International Youth Day is meant to recognise the ambitions, contributions and potential of young people. But this year, it arrives against a global employment picture that is moving in the wrong direction.
Global youth unemployment rose to 12.4% in 2025, leaving around 67 million people aged 15 to 24 without work, according to new research from the International Labour Organization (ILO). More than 257 million young people are now not in employment, education or training. Youth unemployment increased across eight of the world's 11 subregions between 2023 and 2025.
At the same time, AI is adding another layer of uncertainty. The ILO estimates that 6.1% of jobs currently held by people aged 15 to 29 are in occupations most exposed to AI-related change. But exposure doesn't mean those jobs will disappear, and the ILO isn't predicting millions of AI-driven job losses.
The concern is more complicated. Young people are entering an already difficult labour market while some of the roles that have traditionally helped them gain experience are becoming scarcer. AI didn't create that problem, but it could accelerate the shift.
The Youth Employment Problem Started Before AI
It's tempting to look at falling entry-level hiring and draw a straight line to generative AI. The global picture doesn't support such a simple explanation. The ILO points to weaker economic growth, geopolitical tensions and sluggish job creation as pressures on youth employment. The problem also looks different depending on where young people live.
Youth unemployment reached 26.2% in the Arab States and 22.6% in Northern Africa, while North America saw its rate rise from 8.3% in 2023 to 9.8% in 2025. In low- and lower-middle-income countries, nearly nine in ten young workers are in informal employment, often without adequate labour or social protections.
But another change cuts across that picture. The ILO has identified a decline in middle-skilled clerical, administrative, sales and manufacturing jobs. These aren't simply another group of occupations losing ground. They've traditionally provided a route into employment for people leaving school or university.
Meanwhile, high-skilled employment in areas such as science, engineering, healthcare and IT continues to expand. The jobs may be there further up the skills ladder, but reaching them becomes harder if the lower rungs start disappearing.
AI is now changing many of the tasks found in those early-career roles, which makes it important to separate what we know from what we're still trying to understand.
AI Exposure Isn't the Same As AI Job Loss
The ILO's 6.1% figure describes jobs held by young people that sit in occupations with the highest exposure to AI-related change. It doesn't mean 6.1% of young workers are about to lose their jobs. The report offers a hypothetical scenario to show the potential scale of the risk.
If 10% of those highly exposed jobs disappeared completely, around 5.6 million young workers could lose work, change careers or leave the labour force. The ILO is clear that AI's long-term employment effects remain uncertain. There are also important differences between exposure, automation and displacement.
A job is exposed when AI can affect meaningful parts of the work. AI takes over specific tasks and you get automation. Displacement goes further and removes the need for the worker or the role itself. AI can also improve work by helping people do things faster, or by helping them do things they couldn’t do before — either because they didn’t know how or didn’t have the capacity.
So the more useful question isn't whether every exposed job will disappear. It's whether the employment prospects of young people in highly exposed occupations are already changing. There are early signs that they are.
The Early Signal Is Showing Up in Hiring, Not Mass Layoffs
Research into entry-level employment is starting to show a pattern that isn't necessarily visible in redundancy announcements. Stanford researchers examining millions of US payroll records have found declining employment among young workers in AI-exposed occupations, with the pressure strongest where AI is more likely to automate rather than augment human work.
Their wider research into early-career employment also suggests the effect is appearing through weaker hiring rather than companies simply replacing existing employees with AI. That changes how we need to think about AI displacement. A business doesn't have to announce thousands of AI-related redundancies to change the workforce.
It can simply hire fewer people when existing employees and AI systems can absorb work that previously justified another junior role. UK data offers another warning, although it also shows why caution is needed. Government analysis found overall UK hiring was down 14% year on year in April 2026, with entry-level hiring broadly tracking that wider decline.
However, 30 of the 38 entry-level occupations examined were shrinking, including accountants, graphic designers, software engineers and data analysts. Many of the sharpest declines were in information-processing roles where AI capabilities have grown quickly. The researchers explicitly warn that this isn't proof AI caused those declines.
Economic conditions, skills mismatches and greater competition for jobs are all part of the picture. Still, the emerging concern isn't mass unemployment caused by AI. It's whether fewer young people are being given the opportunity to enter particular professions in the first place.
