As a specialist in diversity, equity, and inclusion, Sofia Khaira helps businesses navigate the evolving landscape of talent management. Today, she joins us to discuss a critical challenge: the hollowing out of early-career training in the age of AI. We’ll explore the strategic risks of over-automating junior roles, the disappearance of the informal “training ground,” and how HR leaders can become “designers of progression,” ensuring that a new generation of professionals develops the essential human skills that technology can’t replace.
With data showing a steep decline in graduate job postings as AI automates entry-level work, what are the most critical “human skills” being lost in this shift? Beyond efficiency, what is the long-term strategic risk for a business that over-automates its junior roles?
It’s a stark reality. When we see data from recruitment groups like Reed showing a 70% drop in graduate postings in just two years, or companies like PWC reducing their intake, it’s a clear signal. We are losing the foundational experiences that build judgment, resilience, and confidence. These aren’t just buzzwords; they are the bedrock of professional growth. By automating away the so-called “menial” work, we’re removing the very sandboxes where young professionals learn to navigate uncertainty, receive real-time feedback, and simply become capable. The long-term risk is a critical soft skills deficit. You end up with a generation of employees who are technically proficient but struggle with leadership, collaboration, and ethical decision-making when the rules aren’t clear. The short-term efficiency gains will be completely overshadowed by a future leadership vacuum.
Early-career roles often serve as a training ground where learning happens through proximity and observation. As AI handles routine tasks, how can leaders replicate this “learning by osmosis”? Please share a specific example of how to intentionally design experiences that build professional judgment and confidence.
That “learning by osmosis” is absolutely vital, and it’s what I see disappearing the fastest. It used to be about sitting in on meetings, hearing how an experienced colleague handles a difficult client, and absorbing the unspoken cues of professional life. When AI automates the entry points, those opportunities vanish. To replicate this, leaders must be incredibly intentional. For instance, instead of just assigning a task, design a structured shadowing experience. An early-career employee could be paired with a senior team member for a week, not just to watch, but to debrief. After a client negotiation, the leader could ask, “What did you observe? What question do you think was most pivotal? What would you have done differently?” This transforms passive observation into an active learning process, deliberately building the judgment and confidence that once grew more organically.
A future workforce skilled in tech but deficient in leadership and collaboration presents a significant challenge. How will this soft skills gap manifest in day-to-day operations in five to ten years? What are the first warning signs that a company’s talent pipeline is becoming hollowed out?
In five to ten years, this gap will be painfully obvious. You’ll see it in project meetings where technically brilliant team members can’t build consensus or navigate conflicting priorities. You’ll see managers who can execute a plan flawlessly but are unable to inspire their teams or provide meaningful, constructive feedback. The day-to-day friction will increase because the interpersonal skills that smooth collaboration—reading the room, showing empathy, building trust—will be underdeveloped. The first warning signs are subtle. You might notice a rise in mid-level managers who escalate every minor interpersonal issue because they lack the confidence to handle it themselves. Another red flag is when your internal promotions consistently fail to produce effective leaders, forcing you to always hire externally for roles that require strong decision-making and people skills. That’s when you know your internal pipeline has been hollowed out.
The concept of HR acting as “designers of progression” is powerful. Can you walk us through the first three steps an HR team should take to remap their early-career journeys? What metrics could they use to measure the development of confidence and capability, not just task completion?
I love this shift in mindset from HR as administrators to designers. The first step is to adopt human-centered design thinking. Instead of starting with what tasks can be automated, start with the question: “What experiences does an emerging professional need to gain confidence and capability over the next two years?” Step two is to map the entire early-career journey and identify the critical moments that build judgment—the first client presentation, the first time handling negative feedback, the first project failure. These are your design targets. The third step is to intentionally redesign roles around these moments, creating structured opportunities for mentorship, feedback, and meaningful responsibility that AI can support, not replace. For metrics, move beyond task completion. You could use qualitative feedback through 360-degree reviews focused on collaboration and problem-solving. You could also track an employee’s progression from “requires supervision” to “can work autonomously” on complex, ambiguous tasks—that’s a direct measure of growing confidence and capability.
When used intentionally, AI can strengthen professional development rather than replace it. Can you provide a concrete example of an early-career task that could be redesigned? How would AI handle the busy work, while the intern focuses on developing creativity, problem-solving, or client interaction skills?
Absolutely. Let’s take a classic early-career task: compiling a market research report. Traditionally, an intern would spend 80% of their time manually gathering data, formatting spreadsheets, and finding sources. That’s the busy work. In a redesigned role, an AI tool could do all of that in minutes, surfacing key data points and identifying market trends. This frees up the intern to spend their time on higher-value activities. Their new task becomes interpreting the AI’s output, developing a strategic narrative from the data, and creating a compelling presentation for the client. They could even role-play the client presentation with a mentor. In this model, AI handles the “what,” while the human focuses on the “so what” and the “now what”—developing critical thinking, creativity, and the ability to influence others.
What is your forecast for early-career development over the next decade?
My forecast is that we’re at a critical inflection point. Companies that continue to prioritize short-term efficiency by simply automating entry-level work will face a severe leadership crisis within a decade. They will have a workforce that is technically competent but strategically fragile. However, the organizations that thrive will be those who embrace their role as builders of people. They will use AI not to eliminate opportunities but to enrich them, creating more space for the human skills that truly drive innovation. The real competitive advantage won’t come from having the best technology, but from designing a work environment that intentionally helps people grow into confident, capable, and resilient professionals.
