AI in FM recruitment is changing both sides of the hiring process. Employers are using it to source and sift candidates more efficiently. Candidates are using it to improve CVs, tailor applications and prepare for interviews.
Neither development is inherently a problem. A candidate who uses AI to communicate their experience more clearly may still be exactly the person an organisation needs. The challenge begins when a polished application is mistaken for proof of capability.
That tension came through clearly at a recent Boden Group roundtable with FM and Talent professionals. Participants had seen candidates pass initial screening with strong AI-assisted applications, only for gaps in practical knowledge to emerge later.
Their conclusion was not that employers should try to detect or prohibit every use of AI. It was that assessment needs to work harder.
Finding genuine FM capability still takes market knowledge, careful assessment and human judgement. Our FM specialists combine that expertise with access to a network of over 125,000 professionals, helping you identify candidates with the skills and experience to succeed.
For years, a well-written CV has acted as a useful first indication of communication, attention to detail and career understanding. Generative AI weakens that signal because almost anyone can now produce a professionally written application that mirrors the language of a job description.
This can be positive. Candidates who have relevant experience but weaker writing skills may be able to present themselves more fairly. Career changers and people who are unfamiliar with recruitment conventions can explain transferable experience more effectively.
But the same tools can make an applicant appear more knowledgeable or precise than they are. Keywords, confident language and technically credible answers may reflect the quality of the prompt rather than the candidate’s independent understanding.
The result is an uncomfortable truth for employers: a stronger application no longer necessarily indicates a stronger candidate.
AI screening tools generally look for evidence that matches predefined criteria. This can be useful when employers receive hundreds of applications, but it can also place too much weight on keywords, job titles and the presentation of a CV.
Strong FM candidates do not always follow a predictable career path. Someone may have gained valuable operational experience in another sector, progressed without formal qualifications or have the right transferable skills without using familiar FM terminology.
If screening criteria are too narrow, these candidates may be rejected before a recruiter or hiring manager has the opportunity to consider their potential.
This reflects Information Commissioner’s Office guidance on automated recruitment, which stresses the importance of meaningful human involvement, transparency and monitoring recruitment technology for unfair bias.
The question for employers is therefore not simply whether AI can identify suitable applicants. It is whether the process also allows people to recognise the relevant capability that AI may miss.
If CV presentation is becoming less reliable, employers need assessment methods that reveal how someone thinks and performs. For FM roles, that does not require an elaborate selection process. It does require greater connection between the assessment and the work.
A candidate might be asked to prioritise competing maintenance issues, respond to a client scenario or interpret a simple set of performance data. They could also explain how they would approach a service failure.
For technical and specialist roles, a short monitored task can reveal far more than another round of general interview questions.
Structured follow-up questions are equally important. Asking what assumptions a candidate made, why they chose a particular approach and what they would do differently makes it harder to rely on a prepared answer. It also gives candidates space to demonstrate judgement rather than presentation skills alone.
Participants also valued genuine face-to-face conversation. This should not be treated as a guarantee of authenticity or an answer to bias. Used alongside clear and consistent criteria, however, it can help employers understand how someone communicates, builds trust and responds when the conversation moves beyond a rehearsed answer.
Our Client Solutions team can help you review your hiring process and identify the skills, evidence and assessment methods that will reveal genuine capability.
AI can now write job adverts, rank applications and suggest interview questions. But the roundtable view was that AI is more likely to change the recruiter’s role than replace it.
This matters particularly in FM, where similar CVs can hide significant differences in practical knowledge, judgement and suitability for a particular environment.
AI can make recruitment faster, more accessible and easier to manage. Candidates should not be penalised simply for using tools that employers are also adopting. But employers must stop treating a polished application as evidence that someone can do the job.
The strongest response is not an arms race to detect AI use. It is a hiring process that asks candidates to demonstrate the judgement, knowledge and behaviours the role requires.
AI in FM recruitment will continue to develop. As presentation becomes easier to automate, genuine capability becomes the signal that matters most.
At Boden Group, we combine specialist FM market knowledge with a people-led approach to help employers look beyond the CV and identify candidates with the capability, judgement and experience to succeed. If you are reviewing how you attract, assess or hire FM talent, we can help strengthen your approach.
