensuring that systems are in place to execute a strategic vision. This isn’t just about setting a direction; it’s about verifying that every task contributes toward delivering a shared goal.
These abilities (tactical oversight, process optimization, and strategic judgment) are specialized skills that don’t easily transfer among different domains. It’s one reason why a stellar sales manager might struggle if suddenly tasked with running an engineering team, and why an esteemed product manager might struggle to motivate a sales team.
In a world where AI agents work alongside us, these two facets of management become even more critical. While AI can execute many tasks with remarkable speed and precision, a manager guiding a team of AI agents must both understand the intricate mechanics of the technology and appreciate the human elements of collaboration to work with other human peers who are managing AI systems.
The common notion that great managers need to be skilled only in people management, without truly grasping how the work is done, misses the mark entirely. Anyone who’s experienced a manager disconnected from the practical realities of the job will tell you that true leadership demands a hands-on understanding combined with a clear vision.
Revisiting the Job Displacement Myth
Some worry that as AI becomes more capable, we’ll need far fewer humans in the workforce, which will ultimately lead to mass unemployment. The counter-argument to this common claim is known as Jevons paradox: the idea that increases in efficiency can paradoxically lead to even greater overall demand. While AI might take over tasks that human beings currently do in the workplace, the gains in efficiency in certain tasks will increase the need for human operators (and the human touch) in other ways.
The mistake people continually mistake is assuming that the demand for humans (and human skills) is elastic only in one direction—down. That we’ve reached a ceiling for the usefulness of the collective human race and, over time, that ceiling will get lower and lower.
If we embrace the possibility that a single person managing AI could deliver outputs far beyond what we see today, we aren’t looking at a future with fewer opportunities.
Similarly, the industrial revolution replaced countless manual jobs, particularly in sectors like garment manufacturing, but at the same time it led to a historic explosion of wealth that continues to this day, although, admittedly, unevenly shared. It led to lower prices for many staples of living, not to mention luxuries, which in turn raised our standard of living.
The current wave of AI pessimism ignores previous historical trends. It’s equally plausible that the productivity boost of AI will unlock entirely new opportunities—new markets, industries, and innovative products—that we can’t even imagine now. While some jobs might be displaced, others may emerge in the economy that offset that loss. AI agent managers are just one example.
So, How Do We Get Ready for This Shift?
I’ve been careful not to minimize the pain that a transition to an AI-centered economy will bring. Just like the industrial revolution brought its own short-term displacement, the same will happen here, but with nowhere near the force and system shock that came with the full-blown mechanization of human labor. I believe AI’s path will be slower and more deliberate, and that there are many steps we can take along the way to make the transition much smoother.
First, let’s talk about education. Universities are great at producing academics, but they don’t necessarily provide vocational and professional skills. A computer science program will teach you about algorithms, but it might not cover things like GitHub and Docker. As we transition to an AI-powered workforce, it’s likely we’ll need to shift the emphasis away from academics and toward practical, real-world skills. These are the skills that were, in many parts of the world, once provided by polytechnic institutes and are now offered by community colleges in the United States. I would argue that we need more of them, and to treat them with greater esteem.
For the current workforce, companies need to make AI literacy part of their playbook, inculcating it within existing workers and incorporating it into their onboarding processes. Training should be provided evenly, from the most junior hires to the C-suite. The companies that start from the outset with an AI-enabled, AI-aware workforce will be those that thrive during this period.
And for individuals, especially those in jobs most vulnerable to being disrupted by AI, this is the time to take action. The best thing you can do? Start learning. Not everyone needs to become a software engineer, but understanding AI tools, getting comfortable with digital workflows, and building problem-solving skills will make all the difference.
But here’s the catch: It’s not just about knowing how to use AI. It’s about knowing enough to question it.
AI is powerful, but it’s not perfect. Blindly accepting AI-generated outputs without understanding the logic behind them, or the limitations of the models themselves, is a recipe for disaster. It’s also, fundamentally, the definition of AI illiteracy. Ultimately, the role of an AI agent manager will be to push back against their “employees” from time to time.
The professionals who thrive in this new era will be those who keep their critical thinking skills sharp and who can evaluate AI’s suggestions, knowing when to trust it and when to override it. The good news? There’s no shortage of ways to level up: free courses, employer-led training, AI boot camps, and self-guided learning. The resources are there, but you have to take the first step. The future belongs to those who adapt—and those who think critically.
No comments