AI has been a buzzword in the recruitment industry for a while now. Don’t worry, it can’t do the recruiters’ job! What it can do is help us enhance our processes, work with a larger amount of data and focus on important tasks. There are many things that AI tools can assist us with, but today we want to talk about candidate matching and reducing bias.
Firstly, we need to discuss why problems with candidate matching and bias might arise during the hiring process. Candidate matching in recruitment is often limited by resume filters and keyword-based screening, which can miss out on skilled candidates just because their resumes don’t match specific terms or formats. Recruiters may also rely too much on “gut feelings” during interviews, making it harder to objectively match candidates to job roles.
Bias in recruitment happens when recruiters, often unconsciously, favour candidates based on things like name, age, gender, or background. This can lead to a lack of diversity, as candidates who don’t fit a certain mould are overlooked. Biased language in job descriptions can also discourage certain people from applying. Altogether, these biases make the hiring process less fair and can result in missing out on qualified talent.
How to improve a candidate matching process with AI?
AI tools can improve candidate matching by moving beyond simple keyword searches to analyze candidate skills, experience, and potential more holistically. These tools use machine learning to evaluate candidates based on data, matching them to roles based on skillsets rather than just resume keywords.
For example, tools like HireEZ or Eightfold.ai scan profiles and rank candidates based on relevant skills, even if they use different terminology. This makes matching more accurate and consistent, helping recruiters find strong candidates who might otherwise be overlooked due to resume formatting or non-standard language.
How to reduce bias with AI?
AI can reduce bias by anonymizing candidate data and focusing on objective factors like experience, qualifications, and performance metrics.
Tools like Harver assess behavioural traits without taking into account demographic factors, while HireVue and Rival anonymize initial candidate information, ensuring that early screening decisions are based purely on skills and fit rather than age, gender, or background.
Additionally, AI-powered writing tools such as Textio help craft inclusive job descriptions that appeal to a broader audience, helping attract diverse applicants from the start.
By using these AI tools, companies can make hiring more objective and equitable, ultimately leading to more diverse and qualified teams.
As an International Talent Acquisition Consultancy and Recruitment agency, Global M always tries to stay on top of the latest trends and test new tools that can help with the recruitment process and candidate experience. Our industry will always need a human touch, but we suggest our employees and clients be open to new technology and solutions.
