AI Hiring Disclosure Laws Are Reshaping Recruitment Across North America

The AI hiring disclosure requirement comes from Bill 149 (Working for Workers Four Act, 2024), which received Royal Assent on March 21, 2024, and added Sections 8.1–8.6 to Part III.1 of the Employment Standards Act. The implementing regulation is Ontario Regulation 476/24, filed November 29, 2024. The law has been in force since January 1, 2026.

The requirement is straightforward in principle: every employer with 25 or more employees that uses AI to screen, assess, or select applicants for a publicly advertised job posting must include a disclosure statement in that posting. The regulation defines AI broadly as "a machine-based system that, for explicit or implicit objectives, infers from the input it receives in order to generate outputs such as predictions, content, recommendations or decisions that can influence physical or virtual environments" — language tracking the OECD framework.

This breadth is the source of the law's biggest compliance challenge. Multiple major law firms — Osler, Fasken, Hicks Morley — have flagged that employers may struggle to determine whether everyday recruitment tools (LinkedIn Recruiter features, ATS keyword matching, Workday's embedded scoring) fall within this definition.

Ontario's Information and Privacy Commissioner (IPC) and the Ontario Human Rights Commission (OHRC) have been more active. On January 21, 2026, they jointly released non-binding "Principles for the Responsible Use of Artificial Intelligence," covering validity, safety, privacy, human rights, transparency, and accountability. The OHRC has consistently criticized the legislation as too narrow — its February 2024 submission argued the disclosure requirement is "vague," fails to cover discriminatory AI-targeted advertising, and should mandate testing for human-rights compliance before deployment.

Quebec's Law 25 (formerly Bill 64), fully phased in by September 2024, represents the most substantive AI employment regulation currently in force in Canada. Its core provision, Section 12.1 of the Private Sector Act, governs decisions based exclusively on automated processing of personal information — meaning no meaningful human involvement.

When such processing occurs in hiring, the employer must: inform the individual no later than at the time of the decision; and on request disclose the personal information used, the reasons, principal factors, and parameters behind the decision, and the individual's right to correct data and submit observations for human review.

At the federal level, AIDA is dead. Bill C-27, which contained the Artificial Intelligence and Data Act as Part 3, died on the order paper on January 6, 2025, when Parliament was prorogued following Prime Minister Trudeau's resignation. The Carney government, elected April 2025, has taken a fundamentally different approach — the first-ever Minister of Artificial Intelligence and Digital Innovation (Evan Solomon) has stated the government won't "over-index" on regulation. Budget 2025 allocated $925.6 million for sovereign AI infrastructure, emphasizing adoption over guardrails.

The scale of AI penetration in hiring is staggering. Over 99% of Fortune 500 companies use AI-based tools in their hiring processes, and more than 90% of employers use some form of automated system to filter or rank applications. Yet many employers — particularly those now subject to Ontario's disclosure requirement — may not realize their standard recruitment software qualifies as AI under the broad OECD-aligned definition.

As one IAPP expert observed: "Everyone's slapped AI on their product, and it's hard to sometimes tell what might be the artificial intelligence in the product." Even platforms marketed as more human-centric — Greenhouse, Lever — integrate AI through extensive third-party ecosystems.

Depending on how "AI ethics policy" is defined, somewhere between 12% and 55% of organizations have meaningful governance. The original ~22% figure remains a reasonable approximation for organizations with comprehensive, implemented policies rather than aspirational frameworks.

Ontario's disclosure requirement represents the minimum viable regulatory intervention — a transparency mandate with no bias-testing obligation, no algorithmic impact assessment, and minimal guidance on what constitutes compliance. Its significance lies less in what it demands than in what it signals: that AI in hiring has crossed from a technology question into an employment law question.

Three dynamics will shape the next 12 months. First, the definition problem is universal — Ontario's broad OECD-aligned AI definition, Colorado's "high-risk" framing, and NYC's "automated employment decision tool" construct each draw different boundaries around similar technology. Second, enforcement remains the weakest link everywhere — NYC's two-year track record demonstrates that even enacted laws achieve little without institutional capacity. Third, the federal vacuum in both Canada and the United States means provinces and states are writing the rules, producing a fragmented landscape that favors employers sophisticated enough to navigate it and disadvantages workers in jurisdictions without protections.