A feature published in The Times and shared on Facebook by Richard Anim has reignited debate over how artificial intelligence is reshaping the structure of work, particularly at the early stages of professional careers.
According to the report, written from the perspective of a former Microsoft AI executive, the impact of AI is becoming most visible not in senior roles, but in entry-level positions that have traditionally served as the starting point for careers in sectors such as finance, law, and accountancy.
The article argues that these roles; graduate analyst positions, junior legal work, and trainee accounting functions, have historically acted as “apprenticeship layers,” allowing young professionals to build experience through structured, routine tasks. However, it suggests that many of these functions are increasingly being automated or absorbed by AI systems capable of performing similar tasks faster and at lower cost.
Citing developments across major firms, the piece notes reductions in graduate intake and a decline in junior-level hiring in some professional services firms, pointing to a shift in how organisations structure their workforce pipelines. It references examples including KPMG, where UK graduate intake has fallen by 29%, Deloitte by 18%, and EY by 11%, alongside a reported 44% year-on-year drop in accountancy graduate job adverts in the UK and a near one-third decline in entry-level job postings since the emergence of ChatGPT.
The central concern raised is not necessarily that careers are disappearing, but that the “entry door” into these careers is narrowing. If AI systems take over much of the routine work traditionally assigned to beginners, the question becomes how new entrants are expected to gain the experience needed to progress within those fields.
At the same time, the article frames the broader labour market transition as one of restructuring rather than collapse. Drawing on projections from institutions such as the World Economic Forum, it notes that while certain roles are being displaced, new categories of work are also emerging, particularly in AI-related fields, data systems, and human–machine interface roles.
However, it highlights a potential mismatch: many of the emerging roles require technical exposure or advanced skills, while the traditional entry points that once provided gradual skill-building are weakening.
The feature also introduces a broader framework of “AI-resistant careers,” suggesting that roles requiring emotional intelligence, physical skill, ethical judgment, and complex human interaction, such as healthcare, education, skilled trades, and diplomacy, are less exposed to automation in the near term.
Yet the underlying concern remains structural. If early-career professional roles are reduced or reshaped significantly, the pathway into high-skill industries may become less accessible to new entrants without alternative training routes.
For students and parents, the implication drawn from the piece is not to abandon traditional career paths, but to recognise that the way people enter those careers is changing. Increasing emphasis is placed on AI literacy, adaptability, and interdisciplinary skills as new baseline requirements rather than optional advantages.
The broader question the report raises, however, is whether artificial intelligence is quietly reshaping not only what people will do in future economies, but also how they will enter the world of work in the first place.
