AI in Hiring Compliance Checklist for 2026

 AI is already embedded in many recruiting and HR workflows, often within applicant tracking systems, screening platforms, assessments, and scheduling tools that require strong HR compliance support.  Federal agencies have cautioned that algorithmic decision tools can create discrimination risk, including disability discrimination under the ADA, if employers do not design and use them carefully.

At the same time, certain jurisdictions have enacted specific rules governing automated tools in employment decisions. For example, New York City regulates “Automated Employment Decision Tools” used to screen candidates or employees and requires notice and a bias audit before use, with enforcement that began July 5, 2023.

The regulatory landscape is still developing, but the compliance risk is real today.

Where AI Shows Up in Hiring

AI or automated decisioning frequently appears in:

• Resume screening and ranking - Many modern hiring and applicant tracking solutions include these capabilities by default.

• Pre-employment assessments and scoring

• Candidate chatbots and automated scheduling

• Video interview analysis within certain platforms

In Illinois, if an employer asks applicants to submit recorded video interviews and uses AI to analyze those recordings, the Illinois Artificial Intelligence Video Interview Act requires specific disclosures and applicant consent before proceeding.

In Maryland, employers may not use facial recognition services during an interview unless the applicant provides consent.

Even if your organization is not intentionally “using AI,” many vendor platforms now incorporate automated decision features by default. That makes inventory and documentation essential.

The Compliance Risks You Need to Manage

These are the most defensible, source-aligned risk areas:

1. Disability Discrimination Risk Under the ADA

If automated tools screen out candidates who need reasonable accommodations, or if selection procedures have discriminatory effects, employers may face ADA risk. Federal guidance has specifically warned employers about these concerns when using algorithmic tools.

2. Jurisdiction-Specific AI Requirements

New York City’s Automated Employment Decision Tool rules require notice and an independent bias audit before use. Other states have more limited but specific requirements tied to AI in interviews or biometric analysis.

3. Employer Responsibility

Using a third-party vendor does not eliminate employer responsibility for employment decisions. Employers remain accountable for how tools influence outcomes. Vendor documentation supports risk management, but it does not transfer legal liability.

The Practical Checklist: What to Do Now

1. Inventory Every Tool That Influences Hiring Decisions

Document each system that screens, ranks, recommends, assesses, or filters candidates.

Capture:

• Tool name and vendor
• What decision it influences
• What data it ingests
• Who uses the output and at what stage

You cannot govern what you have not mapped. This same visibility principle applies to structured onboarding workflows as well. 

2. Map Where Automation Affects Outcomes

Identify the exact point where automation impacts a candidate’s experience or status.

Examples:

• Knock-out questions
• Automated scoring thresholds
• Ranked candidate lists
• Auto-rejection triggers

This creates clarity for audit and review.

3. Put Human Review in the Right Places

Establish required human checkpoints for:

• Rejections based primarily on automated scoring
• Situations involving accommodation requests
• Edge cases or nonstandard applications

This aligns with federal agency emphasis on preventing discriminatory screening effects and maintaining ADA compliance.

4. Establish an ADA Accommodations Path for AI-Based Steps

If you use assessments, timed evaluations, or automated screening:

• Clearly explain how candidates request accommodations
• Assign responsibility for reviewing accommodation requests
• Define how the hiring process changes when accommodations are approved

This step directly addresses federal guidance on AI and disability discrimination risk.

5. Confirm Jurisdiction-Specific Requirements

Review whether your hiring practices trigger specific rules.

Examples:

• NYC: Automated Employment Decision Tool notice and bias audit requirements
• Illinois: Disclosure and consent for AI analysis of recorded video interviews
• Maryland: Consent required for facial recognition use during interviews
• Colorado, effective February 1, 2026: Evaluate whether your AI tools may qualify as high-risk systems and whether “reasonable care” obligations apply

Requirements depend on where applicants are located and where roles are based.

6. Conduct Vendor Due Diligence

Request and retain:

• Clear documentation describing how the tool functions
• Description of data inputs
• Information about available audit logs
• Any validation or bias testing documentation the vendor provides

Frame this as due diligence and risk management, not as a guarantee of compliance.

7. Create a Simple AI Governance Policy

Define:

• Who approves new tools
• Who monitors ongoing use
• How often the process is reviewed
• How changes are documented

Governance does not need to be complex. It needs to be consistent.

Conclusion

AI in hiring is no longer experimental. It is embedded in common recruiting workflows across industries. Federal agencies have warned that these tools can create discrimination risk, including under the ADA.

At the same time, jurisdictions such as New York City have enforceable rules governing automated employment decision tools, and states including Illinois and Maryland regulate certain AI-related interview practices.

For HR leaders, owners, and finance teams, the goal is not to eliminate innovation. It is to document, monitor, and govern how automated tools influence employment decisions.

Compliance begins with visibility and accountability.

✴️Need help with compliance? Contact CTR today! 

Disclaimer: This blog is for general informational purposes and is not legal advice.

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