Entry-level job opportunities for the nation's youth are contracting sharply across Western economies, with UK data revealing a 31.9% fall in vacancies between November 2022 and mid-2025. This precipitous decline signals a systemic economic shift, as artificial intelligence tools increasingly augment tasks traditionally performed by new entrants to the workforce, displacing younger generations from foundational career paths.
The Disappearing Ladder
Adzuna, a firm tracking millions of job listings, reported a sharp contraction in entry-level hiring in the UK. Vacancies fell by 31.9% between November 2022 and mid-2025. Over the same period, the share of entry-level jobs in the overall labor market declined from 29% to 25%. These patterns suggest AI's initial labor market effects are emerging through hiring patterns and weaker demand, rather than large-scale job losses, and are more noticeable among younger workers.
In the United States, technology and finance firms are slowing the hiring of entry-level analysts, programmers, and support staff. This reduction occurs as AI tools augment research, drafting, and coding tasks. US Bureau of Labor Statistics data released in February 2026 showed that 181,000 jobs were added to the US economy over the course of 2025, a significant reduction from 2.0 million in 2024. This modest rate of job growth occurred while real GDP growth remained robust, indicating a structural shift beyond typical economic cycles.
Australia is experiencing similar trends, with employment growth for junior white-collar occupations lagging behind broader labor-market growth. This pattern predates recent AI developments but is now being accelerated. Over the past decade, employment in these roles has increased at roughly half the pace of total employment growth, reflecting both recent AI developments and earlier waves of automation.
Elite-Driven Transformation
Deloitte Access Economics’ latest Employment Forecasts report outlined that AI’s largest employment impacts are likely to be in roles defined by routine automatable tasks that do not always require the application of human soft skills. These include a range of clerical and information processing occupations. The scale of AI’s impact on these roles and others will ultimately depend on how organizations adopt the technology.
The critical next step, according to the report, is the shift from organic, individual AI experimentation to enterprise-wide integration. Most AI use remains informal, but some organizations are beginning to implement the technology at scale. Companies in the US and UK are slightly further along the AI adoption curve than Australia, providing an indication of what may come next for the Australian workforce. The analysis, authored by David Rumbens, a Partner at Deloitte Access Economics, targets CFOs and workforce planners, framing the future of work through an elite corporate lens.
Future of the Nation's Youth
Deloitte Access Economics has analyzed which age groups are most exposed to AI-driven disruption in Australia. The findings indicate that younger workers are overrepresented in occupations perceived to be at risk. In November 2025, workers aged 15–24 made up 22.9% of employment in AI-disrupted roles, compared with 15.2% of overall employment. Despite their higher exposure, the overall data does not yet point to AI reducing demand for younger workers in Australia, reinforcing the idea that Australia is further behind on the AI adoption curve.
Looking ahead, Deloitte Access Economics expects employment growth to diverge across occupation groups. Community and personal service workers, trades workers, and many professionals are forecast to see robust demand. Conversely, AI-exposed professions, managers, clerical and administrative staff, and sales workers may see softer demand. The article concludes that AI-driven workforce change will be a labor market feature over the next few years, with workforce decisions grounded in real adoption patterns, operational needs, and sector-specific developments rather than broad headlines or speculation.