Harvard Business Review has published an essay whose headline pulls no punches: "AI Has Broken Hiring. Here's How to Fix It." The title itself is the signal — a mainstream management publication now frames artificial intelligence in recruitment not as an efficiency gain but as a force that has damaged the hiring process itself, and one that employers must actively repair.

For HR leaders, the framing matters. The argument, announced in the piece's title, positions AI as something that has already disrupted core people processes — screening, evaluation, candidate selection — rather than as a tool awaiting careful adoption. That shifts the question for talent acquisition teams from "should we add AI to hiring?" to "what has AI already done to our hiring funnel, and what do we need to fix?"

The article promises a repair plan. The title's "Here's How to Fix It" signals that the authors move beyond diagnosis to prescription — an approach HR Dive and HR Executive readers will recognize as a shift in the AI-at-work conversation, which has spent the past two years focused on adoption roadmaps, vendor selection and governance checklists.

What the headline implies for employers

Harvard Business Review does not typically run alarmist titles about workplace technology. When it states that AI "has broken" a function as central as hiring, it reflects a growing body of concern among researchers and practitioners that automated recruitment tools — resume screeners, chatbot filters, algorithmic ranking systems — have degraded outcomes for both employers and candidates.

The practical implication for people-process decisions is direct. Employers that deployed AI screening or matching tools in recent years may need to audit those systems' actual performance: Are qualified candidates being filtered out? Has the volume of automated applications, some generated by AI on the candidate side, made traditional funnels unworkable? The title suggests the problem is systemic — an arms race between employer-side algorithms and candidate-side AI — rather than a matter of any single tool performing poorly.

The "fix" framing also implies employer obligations. Where hiring processes fail candidates, employers face not just talent-quality risk but compliance and reputational exposure. Regulators and plaintiffs' attorneys have increasingly scrutinized automated employment decision tools, and a process the authors describe as "broken" is one that employers cannot simply leave in place.

A shift in the AI conversation

The publication of this piece marks a turn. Coverage of AI in hiring through 2023 and 2024 centered on productivity gains, bias mitigation and emerging rules such as New York City's Local Law 144. A 2025-era Harvard Business Review headline declaring hiring "broken" suggests the discourse has moved to remediation.

For CHROs, the actionable takeaway from the article's premise is a set of capability questions rather than product questions: Can your organization measure whether AI has improved or worsened hiring outcomes — time-to-fill, quality-of-hire, candidate completion rates? Do you have visibility into where in the funnel automation makes decisions? And do your processes still work when candidates use AI as heavily as your recruiters do?

Questions employers should be asking now

The article's title alone gives HR leaders a checklist worth acting on:

• Audit the funnel end to end. If hiring is broken, employers first need to locate the break — in sourcing, screening, assessment or interview scheduling — before assigning cause.

• Measure candidate-side AI effects. The premise of a "broken" process implies both sides now use AI; employers need data on application volumes, duplicate or AI-generated submissions, and screening pass rates.

• Rebuild processes for the new equilibrium. A "fix," as the title promises, likely means redesigning hiring workflows rather than layering another tool on top of existing ones.

• Treat governance as repair work. Companies that cannot explain how their hiring AI makes decisions will struggle to defend those decisions — to candidates, to auditors and potentially to regulators.

The road ahead

Harvard Business Review's decision to frame the problem in the past tense — AI "has broken" hiring, not "might" — sets the terms for how management thinkers will discuss recruitment technology going forward, and HR leaders should expect the article's proposed fixes to shape both internal expectations and external scrutiny of their hiring practices.