Most HR leaders intend to use AI and many already do. But adoption isn’t the same as readiness.
With new rules and expectations landing across major regions over the next 12–24 months, the risk is simple: you scale what’s broken, not what works. This article keeps it practical (no legalese!) so you can get your organization AI-ready, quickly and safely.
The AI Act is law and phases in through 2026–27, with high-risk obligations applying from August 2026.
No single “AI Act.” Regulators apply principles (transparency, fairness, accountability) and have issued recruitment-specific guidance.
Adoption isn’t readiness. Being AI-ready means you can show where AI fits, who’s accountable, and the job-relevant reasons behind every decision, on demand.
Do that and compliance follows, while hiring gets faster, fairer, and more defensible.
Being AI-ready in hiring means you can answer five simple questions with confidence:
Listen to Matt Alder on The Deep Dive for straight‑talk, tips and predictions on the future of AI within your hiring process.
Job ads & comms: Use AI to draft at scale; humans edit for clarity and tone
AI-powered role profiling: Instantly generate role-specific success profiles that show you what ‘great’ looks like, aligning your team and shortlisting faster.
Scheduling & notes: Automate the back-and-forth and first-draft interview notes; recruiters review and approve.
Workflow nudges: Auto-send structured feedback forms, preliminary scorecards, and next-step reminders.
ATS orchestration: Keep clean “who-did-what-when” logs so audits and reviews are painless.
“The mistake… is [if] you’re applying those technologies to inefficient processes or broken processes.”
Score yourself “Yes / Sometimes / No.” If you have more than three “No” answers, prioritize a readiness sprint before expanding AI use.
“AI is accelerating rapidly and will impact jobs, careers and workplaces. We all need to ensure it is used responsibly and ethically.”
You don’t need a law degree to be ready; you need clarity, explainability and ownership. Start small, measure ruthlessly, keep humans on the hook, and publish what you can. Get your first “win” in 90 days, and then scale deliberately…
It’s being able to demonstrate transparent, explainable and fair use of AI in recruitment—with named human oversight, job-relevant reasons for decisions, and an audit trail that can be produced on demand. Local rules layer on top, but these foundations travel.
Publish a plain-English policy; require human review for adverse decisions; log reviewer name, rationale and any overrides; provide a candidate appeal route; and show sample logs. If you can’t explain a score in job-relevant terms, don’t deploy it.
Start with low-risk, high-volume admin: scheduling, irole profiling, interview notes/transcripts, structured candidate comms and workflow nudges, always with logs and human sign-off. Measure speed, quality and fairness; only then consider shortlisting support.
