The current landscape for early-career roles is mixed. Overall entry-level hiring in major professional services firms has dropped sharply from the post-pandemic high, with graduate intakes at the largest accounting and consulting groups falling to about 2500 positions, down from almost 4700 at their recent peak. This drop reflects employers trying to recover from big technology investments and pausing to see exactly where new skill gaps emerge as AI tools bed in. At the same time, application data from graduate job platforms shows that while the number of employer-led graduate recruitment campaigns is holding roughly steady year on year, unique applicants for these programmes are climbing, which means more people are now competing for a similar volume of roles.
Inside those campaigns, the nature of opportunity is starting to shift. In several industries, employers are beginning to treat the latest graduates as “AI natives” who have used generative tools throughout their studies, often for research, coding assistance or data analysis. Instead of slotting them into repetitive entry-level work, some organisations are moving these hires more quickly into tasks that involve workflow redesign, automation and experimentation with AI-enabled processes. Recruiters in the technology and broader professional services sectors report that leading employers see strong value in pairing these AI-comfortable graduates with senior staff who hold deep domain expertise, using cross-generational teams where younger hires prototype with AI and experienced professionals guard quality, ethics and risk.
This evolving model looks set to reshape what “graduate work” means. Employers in competitive fields are increasingly promoting the idea that new hires will do meaningful and visible work from day one, not just back-office support. To make that promise sustainable, many are adjusting selection criteria. Academic results still open doors, but hiring teams now put more weight on communication, collaboration, adaptability and curiosity than on narrow, specific experience. With AI tools making it easy for applicants to polish CVs and cover letters, recruiters are seeing a rise in applications that look impressive but feel generic, so they are hunting for clearer signals of real capability. They look for things such as sustained commitment to sports clubs, student societies, creative projects, part-time ventures or other “side quests” that show initiative and problem-solving in the real world.
For graduates, this shift brings both opportunity and pressure. Those who can combine AI fluency with people skills and tangible extracurricular achievements appear to move faster into strategic or high-impact work than previous cohorts. However, the competition is intensifying and cultural fit now runs in both directions. Graduates are more selective about where they apply first, while employers face a harder battle to stand out as places where AI-literate talent can grow, experiment and feel aligned with organisational values. Over the next few years this balancing act between cautious headcount planning, ambitious AI adoption and changing expectations on both sides looks likely to decide which organisations attract the strongest new entrants and which graduates get the fastest track.
