AI has made job applications easier – but is public sector recruitment paying the price?

Applying for a job has arguably never been easier. With generative AI, candidates can tailor applications in seconds and submit them by the dozen in a single sitting – even if they’re not qualified for the role.

The number of LinkedIn job applications has surged by around 45% year-on-year, with up to 11,000 applications now submitted per minute on the platform, driven in part by widespread use of AI tools.

But for many employers, particularly those in the public sector, that convenience is creating a new kind of pressure, and the systems designed to manage applications are struggling to keep pace. What was once a challenge of attracting talent is fast becoming a challenge of processing it.

The growing ease of applying for roles is therefore exposing a deeper tension within public sector recruitment: how to maintain fairness and quality in a system that is now operating at a very different scale.

Public sector systems are under siege

Our Salary Guide data shows that 59% of public services organisations see recruiting the right talent as their biggest external challenge, and rising application volumes are making that even harder. As AI shifts candidate behaviour from selective applications to high-volume submissions, recruitment teams and hiring managers are forced to process more applications in less time, without any guarantee of better hiring outcomes.

AI-generated CVs and responses are often polished, well-structured, and optimised for applicant tracking systems (ATS) – and increasingly similar. Hiring managers are faced with large volumes of candidates who appear equally qualified on paper, making it harder to identify genuine capability. Moreover, a rise in fraudulent applications requires an extra layer of diligence when screening, and risks overshadowing those from genuine jobseekers.

For public sector organisations built on principles of fairness, transparency, and consistency, this shift is particularly significant. Public sector hiring processes were designed to ensure equal opportunity and rigorous assessment – not to filter thousands of near-identical applications at speed.

The result is slower hiring timelines, increased pressure on hiring teams, and delayed delivery across critical services.

The rise of the AI hiring arms race

A further challenge is the dual adoption of AI across the hiring process. While more candidates are using AI to optimise applications, this is often in direct response to the increasing number of employers using AI to filter them. This AI “arms race” is creating a system where both sides are continually having to adapt around the technology – rather than their actual skills, requirements or ambitions.

Candidate disillusionment and employer administrative burden are not the only consequence though. If both candidates and employers rely heavily on AI, confidence in the authenticity of the entire application process can decline. Gartner predicts that by 2028, up to one in four job applicants could be fake – a scenario that disadvantages both sides.

However, it could be the case that certain groups have even more to lose. The AI hiring arms race risks creating a two-tier candidate market, where those who can optimise with AI rise to the top, while those less likely to use it are filtered out before their potential is recognised.

What this means for public sector employers

The proliferation of AI tools has turned the tables on early-stage hiring, with public sector organisations feeling its impacts more keenly than most. But there is an opportunity to rethink recruitment processes, and how AI is used to ethically support growing workload.

When applied thoughtfully, AI tools can reduce administrative burden, improve candidate matching and mitigate bias. The key is ensuring these tools complement rather than overwhelm, or even undermine, existing processes.
 

1. Use AI to prioritise, not decide

AI is most effective when augmenting human decision-making, not replacing it. Use it to help identify critical skills, flag risks, or highlight patterns, but retain human oversight and review. Moreover, any AI implementation should be done in a controlled manner, with a clear understanding of which hiring challenges these tools can augment, piloting their use in specific tasks, and adhering to robust compliance and data measures.
 

2. Build in smart checkpoints

Adding targeted steps, such as role-specific questions or timed assessments, can reduce low-intent or automated applications while preserving fairness and a positive candidate experience. Structured assessments, task-based evaluations, and work simulations are harder to optimise through AI alone and provide a more reliable indicator of capability.
 

3. Don’t default to in-person, all the time

While in-person interviewing is an effective way of mitigating AI’s shortfalls, it’s equally important not to lean too far the other way and default to same-room interviews without exception. Doing so risks losing the benefit of understanding capability in hybrid, modern working environments.
 

4. Train hiring managers for AI

Layering on new AI-powered hiring tools is unlikely to guarantee a solution – it could even make it worse. AI capability is critical, but only 8% of public services organisations say they have full access to the right skills to leverage AI. Hiring managers must be equipped with guidance on managing AI-generated responses fairly, probing for depth in interviews, and assessing authenticity.
 

5. Be transparent with candidates

Public sector employers are already expected to be clear and consistent in how they hire. But as AI becomes more embedded in recruitment, transparency needs to go further. Candidates should understand where AI is used, what role it plays in decision-making, and where human oversight remains. That clarity helps protect trust, supports fairness, and strengthens the candidate experience.
 

6. Redesign for volume

AI has altered the way candidates engage with job opportunities, and it’s unlikely that the surge of applications – including those considered fraudulent – will decline any time soon. Rather than treating high volume as a temporary spike, redesign hiring processes to operate effectively at scale; whether that’s adapting workflow automation, improving triage models, or creating clearer role definitions.

A new hiring reality

Amid the rise of AI-assisted applications, there’s a risk that the human touch is being taken from recruitment. However, the need for human oversight in hiring is perhaps more important than ever, and nowhere is this truer than in the public sector. AI can be a powerful way to augment hiring at scale, but maintaining human attention to detail will set your organisation apart and increase the chances of finding the right person – rather than the right CV.

In a hiring landscape defined by disillusion and automation, organisations that can focus on genuine capability, and integrate AI ethically, will hire faster and hire fairer.

To ensure you’re finding the right people needed to drive your organisation, get in touch with one of our expert consultants today.