Hiring faces a growing trust challenge. Artificial Intelligence is transforming recruitment at a staggering pace. For many talent acquisition teams, AI is no longer a future concept – it's becoming essential infrastructure. It helps manage applications, answer candidate questions, support screening, schedule interviews, and improve efficiency across increasingly complex hiring processes.
Yet there's an uncomfortable question the industry needs to confront:
Could AI become the face of rejection in modern recruitment for candidates?
For Early Careers recruitment, this challenge could be particularly significant.
The perfect storm
Today's graduates are the first generation to enter the workforce having grown up alongside digital technologies and AI during adolescence.
In fact, research shows many already use AI to improve CVs, prepare for interviews, write applications and research employers according to Prospects Luminate Early Careers Survey 2025 and 2026 Early Careers Survey. Both highlight a striking truth: that AI is becoming a normal part of how students and graduates navigate the job market.
At the same time, AI is making it easier than ever to apply for jobs. Applications that once took hours now take minutes. As TA leaders, as a result of this lowered barrier to entry to complete job applications, that application volumes are exploding and ever increasing.
One of Wilson’s Early Careers clients receives more than 80,000 applications globally, with more than 99% of these candidates being rejected – the majority at the very early stages before speaking with a human. This means many TA functions are increasingly becoming rejection engines rather than selection functions.
Even if every applicant is talented, most will not receive an offer or even a phone call. That creates a challenge: when candidates are unsuccessful, where do they direct their frustration?
The risk: "The AI rejected me"
Historically, rejection was viewed as the outcome of competition. Tomorrow, it may increasingly be viewed as the outcome of technology.
Gartner research in 2025 highlights a significant trust gap:
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Only 26% of candidates trust AI to evaluate them fairly.
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32% worry AI may wrongly reject them.
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25% trust employers less when AI is used in candidate evaluation.
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Yet 39% of candidates are using AI themselves during the application process
A 2025 Prospects' Early Careers survey found graduates are embracing using AI themselves for CVs, applications and interview preparation, but expect employers to be transparent about how AI is used in hiring.
This contradiction is fascinating. Candidates are happy to use AI as an assistant, but many are much more hesitant when employers use AI to assess them. The issue is not necessarily the technology itself.
The issue is trust.
Addressing the "applications black hole" problem
The UK Government's 2026 Young People and Work Interim Report identifies what it calls the "applications black hole" as a major source of frustration for young people entering the workforce. The report highlights growing concerns around labour market detachment, with many young people describing challenges navigating application processes and gaining access to opportunities.
For candidates, the experience often looks like this:
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Submit application.
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Receive automated acknowledgement.
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Complete online assessments.
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Complete a recorded interview.
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Wait.
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Receive rejection.
When little feedback is provided, candidates fill in the gaps themselves.
Increasingly, one of those assumptions may become:
"An algorithm rejected me."
Whether that's true or not may become almost irrelevant. Perception becomes reality.
Will candidates request non-AI selection routes?
It is entirely possible, particularly in graduate hiring where competition is intense and rejection rates are high.
We may begin to see more requests for:
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Human review guarantees.
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Alternative assessment routes.
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Greater transparency around screening.
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Accessibility exceptions.
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Clear explanations of how AI is used.
Neurodivergent candidates may raise these concerns even more strongly, particularly regarding fairness and accessibility.
So what should we do?
The answer isn't to remove AI. Volumes are not decreasing, and in a world where we are being asked to do more with less, increasing headcount isn’t an option.
The answer is to build trust.
1. Be transparent
Candidates should know:
Uncertainty creates suspicion. Transparency creates confidence.
2. Keep humans in the decision loop
AI should support decisions, not make them.
This is a legal requirement in many countries/regions to ensure it’s humans that are rejecting candidates, not AI.
3. Design AI-resilient assessments
The discussion should move beyond: "How do we stop candidates using AI?" to: "How do we assess capability in a world where everyone uses AI?"
Assessment design increasingly needs to focus on:
Rather than simply testing information recall and response articulation.
4. Provide better feedback
The less feedback candidates receive, the more likely they are to assume technology was responsible for the outcome.
Even limited feedback can significantly improve trust and perceived fairness.
The real challenge ahead
The debate is often framed as:
"Will AI replace recruiters?"
The more important question may be:
"Will candidates trust recruitment processes that use AI?"
Early Careers hiring is uniquely exposed because it combines huge volumes, highly competitive selection, and a generation that both embraces and questions technology.
The reality is that AI can make recruitment more efficient, consistent and scalable.
However, efficiency alone does not create trust.
As rejection rates rise and AI adoption accelerates, employers that can clearly demonstrate fairness, transparency and human oversight will be best placed to attract and engage the next generation of talent.
Because in the future, the organisations that succeed won't be the ones that simply use AI.
They'll be the ones candidates trust to use it responsibly.
