AI is creating a leadership crisis, and our race for efficiency is to blame

Business leaders have been asking the wrong question about AI. While we constantly debate whether AI will eliminate jobs, we’re overlooking a much greater risk: the disappearance of the apprenticeship model that builds our future leaders, writes Ashok Govindaraju.

For decades, junior employees learnt the ropes by doing the foundational, often tedious work.

Analysts in banks reconcile data between different teams and systems and produce analysis on Excel sheets. Accountants tally figures and books. Fresh recruits in marketing build competitor decks to learn about strategies.

None of this is glamorous, but it teaches new graduates how a business truly operates, lessons they would never learn in a textbook.

With a staggering 84 per cent of Australian knowledge workers already using generative AI at work, the crucial training ground that builds skills and experience gradually is now disappearing.

With AI drafting the first analysis, correcting the data, and building the initial presentation, our junior team members are thrown straight into quality assurance and synthesis.

They are expected to show judgement earlier, but without having built it or only half living the situation.

And this leaves businesses at risk of creating future leaders who have never been trained to do the groundwork.

A common belief is that AI will free us from tedious work, with some predicting a future where robots run an entire department.

At Fujitsu, where we sit between technology and business transformation, we see this paradox firsthand.

The reality is that most enterprises still run on a tangled spaghetti of legacy systems: decades of SAP/Oracle and custom platforms wired together through fragile integrations.

AI can help speed up individual tasks, but it does not dismantle 50 years of accumulated technical debt.

If anything, transformation projects have become larger and more complex.

AI is changing the experience of our work by automating repetitive tasks. As a result, the manual repetition that graduates once cut their teeth on is evaporating.

What remains is what AI can’t replicate: making nuanced judgement calls, navigating stakeholder trade-offs, and applying industry context.

The annual survey of the Australian Association of Graduate Employers consistently finds that when hiring graduates, Australian companies value “soft skills” like communication, teamwork, and problem solving, far more highly than technical knowledge.

Yet, the AI-driven automation of entry-level tasks is destroying the very apprenticeship model that builds it.

This creates a two-speed reality.

Legacy-heavy firms may still need hands on deck to manage the transition, but tech-first firms and consultancies already see the effects: project teams are smaller, more senior, and require juniors to perform at a level that once took five years to reach.

Most companies will hover uncomfortably between the two.

So, how do we collectively avert this leadership crisis and architect the new model of apprenticeship?

The key is to shift our focus from chasing efficiency to deliberately cultivating the human skills AI can’t replicate.

Even in the most AI-saturated future, some fundamentals stay human:

Trust: Leaders still want water-tight, deeply considered advice they can trust.

Problem definition: Defining and framing a problem in unique ways and angles is a deeply human skill. AI can optimise, but only within a box.

Context: Industry politics, regulatory nuance, and organisational culture are not easily reduced to what a large language model can spit out.

What organisations need to focus more on is how we can produce collective value, bringing everyone along together so that technology benefits us collectively, not just organisations and shareholders.

Business leaders need to build the new proving grounds. This means creating safe, simulated environments where junior staff can tackle complex problems, fail safely, and learn from the experience. It requires structuring mentorship programs where seniors explicitly narrate their decision making logic.

Secondly, schools, universities and training institutions will need to help students develop skills of critical thinking, synthesis, and “red-teaming” AI outputs to spot errors and hallucinations that can derail a strategy.

Finally, the corporate ladder will now be shorter, steeper, and less forgiving. New professionals must own their development. They need to attend important meetings to observe, ask senior leaders why they decide, and look for rapid, constant feedback.

AI isn’t killing graduate work. It’s transforming it. By freeing graduates from routine, it empowers them to drive strategic innovation.

Businesses not adapting to this transformation will be left behind, facing inefficiency, talent attrition, and a loss of competitive edge in an AI-driven world.

Ashok Govindaraju is vice president and partner at Uvance Wayfinders – Consulting by Fujitsu.