AI hiring filters, "digital native" wording and age discrimination at work in Great Britain

Age is the protected characteristic that AI hiring tools touch most directly. Date of birth and graduation year are easy fields to filter on, experience bands can cap applicants at a number of years, and job adverts generated by AI can ask for "recent graduates" or "digital natives". Age is also the one characteristic where the Equality Act 2010 lets an employer justify direct discrimination, so the rules work a little differently.

The short answer: age is a protected characteristic, and people share it if they are in the same age group, defined by a particular age or a range of ages (s5). Treating someone less favourably because of age is discrimination unless the employer can show it is a proportionate means of achieving a legitimate aim (s13(1)-(2)); the same justification test applies to indirect age discrimination (s19(2)(d)).

What the characteristic covers

• Age group: a group of persons defined by reference to age, whether a particular age or a range of ages (s5(2)). "Under 30", "over 50" and "people born in the 1990s" can all be age groups.
• Sharing the characteristic: people share it if they are in the same age group (s5(1)(b)).

Direct and indirect age discrimination

• Direct (section 13): less favourable treatment because of age. Unlike other characteristics, the employer can defend it by showing it is a proportionate means of achieving a legitimate aim (s13(2)). See direct discrimination.
• Indirect (section 19): a rule applied to everyone that puts an age group at a particular disadvantage, unless justified on the same test (s19). See indirect discrimination.
• Harassment (section 26): unwanted conduct related to age with the effect set out in section 26 is covered too (s26(1); s26(5)).

Specific exceptions for pay based on length of service, national minimum wage age bands and enhanced redundancy pay are explained on age exceptions at work.

Where AI tools come in

• Date of birth and graduation year filters: screening out applicants by date of birth applies age directly. A graduation-year filter can work as a stand-in for age, and is at least a criterion that puts older applicants at a disadvantage.
• Experience bands: a maximum number of years' experience can disadvantage older applicants; a minimum can disadvantage younger ones. Either needs a reason linked to the job.
• AI-written adverts and prompts: wording such as "recent graduate", "young and dynamic team" or "digital native" can signal a preference for an age group, and a screening prompt built on it can apply that preference.
• Retirement and succession flags: a workforce planning tool that flags people for exit or succession because they have reached a particular age treats them differently because of age, and the employer would need to justify it under section 13(2).
• Training and promotion models: models that rank "potential" from career stage or years to retirement can carry age into who is offered training or promotion.

Justification in practice

The Act does not list legitimate aims. An employer relying on one has to show that using age, or a criterion linked to it, was a proportionate way to achieve that aim. Questions to ask: what is the aim, does the criterion actually serve it, and could a criterion that does not depend on age, such as a skills test, meet it instead?

Practical steps

• Employers: remove date of birth and graduation year from screening, review experience caps and AI-generated advert wording, and record the aim and reasoning for any age-linked rule that stays.
• Candidates and workers: keep the advert and any rejection, note fields the form required such as date of birth or graduation year, and ask what criteria were applied.

For time limits and proof, see time limits and the burden of proof; for the Act's other workplace rules, AI and the Equality Act 2010.

This page covers Great Britain and is general information on the law as at 2 November 2026, not legal advice.