Traditional recruiting software waits for a person to click a button. In an agentic setup, an AI agent is given a goal and a set of permitted actions, then works through the steps itself. For example, an agent assigned to a warehouse role might notice new applications overnight, score each CV, invite suitable applicants to a voice screening and have an updated shortlist ready when the recruiter logs on.
The appeal is speed and coverage at volume, since no applicant waits days for someone to open the inbox. The risk is losing sight of what the agent did and why. Good practice keeps the boundaries clear: agents handle repeatable tasks, every score comes with its reasoning, actions are logged, and people decide who progresses, who is interviewed and who is hired.