Klarus survey points to junior AI opportunity

Senior technology decision-makers in UK and Irish mid-market companies are more likely to report artificial intelligence improving junior employees’ work or creating opportunities than removing entry-level roles, according to research from Klarus.

The survey found that 45% of respondents said AI was enabling junior staff to do their jobs better or more quickly, while 24% said it was creating new roles and opportunities. The figures describe executives’ assessment of AI’s effect inside their organisations rather than measured changes in employment.

The research was conducted in May and June 2026 among 500 senior decision-makers at mid-market businesses in the UK and Ireland. Companies in the sample had annual revenue between £200m and £2bn and employed between 300 and 3,000 people. Respondents held responsibility for, or influence over, technology decisions across both IT and wider business functions.

The talent findings sit within a broader picture of widespread AI deployment but mixed implementation. Almost three quarters of respondents, 73%, said their organisations had partially or fully deployed AI. Among companies that had explored the technology, however, only 10% said every initiative had successfully progressed beyond pilot stage.

Expertise remains one of the obstacles. Lack of AI expertise was cited by 48% of respondents who had explored the technology as a reason projects failed to progress beyond pilots, while 39% identified building internal expertise as a priority for the coming 12 months. Governance and data quality were also repeatedly identified as constraints on deployment.

That gap between adoption and execution complicates predictions about junior work. Automating a routine task does not necessarily mean the associated role disappears. It can change the work expected from the employee, particularly where organisations still need people to check outputs, apply judgement, work with customers or combine information from several systems.

The survey cannot establish whether entry-level hiring is rising as a result. It records the views of senior decision-makers, not vacancies, payroll movements or the experiences of junior employees. Other evidence has shown employers reducing some entry-level recruitment as artificial intelligence and automation alter the economics of routine work.

The two trends can coexist. A business may recruit fewer people into highly repetitive roles while placing greater value on junior employees able to use AI effectively. In that environment, the change is not limited to headcount. It affects what constitutes an entry-level job and which skills employers expect at the beginning of a career.

That creates a training question for companies deploying the technology. Junior employees have traditionally developed judgement through repeated exposure to lower-risk work before progressing to more complex decisions. If AI absorbs part of that workload, employers have to consider how employees gain the underlying knowledge needed to identify weak outputs and know when automated recommendations require challenge.

Governance therefore becomes part of workforce development. Clear rules about where AI can be used, how outputs are checked and which decisions remain subject to human review affect both operational risk and the way employees learn their roles.

Klarus’s findings suggest many mid-market organisations are confronting those questions before their AI programmes are fully mature. The effect on junior work is likely to depend less on whether AI is present than on how companies redesign roles, supervision and training around it.