NYC’s AI Bias-Audit Law Doesn’t Reach India Yet — Don’t Wait For It To

New York City’s Local Law 144 already requires any employer using automated hiring software on NYC-based candidates to publish an independent bias audit before deploying it. India has no equivalent statute — not yet, and maybe not for a few years. That gap isn’t safety. It’s a countdown, and most Indian HR teams running high-volume AI screening are spending it as if the clock isn’t running.

The law that isn’t here yet

Local Law 144 requires bias-audit results to be published and candidates to be notified when an automated tool is used to help decide who advances. It’s narrow — it only binds NYC-based hiring — but it set a template that other jurisdictions are copying. The EU AI Act classifies hiring AI as “high-risk,” which triggers mandatory risk-management and human-oversight obligations under Article 6. None of these reach an HR team in Pune or Coimbatore. But the direction is unambiguous: wherever AI makes or materially influences a hiring decision, regulators are moving toward requiring someone to explain that decision on demand.

The clearest signal of what happens when nobody can explain it is Mobley v. Workday — the first major AI-hiring discrimination case to reach this scale in US courts, alleging that an automated screening tool disproportionately filtered out older applicants. The lawsuit isn’t about whether AI screening is inherently good or bad. It’s about what happens when a company can’t produce a clear account of why the algorithm did what it did.

Why “no law yet” isn’t the same as “no exposure”

Here’s the number that should make Indian HR teams sit up regardless of what the law says today: when we ran a pilot with HyperVerge across their campus hiring funnel, our AI voice screening auto-rejected 60%+ of candidates before a human ever looked at a resume. Across the pilot, we logged 1,099 completed interviews. In one single evening, we screened 3,000 candidates for one drive in under two hours.

Those numbers are the entire pitch for AI screening — and they’re also exactly the numbers a regulator, a candidate’s lawyer, or your own legal team would ask you to explain if a rejected applicant complained. When 6 out of every 10 candidates never make it past an algorithm, “the AI decided” is not an answer. It’s an admission that nobody can answer.

This isn’t a hypothetical. Campus hiring in India runs at a scale where a single role can draw thousands of applicants, and adoption of AI in HR is accelerating fast enough that “we don’t have a law for this yet” is a temporary comfort, not a strategy. The Indian HR teams that build audit habits now, before any law forces them to, will not be scrambling when one arrives. The ones who wait will be retrofitting explainability onto a year’s worth of decisions they can no longer reconstruct.

What audit-readiness actually requires — and it’s not much

You don’t need a law, a compliance team, or new software to start. You need three things, and most HR teams screening at volume already have the raw material for all three:

• A record of the criteria, not just the outcome. If your screening process decides communication ability matters more than resume keywords, write that down before you run the drive, not after someone asks.
• A sample review habit. Pull 20–30 auto-rejected candidates every drive and have a human check whether the rejection reasoning holds up. This is cheap insurance against the version of this story where nobody checks until a lawsuit forces it.
• A rejection reason you could say out loud to the candidate. Not a technical score, a sentence. If you can’t produce one, that’s the gap to close before you scale the drive further, not after.

None of this requires slowing down. It requires treating the audit trail as part of the screening process, not a compliance afterthought bolted on when a regulator eventually asks. Our own audit-trail practices for HR and legal teams came out of exactly this pressure — not from a law, but from knowing the question was coming eventually.

The take

Waiting for India to pass its own Local Law 144 before building explainability into your screening process is a bet that the law will arrive after you need it, not before. Given how fast AI adoption in Indian HR is moving, that’s not a safe bet. Build the habit now, while it’s cheap, instead of retrofitting it later under legal pressure.

Curious how audit-ready your current screening funnel actually is? Talk to us about what a 60%+ auto-reject rate looks like when it’s fully explainable.