AI efficiency is raising the bar for entry-level jobs

AI may be changing white-collar hiring in a way that does not show up as a broad jobs collapse, Fortune reported. The strain is showing first in entry-level work, where employers increasingly want junior staff who can use AI tools and exercise skills once associated with more experienced workers.

Fortune business editor Nick Lichtenberg wrote that two economic ideas help explain the split: the lump of labor fallacy and the Jevons Paradox. The first rejects the idea that an economy has a fixed amount of work; the second holds that when a resource becomes cheaper or more efficient, total use can rise.

Legal software firm sees AI changing tasks, not whole jobs

Wolters Kluwer, the Dutch information services company that sells AI-powered software to law firms, recently applied both concepts to legal work, according to Fortune. The company said AI is letting lawyers spend more time on strategy, counseling and judgment-heavy work, rather than cutting the size of legal teams.

Wolters Kluwer said legal employers increasingly want junior professionals who already know how to work with AI. Those workers are expected to check AI output, oversee workflows and apply professional judgment to the material the systems produce, Fortune reported.

The company also said AI performs better on isolated tasks than on full professional assignments. Citing its internal research, Wolters Kluwer said AI produced professional-quality work on individual tasks roughly 50% to 60% of the time across roles, while its success rate fell to about 2% on complete end-to-end projects.

Fortune reported that this pattern supports a view of AI as a tool for completing parts of work rather than a replacement for entire jobs. Apollo Global Management chief economist Torsten Slok has regularly invoked the Jevons Paradox to argue that AI could increase demand for labor, and Dario Amodei referred to the concept in May while softening earlier warnings about AI-driven job losses, according to Fortune.

Data shows pressure on the first rung

The same framework helps explain why young workers are having trouble getting started, Fortune reported. The publication said the entry-level job market is at its weakest point in 37 years, with entry-level roles across professional services down 29% since January 2024.

Fortune also reported that finance and information services, which have long served as major hiring channels for college graduates, have lost an average of 9,000 jobs a month since 2023. Before the pandemic, those sectors were adding an average of 44,000 jobs a month.

A Stanford study found employment among workers ages 22 to 25 in occupations heavily exposed to AI has fallen 13% since 2022, according to Fortune. Amodei had previously warned that AI could wipe out about half of entry-level white-collar jobs within five years before later walking back that prediction, Fortune reported.

PwC has described the shift as “seniorization,” according to Fortune. In its 2026 AI Jobs Barometer, based on more than 1 billion job postings, PwC found that entry-level roles in highly AI-exposed occupations are now seven times more likely to require skills that typically appeared later in a career, including strategic decision-making, leadership, stakeholder management and judgment.

Fortune framed the result as a labor market where companies still need experienced professionals, while the training ground for future professionals is shrinking. Wolters Kluwer sees AI expanding what clients expect from firms; PwC’s data suggests the workers asked to meet those expectations are being pushed to arrive with more advanced skills from the start.

This story draws on original reporting from Fortune.