3. Ready for a job that keeps changing?
A carefully managed digital profile may help a young person reach the recruitment process. They can still find themselves excluded by another poorly explained expectation: that they should already be ‘job-ready’.
The signal: Entry-level candidates are increasingly expected to use AI confidently, challenge its output and show commercial judgement. Yet many employers continue to use previous experience as the main evidence that someone can do these things.
This creates an obvious difficulty. A school leaver or graduate may be familiar with generative AI without understanding its limitations or the risks surrounding data and accuracy. Equally, they cannot arrive with the professional judgement that develops through seeing decisions made at work and learning from their consequences.
Victoria Knight, chief people officer at Node4, says employers need to stop expecting young people to arrive as the finished product. Recruitment should look for how someone approaches an unfamiliar problem, what information they question and whether they can explain why they changed course.
Why it matters: If employers define ‘job-ready’ as already having experience and confident judgement they shift the burden of development onto young people before giving them access to work. That favours candidates with family networks, internships and the financial freedom to take poorly paid opportunities while excluding others who may have equal or greater potential.
It also creates a business problem. Organisations need people who can learn quickly and use AI responsibly, but previous experience is an increasingly weak proxy for either. Recruitment that continues to screen for yesterday’s version of the role may miss the people best equipped to grow into tomorrow’s.
What’s really going on: The meaning of ‘job-ready’ is shifting as AI takes over some of the routine activity previously given to junior employees. Preparing basic research or checking figures may have been repetitive but it also helped people recognise mistakes and understand what good work looked like.
Dr Vijayakumar Parameswaran Unnithan describes the risk through the example of a consultant who once had to wrestle with a difficult brief before finding a way through it. AI can now produce several frameworks before she has properly encountered the problem. The output may improve while the capacity built through that struggle weakens.
Young people can reasonably be expected to bring curiosity, communication skills and evidence that they can learn from. Employers have to provide the role knowledge, feedback and exposure through which sound judgement develops.
One recruitment change could help. Replace at least one experience requirement in every entry-level job with a direct assessment of reasoning. Give candidates an AI-generated recommendation and ask what they would check, what seems to be missing and when they would seek help. This shows how someone thinks without demanding knowledge they could only gain after being hired.
The leadership question: Does your definition of ‘job-ready’ describe what a young person needs to begin learning or what you hope they will become after several years in the role?
👉 Read the full story to explore how employers can assess potential more fairly and rebuild early-career learning as AI changes the work available to beginners: What does ‘job-ready’ mean when AI is changing entry-level work. 5-minute read
I’m taking a short break from the Digest now and will be back in September. I’ll still be sharing new stories and podcast episodes on LinkedIn so do keep an eye out there. Wherever the next few weeks take you I hope you find some time to pause, recharge and enjoy a change of pace.
Find your quiet space!
Siân
Editorial director, The People Space
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