When Entry-Level Work Changes, So Does the Route to Experience
Entry-level employees don't arrive with years of judgement and practical knowledge behind them. That's partly the point. Early-career work gives people exposure to customers, systems, colleagues, decisions and mistakes. They learn how a process works on paper, then discover all the situations where reality doesn't quite follow the process.
AI creates an unusual problem here because of the difference between codified and tacit knowledge. Codified knowledge can be documented, taught and stored in digital form. Tacit knowledge is what people pick up through experience, such as judgement, intuition and knowing what to do when the standard answer doesn't fit.
Generative AI is particularly capable of working with codified knowledge. Tacit knowledge is much harder to reproduce. Research examining AI and employment has therefore raised the possibility that the technology can substitute for some of the work performed by inexperienced employees while complementing experienced workers who already possess knowledge gained through years of practice.
PwC has identified another side of the same shift. Its 2026 Global AI Jobs Barometer found that AI-exposed entry-level roles are seven times more likely to demand skills traditionally associated with senior workers, including leadership and creativity.
Since 2019, openings for these “seniorised” entry-level jobs are up 35%, while other entry-level jobs are down 10%. This is a terrible loop to be in. Experienced workers are valuable to businesses because they have skills that AI can’t easily replicate. But young workers need a place to get that experience.
Whether AI breaks that route or changes it depends partly on how businesses choose to use the technology.
AI Can Remove the First Rung or Help Workers Climb It Faster
There isn't one inevitable future for entry-level work. Research from Strada Institute found that 2.7 times as many senior talent leaders expect AI to increase entry-level hiring in 2026 as expect it to decrease it. Some employers are using AI to reduce routine administrative work while shifting junior employees towards more analytical responsibilities.
That leaves enterprises with two very different ways to think about AI and early-career work.
AI as substitution
AI can absorb tasks previously handled by junior employees, allowing experienced workers to cover more work with fewer people. That can deliver an immediate productivity gain and reduce hiring requirements.
But if fewer people enter the organisation at the bottom, workforce planning eventually has to account for where the next generation of experienced employees will come from.
AI as capability
The alternative isn't to preserve repetitive work simply because junior employees have always done it. AI can remove low-value tasks while helping early-career workers contribute at a higher level sooner.
With mentoring, review and exposure to real decisions, young employees can spend more time developing the judgement and practical knowledge businesses actually need. The difference isn't whether an organisation automates. It's whether automation removes the development pathway along with the task.
The Workforce Question Enterprises Need to Ask Now
For enterprise leaders, the ILO's warning should broaden the conversation beyond how many roles AI can replace. Workforce planning also needs to account for what happens after work is redesigned.
What happens to the role after the routine work disappears?
Removing repetitive tasks can make an entry-level role more valuable. But if enough work disappears that the role no longer exists, the organisation also loses an entry point into its talent pipeline.
Where will tomorrow's experienced workers gain experience?
If AI takes over work people previously learned from, businesses need another way for employees to develop judgement, organisational knowledge and practical skills. Experience can't become a requirement that nobody gets the opportunity to acquire.
Are productivity decisions being measured beyond the next headcount cycle?
Hiring fewer junior employees can produce visible savings quickly. The effects on succession, recruitment and internal skills may take years to appear. For young workers, those decisions determine whether a changing labour market still offers a credible way into skilled employment.
For enterprises, they help determine whether today's productivity gains leave enough people ready to become tomorrow's specialists and leaders.
Final Thoughts: AI Shouldn't Break the Route From Novice to Expert
On International Youth Day, the ILO's 6.1% AI exposure figure will understandably attract attention. But the wider youth employment picture carries the more important warning. Young people were already struggling to enter secure work before generative AI became a serious workforce consideration.
AI is now changing some of the jobs and tasks that have traditionally helped people get started, without necessarily producing the dramatic wave of redundancies many expected. Enterprises don't need to preserve outdated roles or inefficient work to protect the old career ladder. They do need to consider what replaces each rung they remove.
Decent work for young people isn't only about how many jobs exist today. It's also about whether there is still a viable route into the skilled work economies and businesses will need tomorrow. The organisations that handle this transition best won't necessarily automate the least.
They'll find ways to use AI to shorten the journey from novice to expert without eliminating the journey itself. As the evidence around AI, skills and employment develops, EM360Tech will continue examining what those changes mean for the enterprises building the future of work.
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