Is Artificial Intelligence Really as Impartial as We're Led to Believe During the Recruitment Process?

AI-powered recruitment is on the rise. After a recent IBM survey revealed that 42% of businesses are now introducing AI screening to improve recruiting and human resources, it’s no surprise that AI in the hiring landscape has become a topic of conversation.

Artificial intelligence is redefining the way we recruit and onboard employees. From CV screening to automated interviewing, the opportunities for integrating AI into modern-day hiring strategies appear endless.

The question is: just how beneficial is AI in mitigating bias in the hiring process? As one of the age-old challenges faced by hiring teams, prejudice and bias still play out in the recruitment industry.

Conscious and unconscious bias are products of a human-based hiring process. The introduction of AI screening technology and other automated recruitment software aims to put a stop to the prejudices that unfairly influence hiring decisions, in turn, creating a more diverse workforce.

Or does it? If AI systems learn from the data that hiring teams input, are they really as impartial as we’re led to believe during the recruitment process? Let’s find out.

The UK’s Push For AI-Powered Recruitment

There’s no doubt that the UK is continuing to push for an AI-powered recruitment scene.

With approximately 3 in 10 UK employers currently using AI to enhance their recruitment strategy, it is becoming increasingly common to encounter AI screening tools at the first hurdle of the application process.

In 2025, just over half of those investing in AI for recruitment use the technology for candidate sourcing, 44% for candidate interview and selection, and a further 29% for screening candidate applications.

In fact, 8 million UK recruitment workers are currently at risk of being replaced by AI in 2026.

While the UK’s push for automated recruitment aims to save teams time, money, and effort, could the switch to AI hiring bots help or hinder recruitment transparency and ethics?

Why AI in Recruitment Can Be Biased

Speaking to the BBC, Hilke Schellmann, US-based author of the book " The Algorithm: How AI Can Hijack Your Career and Steal Your Future”, claimed:

"One biased human hiring manager can harm a lot of people in a year, and that's not great. But an algorithm that is maybe used in all incoming applications at a large company… that could harm hundreds of thousands of applicants."

AI is the key to streamlining your recruitment process, but it does come with ethical risks that shouldn’t be ignored:

Historical Data Bias

Did you know that an AI system learns from your past hiring decisions?

If your business is known for only accepting a specific employee profile, this historical bias will be filtered into the AI algorithm, causing it to learn from those biases and make the same choices.

Take Amazon, for example. In 2018, the e-commerce giant scrapped its own AI-powered screening tools after discovering they were biased against women.

Trained on more than a decade of male-focused employment contracts, the AI-powered screening tech penalised female applications as a result.

Lack of Diverse Data

Most businesses invest in AI-powered hiring to diversify their workforce. However, if the dataset used to train the AI-screening tool is based on current company data, it may be difficult to represent all target groups accurately.

For example, if you’re opening up your recruitment drive to a global talent pool, but have only hired locally in the past, your system may perform poorly or inaccurately for underrepresented groups.

This can also be the case for other attributes such as education, race, age and disability based on a business's inadvertent embedded biases.

For example, Workday received a lawsuit in 2023 after its AI-based applicant screening system discriminated against thousands of applicants based on their age, race and disabilities. Driven by Derek Mobley, a Black job seeker over age 40 with a disability, an inquest found that the AI technology had a distinct algorithmic and feature selection bias.

Proxy Discrimination

Even when businesses take time to remove sensitive data from their AI systems, like gender, race and background, sometimes AI tools can still use proxy variables to make the same discriminatory decisions.

We’re talking about anything from postcodes to employment gaps. While many of these factors could be understood in context by a human recruiter, AI systems could correlate them with protected characteristics and make assumptions based solely on data.

Without human interaction, AI-powered hiring tools are unable to dig deeper and could reject an application based on something as simple as a spelling mistake or an employment gap due to caregiving/personal challenge.

The Key to Mitigating Bias

According to Sandra Wachter, professor of technology and regulation at the University of Oxford, "Having AI that is unbiased and fair is not only the ethical and legally necessary thing to do, it is also something that makes a company more profitable."

"There is a very clear opportunity to allow AI to be applied in a way so it makes fairer, and more equitable decisions that are based on merit and that also increase the bottom line of a company."

To reach this stage, businesses must reduce their reliance on AI and work alongside it instead.

The benefits of AI in recruitment are unmatched, but the key to creating a solid strategy is to prioritise human oversight, train on diverse data, and remain transparent with your applicants.

Recruiters must apply critical thinking when reviewing candidate applications and not just rely solely on AI-generated recommendations.

Conducting regular bias audits is also essential to ensure that your recruitment tool is in line with anti-discrimination laws in the UK.

Finally, just be upfront with your candidates. Let them know that AI is at play during the hiring process. This immediately builds trust and allows job seekers to appeal the rejection of their application if they feel they were unfairly screened.

Businesses that strike the perfect balance between AI and human involvement will create an unbeatable recruitment strategy that attracts the best talent from lots of different talent pools.