AI in Your Workplace: What You Must Disclose Before It's Too Late

For multi-state employers, the compliance challenge is significant: different disclosure formats, different audit requirements, different enforcement mechanisms, and different definitions of what counts as "AI" or an "automated employment decision." Meanwhile, federal bipartisan bills in both the Senate and House would impose human oversight and disclosure requirements for AI used in employment decisions at the national level. Employers who are using AI tools today — even off-the-shelf HR software with embedded AI features — without understanding their disclosure obligations are already out of compliance in at least three jurisdictions and accumulating penalties. The time to act is now. 

 

Areas Covered

Attendees will gain practical, actionable knowledge across these seven critical areas:

Illinois HB 3773 — Effective January 1, 2026: The full scope of Illinois's AI employment law: prohibition on AI that results in discrimination based on protected characteristics, even unintentionally; the notice requirement triggered whenever AI is used "to influence or facilitate" a covered employment decision (recruitment, hiring, promotion, training, discipline, discharge, and terms of employment); what the notice must include per IDHR draft regulations (AI product, purpose, data collected, point of contact); the 4-year recordkeeping requirement for all AI-related notices and disclosures; and enforcement by the IDHR and Illinois Human Rights Commission with private right of action available to employees.

Colorado SB 24-205 — Effective June 30, 2026: Colorado's comprehensive AI Act: the "deployer" framework that applies to every employer using AI in any employment decision; the definition of "high-risk AI system"; the annual impact assessment requirement to identify and document algorithmic discrimination risks; the employee notice and opt-out rights when AI is used in employment decisions; the 90-day reporting obligation to the state attorney general when algorithmic discrimination is discovered; the public statement requirement disclosing AI systems in use; and the narrow exemption for employers with fewer than 50 employees who do not use their own data to train AI systems.

New York City Local Law 144 — Bias Audits, Disclosure & Fines: NYC's AEDT law requirements for employers using Automated Employment Decision Tools in hiring or promotion decisions: annual independent bias audits by a qualified third-party auditor; public disclosure of audit summaries and AEDT deployment dates on the employer's careers page; advance written notice to applicants and employees at least 10 business days before the AEDT is used, with opt-out options and alternative assessment methods; and fines of $500 to $1,000 per violation for noncompliance. Critical: remote employers recruiting in NYC or whose AI tools affect NYC-based employees are subject to this law regardless of where the employer is headquartered.

Texas TRAIGA & California FEHA/ADMT — What Employers in These States Must Do: Texas's TRAIGA (effective January 1, 2026): prohibition on intentional AI-based discrimination against protected classes, 60-day notice and cure period for violations, no requirement for audits or user disclosures — but vigilance required to avoid harmful discriminatory outcomes. California FEHA amendments (effective October 1, 2025): new obligations under the Fair Employment and Housing Act addressing automated decision systems in employment. California CPPA ADMT regulations (effective January 1, 2026): advance notice requirements for CCPA-covered businesses using automated decision-making technology in employment decisions.

Identifying Every AI Tool in Your Employment Process: A practical framework for conducting an AI inventory audit: how to identify every tool — including off-the-shelf HR software with embedded AI features — that collects data, scores candidates, ranks employees, flags performance issues, or generates recommendations that influence any employment decision. How to categorize each tool by jurisdiction, law applicability, and disclosure requirement. Questions to ask every HR technology vendor about AI features, bias testing, and data collection — and how to document the answers to support your compliance record.

Testing for Algorithmic Discrimination & Documenting Mitigation: What algorithmic discrimination is, how it occurs (disparate impact, biased training data, proxy variables), and why it does not require discriminatory intent under Illinois, Colorado, or California law. How to conduct or commission a bias audit, what data to analyze (selection rates by race, sex, age, and other protected classes), how to document mitigation efforts, and why proactive bias testing is both a legal defense and a business imperative as AI discrimination claims begin to reach courts.