UK Employers Cut 36% of Entry-Level Job Recruitment, Partly Due to Increased Use of AI and Automation Technologies
A survey of 1,001 companies in the UK shows that 36% of employers have reduced entry-level positions aimed at young people over the past year, partly due to increased use of AI and other automation technologies.
The contraction is most pronounced among medium and large enterprises: 48% of medium-sized companies and 46% of large companies have reduced entry-level positions, compared to 24% for smaller businesses; nearly half of large employers report that their total number of job vacancies is lower than a year ago.
Among small businesses, 24% of respondents say AI and automation have reduced the available positions; the corresponding proportions for medium and large enterprises rise to 58% and 60%, indicating that organizations with higher technology budgets and standardized processes are quicker to use automation to cut entry-level jobs.
73% of employers believe that it is harder for young people to find jobs now than it was five years ago. The survey was conducted by Survation for the Lancaster University Work Foundation from May 7 to 20, and the conclusions reflect the judgments and hiring behaviors of the surveyed employers, which do not solely prove that each job cut is entirely due to AI.
The most directly affected positions are those focused on repetitive, regularizable, and digital tasks, such as basic administration, customer support, data processing, entry-level analysis, routine content production, and some entry-level programming jobs. AI does not necessarily eliminate entire jobs but can first replace modular tasks, allowing companies to achieve the same output with fewer entry-level employees working alongside senior staff and automation tools.
In market mechanisms, companies will shift their hiring budgets towards AI software, process automation, and a few senior employees who can supervise agents and bear responsibility for outcomes; the supply of entry-level labor increases, and competition for jobs intensifies. Beneficiaries include AI suppliers, automation integrators, and workers with domain experience and AI tool capabilities; those under pressure are job seekers lacking demonstrable projects, industry knowledge, and manual review capabilities, as well as traditional organizations that rely on a large number of entry-level positions to cultivate talent.
Source: Public Information
ABAB AI Insight
It is not surprising that entry-level positions are the first to be compressed, as they have long been responsible for "low-risk, repetitive tasks + learning curves": organizing materials, writing drafts, conducting basic tests, entering data, and responding to standard questions. In the past, companies used these tasks to train newcomers, but now some tasks have been taken over by AI agents and automated workflows, allowing companies to assign work that was originally distributed among multiple entry-level employees to a few senior employees for review in the short term. The capital path shifts from labor costs to software, computing power, and process restructuring. Medium and large enterprises report a higher proportion of job reductions due to AI and automation, not only because of stronger technology but also because they have larger budgets to purchase enterprise software, clean data, build permission systems, and transform processes. While small businesses also use general AI tools, they have less capacity to embed them into full-chain operations, resulting in a lower proportion of entry-level job cuts. Historically, this is similar to how ATMs reduced cash handling tasks for bank tellers, ERP systems compressed backend data entry, and cloud services lowered the threshold for basic operations: in the early stages of technology, standard steps are usually eliminated first, followed by changes in how organizations configure newcomers. The difference with AI is that it simultaneously covers text, code, analysis, and customer communication, thus more broadly eroding "apprentice tasks" in traditional white-collar professions; if companies stop hiring newcomers, they will face a gap in the supply of mid-level talent in a few years. This falls under technological substitution. AI does not first replace top-level decision-makers but rather consumes entry-level tasks that can be clearly described, quickly reviewed, and have low error costs. The mechanism is that the output of entry-level employees typically requires review by senior personnel, whereas AI can generate similar drafts at extremely low marginal costs; thus, companies raise the experience threshold for newcomers, shifting training costs onto schools, job seekers, and freelance projects. This will tighten the cycle of "no experience means no opportunity to gain experience." ABAB News · Cognitive Law
- AI first replaces apprentice tasks, then raises entry barriers.
- When drafts become cheap, review capability becomes a new professional asset.
- Companies reduce training costs, leading to increased employment friction in society.