AI in Recruitment: can employers use AI to shortlist candidates

AI in recruitment is becoming a key tool for businesses looking to improve efficiency and make smarter hiring decisions. From screening CVs to identifying top talent, this system is increasingly being used to streamline time-consuming recruitment tasks, allowing hiring managers to focus on the more human side of the process.

One of the most common questions employers are now asking if Artificial intelligence can be used to shortlist candidates? In this article, we’ll explore how AI is being used in recruitment, the benefits it can bring, and what employers need to consider before relying on it in their hiring process.

Can employers use AI in recruitment to shortlist candidates?

Yes, employers can use this system to shortlist candidates, but it must be done carefully and responsibly.

While Artificial intelligence can significantly speed up the shortlisting process and help identify suitable candidates more efficiently, it cannot be used as a completely hands-off solution. Employers still have a responsibility to ensure their recruitment processes remain fair, transparent, and compliant with legal requirements.

AI in recruitment should be used to support decision-making rather than replace it. Human oversight remains essential to review outputs, challenge decisions where needed, and ensure candidates are assessed on a fair and consistent basis.

GDPR

Organisations need to make sure they are handling candidate data properly, in line with UK GDPR. This means keeping information secure, using it for a clear and lawful purpose, and being transparent about how and why it is being used.

Under UK GDPR, candidates have the right to challenge decisions made solely by automated systems where those decisions have a significant impact on them, such as being rejected for a role.

This legislation sets strict rules around how personal data is collected, used, and stored. As AI in recruitment relies heavily on large volumes of data, including CVs, interview recordings, and potentially even information from online profiles, employers must take extra care to ensure they are handling this data lawfully and transparently.

To remain compliant, organisations should be clear about how Artificial intelligence is being used in their hiring process. You must ensure there is a lawful basis for processing candidate data, and maintain appropriate safeguards. It’s essential to include human oversight where required.

Risk of Discrimination

When it comes to shortlisting candidates, AI in recruitment may have some very real discrimination risks that employers need to be aware of.

Bias in training data

These systems learn from historical data. If past hiring decisions have favoured certain groups, the system can replicate those patterns. For example, if previous hires were predominantly male or from similar educational backgrounds, the AI may unintentionally prioritise similar profiles, disadvantaging others.

Indirect discrimination

Even if protected characteristics are not explicitly included, AI can still make decisions based on proxy data. Things like postcode, school attended, career gaps. Even hobbies can indirectly relate to age, race, gender, or socio-economic background. This creates a risk of indirect discrimination under Equality Act 2010.

Lack of transparency

It’s not always clear how decisions are made when it comes to artificial intelligence. If a candidate challenges a decision, employers may struggle to explain or justify why someone was rejected, increasing legal and reputational risk.

Over-reliance on automation

Relying too heavily on AI can remove important human judgement from the process. The tool may miss transferable skills, potential, or non-traditional career paths, which could disproportionately impact certain groups.

Inconsistent or flawed algorithms

If AI tools are not regularly tested and audited, they can produce inconsistent or biased outcomes. This is particularly risky if the system is updated or trained on new data without proper oversight.

Data quality issues

Poor-quality or incomplete data can lead to unfair decisions. For example, candidates with non-linear career paths or those returning from career breaks (such as maternity leave) may be unfairly screened out.

How to reduce the risk

To use AI in recruitment responsibly, employers should:

  • Keep human oversight in the decision-making process
  • Regularly audit AI tools for bias and fairness
  • Be transparent with candidates about how AI is used
  • Update your privacy policy on your website to explain how you are utilising Artificial intelligence in your hiring process
  • Provide an AI privacy policy
  • Ensure decisions can be explained and justified
  • Avoid using overly narrow or biased training data
  • Train your staff on how to use this software ethically
  • Create an AI policy for staff

AI should support your recruitment process, not replace fair and inclusive decision-making. Getting this balance right is key to avoiding discrimination risks while still benefiting from the efficiencies AI can offer.

Contact Us

Like any tool, AI in recruitment brings both opportunities and risks. While it can improve efficiency and help identify strong candidates more quickly, it’s important to fully understand how the technology works before building it into your hiring process.

Employers should be confident that any AI tool they use is transparent, fair, and compliant with current legislation. This includes understanding how decisions are made, what data is being used, and ensuring there is appropriate human oversight throughout the process.

As partners of Hireful, we work with systems that have been designed with these considerations in mind. Their AI shortlisting tools are built to support compliant, fair recruitment practices, helping you save time without compromising on quality or legal obligations.

If you have any questions about AI in recruitment, or anything covered in this article, our HR experts are here to help. Contact Us.

Collective Redundancy Changes: Employers Guide

Collective Redundancy Changes: Employers Guide

Collective redundancy changes are now in force, adding to the growing list of employment law reforms introduced through the Employment Rights Bill. With further updates expected throughout 2026 and 2027, it is becoming increasingly important for employers to stay...

Salary Sacrifice Schemes Redefining Employee Benefits?

Salary Sacrifice Schemes Redefining Employee Benefits?

Employee benefits have long played an important role in attracting and retaining talent. However, candidates are now looking for more than just a competitive salary. With many employees facing increasing financial pressure, employers are expected to offer benefits...

HR Services for Accountants: Supporting Business Growth

HR Services for Accountants: Supporting Business Growth

Professional services firms often operate in a fast-paced environment where balancing client demands, compliance, recruitment, and people management can quickly become overwhelming. This is especially true for growing accountancy firms that are expanding their teams,...

Fair Reasons For Dismissal: An Employers Guide

Fair Reasons For Dismissal: An Employers Guide

Under the Employment Rights Act 1996, there are five potentially fair reasons for dismissal. If you are reading this blog, you may be considering dismissing an employee and want to ensure you are handling the situation correctly. Before making any decision, it is...

Dismissal Due to Ill Health: Is It Ever Fair?

Dismissal Due to Ill Health: Is It Ever Fair?

Employees cannot automatically face dismissal due to ill health. However, in some circumstances, an employer may be able to fairly dismiss an employee on capability grounds where their health is affecting their ability to carry out their role. Before reaching this...

Conditional Offers of Employment: Can You Withdraw a Job Offer?

Conditional Offers of Employment: Can You Withdraw a Job Offer?

Many employers assume that making a conditional offer of employment means they can withdraw the offer at any time before the employee starts work. However, a recent Employment Appeal Tribunal (EAT) case highlights that this is not always the case. The case...