AI is transforming early careers, not by eliminating them, but by accelerating them. John Schneider explores how companies like PwC are rethinking onboarding and leadership development, equipping new hires to supervise AI from day one. The challenge? Ensuring tomorrow’s leaders don’t miss the vital learning today’s grunt work once offered.
There’s a common refrain in conversations about AI and the workforce: Entry-level jobs are disappearing. If AI can take over the repetitive tasks that have traditionally been the proving ground for young professionals, where will the next generation of managers come from?
The prediction is often gloomy, that young people will struggle to get hired at all, locked out of the career ladder before they’ve had a chance to climb it. But what if the opposite is true? PwC’s recent announcement offers a different picture: junior accountants aren’t being pushed out, they’re being pushed up. With AI taking on routine audit tasks, new hires will step into responsibilities that look more like management within just a few years. In the words of PwC AI leader Jenn Kosar: “Three years from now, we will feel like the first years are functioning more like fourth years.”
AI adoption isn’t just about efficiency
This is more than just a shift in tools; it’s a shift in the pace of careers. And it’s a signal to every organisation that AI adoption isn’t just about efficiency, it’s about rethinking how we onboard, develop, and prepare talent for leadership.
From task execution to AI supervision
In many professions, entry-level work has traditionally meant task execution. For accountants, that might be gathering data, reconciling transactions, or preparing standard reports. In law, it might be a document review. In marketing, it could be drafting copy or compiling campaign results. These were the building blocks, the repetitions that prepared employees for higher-level judgment calls.
AI changes that progression entirely. Routine tasks that once occupied entire early careers are now automated. That means a new hire’s day-to-day isn’t about doing the work, but about overseeing it. They aren’t the hands on the keyboard as much as they are the reviewers, the verifiers, the ones ensuring AI-generated outputs are accurate, ethical, and strategically sound.
I think about how different my own career start might have been. When I joined Deloitte Consulting in San Francisco out of college, my first projects were large-scale ERP transformations using platforms like SAP and Oracle. I was given a PC and asked to write databases in SQL and configure software based on the business requirements I gathered from stakeholders. It was technical, detail-heavy work, the kind of foundational experience that consultants used to spend years mastering.
Now imagine if I’d had an AI assistant capable of writing all the code and configuring the software based solely on my inputs. Suddenly, the focus of my role wouldn’t be buried in technical execution, it would shift to ensuring the quality of the work, engaging more deeply with stakeholders, and spending more time on the change management that makes a transformation succeed.
That’s the leap AI is enabling for today’s entry-level employees. They’re moving straight into work that requires judgment, influence, and leadership, the very skills that used to take years to develop. And that’s thrilling but also unnerving, as developing the skills of a leader takes time and experience.
The new entry-level skills: Critical reasoning and human connection
If you no longer need to spend three years mastering data entry before you can supervise it, what becomes the foundation of early career development? Leadership requires critical reasoning, communication, and interpersonal abilities. These skills are essential for leading teams, navigating ambiguity, and creating value in real-world business environments. Those same skills are now the essential starting point for today’s AI-era entry-level roles.
- Critical reasoning – The ability to spot errors in AI outputs, ask the right follow-up questions, and challenge assumptions
- Communication – Translating AI insights into client-ready narratives and guiding colleagues through changes
- Empathy – Understanding the human context of decisions and the impact they have on clients and coworkers
- Leadership fundamentals – Managing expectations, facilitating collaboration, and resolving conflicts
These have always been valuable skills, but they were often learned later, after years of doing more repetitive work. Now, they’re table stakes from day one. Kosar described PwC’s training as going “back to basics” not in the sense of reverting to old processes, but in prioritising the fundamental mindsets and abilities that AI can’t replicate. In her words, “People are going to walk in the door almost instantaneously becoming reviewers and supervisors.” That changes the kind of onboarding and mentorship that companies must provide.
Human+AI in action: Augmenting the workforce, not replacing it
This shift is a clear example of the new ways of interacting; a workforce where people and intelligent systems work side by side, each amplifying the other’s strengths. In the Human+ era context, AI takes on the heavy lifting of data processing, pattern recognition, and repetitive execution. Humans provide judgment, empathy, adaptability, and creativity. The magic happens in the collaboration, not in one replacing the other.
