AI for recruitment agencies

CV parsing with a person deciding

Reading CVs is the most obvious job for AI in recruitment, and one of the most useful. An agent can read applications in any format, pull out skills, employers, dates and qualifications, and log them consistently in your ATS. It can then compare each candidate with the role and show why they look like a match or not.

What it shouldn’t do is make the final call on its own. We build screening so a recruiter reviews the shortlist and the reasons, and decides who goes forward. That’s better recruitment, because good candidates with unusual CVs don’t get filtered out by a keyword. It’s also the simplest way to stay within the rules on automated decisions.

UK GDPR and automated decisions

The rules changed with the Data (Use and Access) Act 2025. The old near-ban on solely automated decisions has been replaced with a set of safeguards. Where a decision with a significant effect on someone is made without meaningful human involvement, people must be told, be able to challenge it and be able to ask for a person to review it. Stricter limits still apply where special category data, such as health information, is involved.

The ICO has focused on recruitment in particular. In its March 2026 statement on automated decisions in hiring, it asks employers to “test regularly for biased outputs”, to “be clear with candidates if ADM is being used and explain how it works”, and to tell candidates how to challenge a decision and request a human review. Its draft guidance on automated decision-making was consulted on until May 2026, with the final version expected later this year.

Keeping a recruiter in charge of each decision avoids most of this. Where clients want more automation, we build in the notices, logs and human review routes the rules call for. We handle the technical side; your compliance decisions stay with you.

ATS and CRM integration

Agencies run on their ATS, whether that’s Bullhorn, Vincere, JobAdder, Firefish or something else. The value of AI depends on getting data in and out of it cleanly. We connect through each system’s interface, so parsed CVs, call notes and shortlists land in the right record, and nothing is overwritten without a person approving it.

Most ATS products now include some AI features of their own. If those do the job, we’ll say so. A custom agent earns its place when work crosses systems, such as email, LinkedIn, your ATS and a client’s portal, or when you want screening and outreach done your agency’s way.

Fair screening and bias checks

AI learns from data, and recruitment data can carry old biases. A model that ranks candidates by similarity to past hires can quietly favour the same backgrounds again. We test screening tools against real roles before they go live, look for patterns in who gets ranked lower, and keep the reasons for each ranking visible so recruiters can spot when something looks wrong.

We also help agencies explain their use of AI to candidates in plain words, which the ICO expects and which candidates increasingly ask about. The ICO’s Recruitment rewired work is a useful read on where this is heading.

Candidate data

Agencies hold a lot of personal data, much of it collected years ago. AI can help clean it up by flagging records past your retention period, finding duplicates and preparing consent refresh emails. For the AI itself, we use business accounts that don’t train on your data, or private AI for agencies that want candidate data kept entirely in-house.