AI perspectives: what future for recent graduates?

AI to replace juniors?

Over the past year, thanks to improving outcomes from generative models, AI usage has become more widespread and faster-moving than anyone expected. The pace of change has surprised many.

In many firms, routine tasks often entrusted to juniors—simple, repetitive, labor-intensive—have been among the first to be automated, while senior colleagues retained oversight and final review.

This trend affects project governance (project managers), functional experts, and technical teams (developers). Senior staff still handle vision, framing, design, and management; juniors were often doing meeting minutes, drafts, initial code, etc. But now transcripts are fully automated; junior support is less needed or is shifting; developers don’t always have to write each line of code themselves.

Even professions requiring long academic training feel the effects. In an era of transformation, what role can and should we offer to young professionals? How do we harness their skills and energy in a changing world?

Acceleration and automation: levers to reverse the trend

Let’s look back 25 years: when the Internet emerged, similar fears arose. Just as with earlier tech revolutions, AI need not substitute human beings, but instead can be a partner in thinking, creating, and executing.

Arguments against it are familiar:

• it delivers a ready-to-use result;

• it sometimes makes errors or “hallucinates”;

• it might seem to reduce the need for certain human tasks.

But like the internet did, AI can also enable new jobs, new skills, new ways of working.

Key foundational knowledge (e.g. mathematics, logic, critical thinking) remain essential. The risk is delegating everything to the machine. Instead, we can use AI to speed execution — freeing humans to do higher-value work (design, strategy, creativity, oversight, quality control).

Onboarding, training, and AI as coach

AI can shorten learning curves. In many service environments, learning to handle applications, processes or frequent cases took months or years. Now, AI can assist, guide, suggest, and reduce the time to reach autonomy.

Juniors can use AI as a personalized coach when senior experts are not always immediately available. This can help them become productive faster.

In some contexts (maintenance, repeated incidents, support tickets), AI can retrieve past solutions quickly, allowing juniors to tackle and resolve issues earlier in their career than was previously possible.

Rethinking work organisation and processes

Rather than automating old patterns, we can rethink the workflow: which tasks actually need senior input, which can safely be entrusted to juniors (with AI support), and which should be redesigned altogether.

Younger generations — often more comfortable with digital tools, more experimentation-oriented — can lead the transformation. They can challenge established practices, propose new workflows, shorten steps, or remove unhelpful friction.

They can also help support more hesitant colleagues: sharing tools, best practices, demonstrating prototypes, and encouraging adoption.

New opportunities and jobs: prompting, hybrid roles, fusion of skills

While it’s risky to make firm forecasts, several emerging patterns are already visible:

• Prompt engineering / prompting expertise: In professional contexts, asking the right questions or framing the right instructions for models is itself a skill. Juniors often are quicker to master and experiment with these tools.

• Hybrid roles: As technology becomes more accessible and abstracted, the boundary between functional and technical tasks may blur. Some developers may spend less time writing raw code and more on configuration, architecture, logic, or supervision. Functional consultants may increasingly implement rather than just specify.

• The separation of roles (client needs → spec → implementation → review) may gradually shift or compress as AI handles parts of the chain more directly.

Yes, AI may reduce some traditional junior tasks. But it also opens new paths. The key question is: how to adopt AI so as to improve the daily work environment, accelerate learning, and enable younger professionals to shine.

If the reflex was initially to reduce the number of juniors, in many transformation programmes the experiments show the opposite: early adoption, pairing juniors with AI, and involving them in the change process can deliver value.

In short: the future need not be bleak. With the right strategies, AI can become a powerful ally rather than an adversary for young graduates.