On average a recruiter will go through 250 CVs for each job listing, where there is also only a 17% chance an individual’s cover letter will be read. With the rise in redundancies and companies experiencing a reduction in their budget to use towards hiring and training new candidates, leads to many recruiters and HR experts having less time to go through hundreds of CVs, thereby resulting in using AI technology to help in the process. 

Research suggests 48% of UK recruitment agencies use some form of AI technology when hiring candidates. This could be in the form of Application Tracking Systems (ATS), where recruiters use the software to collect all the CVs and scan them for keywords and experiences in order to pick the right candidates to go forward for an interview. 

Yet, AI-driven recruitment tools may unintentionally discriminate against older candidates, primarily because these systems are often trained on historical data that may reflect biassed hiring practices or criteria. A recent survey by Totaljobs has highlighted how there is already age discrimination against over 50s who are searching for a new job, where they found one in seven (15%) candidates over 50 have been rejected from a job explicitly due to their age. 

As some recruiters are still showing signs of age discrimination during the hiring process, some experts believe this could be affecting the AI algorithms which are currently used when scanning CVs.

Matthew Vohs, Founder and CEO of O50C and V&C, has highlighted the use of AI during hiring processes and how it might also be having an effect on those aged over 50 being chosen for certain jobs based on the previous hiring data of the employer. 

He’s found some of the key reasons why Artificial Intelligence is having an impact on age diversity in the workplace.

AI model may favour younger employees in their search

When recruiters use AI tools to go through CVs and streamline talent, it can sometimes use AI algorithms that follow past data which often prioritises candidates with certain work histories or skill sets. Even in the most subtle ways, some algorithms may filter out candidates based on gaps in employment or previous roles deemed “outdated,” which can disproportionately impact older applicants who may have different gaps due to various life events. Following previous hires in a business’s database, may mean the AI will look for more technical keywords based on more ‘modern’ digital skills and certain job titles which favour younger candidates. 

The impact of ATS on older candidates

A common AI tool many recruiters use which is deemed a popular one to be able to streamline talent is the Application Tracking System (ATS), this is particularly useful for recruiters to use when there is a large volume of CVs and it is able to filter through candidates by focusing on keywords in each industry. Due to the criteria set by the recruiter, there tends to be keyword biases in ATS systems that often overlook experiences or skills relevant to older professionals. For example, in the IT and computer science sector some of the keywords include; MATLAB, matrix, software development and software development life cycle. A recent survey by Totaljobs found that 15% of candidates over 50 report age-related rejection during job applications. This report provides insight into how age bias manifests even without AI, if this is already taking place amongst recruiters then AI could replicate such patterns if trained on biassed historical data​.

The Rapid Growth in digital skills poses a risk of job displacement for older workers

Around 7.5 million people in the UK lack the essential digital skills that are needed for the workplace. 18% of those people are adults who do not have the skills or abilities that are needed to gain work in the digital sector. This may also affect older candidates who are applying to roles in the digital and technology sector due to the fact AI has the potential to reinforce age bias in the hiring process from the patterns learned from biassed training data. This means that some AI tools which are used to screen CVs are filtering out candidates who have a skills gap or no recent qualifications in that industry, despite any qualifications they already have. With fewer companies actively considering older workers for tech-heavy roles, this then contributes to a perceived lack of interest from older workers in AI-driven positions, when often they just need more training​ within the digital sector. 

Matthew Vohs, said: “It is no surprise to see the power and influence of AI is now being used for recruitment purposes, as advanced technology has made a positive impact across many industries. Over the years we’ve seen many talent acquisition teams have their budgets reduced, which means there’s now a smaller team of recruiters to go through a higher volume of job applications per job listing, this is where AI can come in and reduce their screening time by 75%. 

“However, I urge all employers and hiring teams to be transparent about how these algorithms are trained and what data they rely on. More companies and businesses, especially in sectors we are seeing an increase in skills shortages, should regularly carry out audits on their AI systems to detect and mitigate age bias, making it more likely for the hiring process to ensure fair outcomes. If more employers could factor in looking into their algorithm criteria, this could show that age inclusivity needs to be more of a priority for organisations. 

“As more of the older generation come out of retirement to continue to work, means more employers need to have strategies in place to help in retaining these employees and offering them support. Having AI recruitment systems that are age-inclusive benefit the entire workforce and ensure we are actively promoting age diversity and fostering a collaborative and inclusive work environment.”