FutureHire's recruiters already used AI, but productivity had plateaued under admin, and a previous automation attempt had failed because tools were dropped in without redesigning the work or supporting adoption. The result: distrust, and private workarounds. The task wasn't more tools; it was a recruiter-controlled redesign people would actually trust, and, because this is recruitment, one that is fair and private by design.
Modelled under stated assumptions. The brief's bar is ≥40% less admin time and 50% faster candidate-summary prep, both cleared.
≈ 1.7 hours per recruiter per week, ~6× the engagement fee on the modelled assumptions. The percentages depend only on per-task time (directly measurable), so they hold even if the volumes are optimistic; dollar figures are an indicative value of reclaimed time.
A consistent, on-brand ad from a short intake, with an inclusive-language check that turns a fairness risk into a fairness feature.
Rough notes → a structured, evidence-only summary. Omits protected attributes, never scores or ranks, the recruiter decides.
A pipeline snapshot → a professional client update, confidential by default. The lowest-risk, fastest-confidence win.
Automated candidate screening is where recruitment AI does the most harm, so it's excluded here, deliberately. The AI drafts and documents; it never screens, ranks, shortlists or decides, and it's constrained to job-relevant evidence with no protected attributes. Candidate data stays in approved tools, and a recruiter reviews and sends everything. AI drafts · a recruiter decides · every candidate treated fairly
Because the last automation failed on trust, the rollout is sequenced to earn it: a six-person pilot proves the workflows, willing desks adopt next, then the firm standardises, with AI Champions, editable SOPs, Bullhorn configuration recommendations, and a benefits tracker that turns scenario estimates into measured results as the pilot runs.