A recent exchange about job applications highlights a subtle but important shift many recruiters are beginning to notice: the growing presence of AI-assisted writing in personal statements. What once served as a window into a candidate’s voice, judgement, and communication skills is becoming, in some cases, a more polished—but potentially less authentic—reflection of their abilities.
At first glance, the use of AI in applications feels like a natural extension of established practice. Candidates have long been encouraged to seek feedback, proofreading, and guidance from others before submitting an application. From that perspective, using AI tools to refine language or structure is not inherently problematic; it may even help level the playing field for those less confident in written communication. For support staff roles especially, where attention to detail and clarity matter, presenting a well-articulated statement can be viewed as a positive.
However, the concern arises when AI shifts from being a support tool to a substitute for genuine expression. As noted in one example, there can be a disconnect between a candidate’s demonstrated level of language proficiency and the fluency of their written statement. This creates a risk that selectors are evaluating an artificially enhanced version of the candidate rather than their authentic capability. In roles where communication is a key competency, this misalignment can lead to poor hiring decisions and subsequent performance challenges.
The central question, then, is not whether AI should be allowed—because, at present, there is little basis for prohibiting it—but how its use can be managed in a way that preserves fairness and integrity in the selection process.
One practical suggestion might be to include a simple declaration within the application form asking candidates to confirm whether AI tools were used in preparing their personal statement. This would not necessarily need to be framed as a restriction, but rather as a transparency measure. The aim would be to normalise responsible use while giving recruiters valuable context when reviewing applications. Candidates who have used AI appropriately are unlikely to be disadvantaged by such a question, while those who rely on it excessively may pause to reflect on how their application represents them.
Alongside this, there may be a need to refine how personal statements are assessed and prompted. If AI tends to produce polished but generic responses, then designing application questions that explicitly require personal, experience-based examples becomes increasingly important. Clear instructions—such as asking candidates to describe specific situations, actions they personally took, and outcomes achieved—can make it harder to rely on generic AI-generated content. This aligns well with existing best practice in recruitment, and is almost always the case with teaching and leadership roles, but it can be harder for some school support roles.
Another complementary approach is to ensure that the personal statement is not the sole measure of communication ability, even in the early application stage. Incorporating elements such as an email exchange, telephone screening or short, timed written task before inviting a candidate to interview can provide a more rounded and authentic view of a person’s communication skills. These stages naturally reduce the impact of pre-prepared AI-generated content and allow recruiters to validate what has been presented in the application.
Ultimately, AI in recruitment is not a problem to be solved but a development to be managed. Like any tool, its impact depends on how it is used. By encouraging transparency, refining assessment methods, and placing greater emphasis on authentic, experience-based responses, schools can and will adapt without losing the integrity of their processes.
In that sense, this is less a disruption and more an evolution—one that invites recruiters to rethink not just what candidates say, but how we ask them to say it.
Lucy Makins