For entry-level employees, their earliest workplace experiences will involve learning how to direct and evaluate AI outputs just as they would a team member’s work. That’s not just an efficiency gain; it’s part of a leadership accelerator. However, while someone can learn to direct and evaluate agentic AI output, and they might become great at it, that’s not the complete picture. Will that experience teach them to be collaborative, active, engaged listeners, empathetic to others, and clear and fair? They need all of these attributes and AI expertise to push ahead in leadership roles.
The career ladder just got shorter and steeper
The traditional career trajectory was predictable: years of foundational work, incremental promotions, and gradual exposure to higher-stakes responsibilities. Now, that timeline is collapsing. An employee who might have taken five years to reach a supervisory role could get there in two or three. That’s exciting, but it’s also challenging. Not everyone is ready to handle that level of responsibility so soon, nor is the education system teaching interpersonal skills. You can’t bottle real-world experience into a leadership course and, without intentional development programs, organisations risk promoting people faster than they can truly grow into their roles.
The real danger is that AI will lead to underprepared managers if companies don’t reengineer their training
The danger isn’t that AI will make early-career employees obsolete. After all, you can’t simply cut out the lower rung. Every company needs to hire, train, and develop new generations of employees. The real danger is that AI will lead to underprepared managers if companies don’t reengineer their training and mentorship to match the new pace.
Of course, there’s a catch. Those “grunt work” years weren’t just filler, they were where we built the instincts and judgment that later defined us as leaders. We learned to spot red flags in the details, troubleshoot under pressure, and understand the nuances of process. If AI takes those tasks off our plates, we need new ways to teach those skills early: immersive simulations where mistakes are safe but costly, rotational assignments that expose employees to different functions, and structured shadowing of experienced leaders making real-time calls. The point isn’t to recreate the old grind, but to design intentional learning experiences that build the same depth of judgment, without requiring years of repetitive execution to get there.
The organisational implications
The acceleration of entry-level employees into managerial roles raises new strategic questions for every organisation:
- How do we redesign onboarding?
Orientation can’t just be about systems and policies — it needs to include critical thinking, AI literacy, and human leadership skills from day one - How do we prepare managers to manage AI-augmented teams?
Leaders at all levels need fluency in what AI can and can’t do, and how to integrate it into workflows without losing human oversight - How do we retain accelerated talent?
If employees are advancing faster, their expectations for growth and impact will be higher. Organisations must find ways to keep them challenged and engaged - How do we keep culture intact?
Moving people into leadership earlier means they’ll be shaping culture sooner. We can’t assume they’ll inherit it; we have to teach it.
Organisations will also have to be mindful when younger employees may be leading teams of seasoned employees with more years in the workforce. While everyone knows and appreciates a good leader of any age, if there is a sense that less experienced employees are being promoted too quickly into leadership positions, there is bound to be tension that can lead to infighting, disengagement, and churn
Why this is exciting, if we get it right
The narrative of AI and the workforce often focuses on loss — of jobs, skills, and stability. But the PwC example shows a different possible future: one where careers advance faster, young professionals contribute at a higher level sooner, and the partnership between humans and AI creates more meaningful work.
That future is only possible if we treat AI adoption not as a technology project, but as a talent strategy. It requires HR, L&D, and functional leaders to work together to design a workplace where AI enables human potential rather than side-lining it.
It also requires a mindset shift: We aren’t just teaching people to use AI; we’re teaching them to lead with it. That’s the most exciting part for me. Looking back at my own start in consulting, I can see how much faster my development would have been if AI had freed me from the most repetitive technical work.
And now, I can imagine my own kids stepping into that reality, not just entering the workforce, but shaping it from day one. The Human+era workforce isn’t about replacing one set of workers with another, it’s about combining the best of human capability with the best of machine intelligence to create something stronger.
If PwC’s prediction holds true, the first generation to grow up with AI as a colleague won’t just be the managers of tomorrow, they’ll be the leaders redefining what management means.
John Schneider is Chief Marketing Officer of Betterworks
