AI Hiring Compliance in 2026: What Staffing Agencies Need to Know

The recruiting landscape just got more complicated. New AI hiring laws are reshaping how staffing agencies screen candidates, evaluate resumes, and make placement decisions. NYC Local Law 144 is in effect. The EU AI Act has entered into force and is being implemented in stages. State-level regulations are emerging across the US. And candidates are increasingly asking: “How was I evaluated?”

For staffing agencies, this is not just a legal checkbox. It is a fundamental shift in how you can operate. The old playbook—using black-box AI scores to rank candidates quickly—is becoming a liability. Regulators, candidates, and clients all want to know the reasoning behind your decisions.

The good news: you do not have to choose between speed and compliance. Explainable AI—where every ranking includes clear reasoning—is not only legally safer. It is also more effective at finding the right candidates.

The AI hiring compliance landscape has shifted

For years, the recruiting industry operated in a gray zone. AI tools existed, but regulation was sparse. Agencies could use whatever screening software they wanted, with minimal transparency requirements.

That era is over.

New York City enacted Local Law 144 in 2021. The law took effect on January 1, 2023, and the Department of Consumer and Worker Protection began enforcement on July 5, 2023. The EU AI Act entered into force in 2024, with its requirements applying in stages. California, Illinois, and other states are drafting or passing their own AI hiring regulations. And more are coming.

What triggered this shift? A combination of factors: high-profile cases of AI bias in hiring, growing candidate awareness of algorithmic decision-making, and regulators recognizing that hiring AI can perpetuate discrimination at scale if not designed and monitored carefully.

“Regulators, candidates, and clients all want to know the reasoning behind your hiring decisions. Black-box AI is becoming a liability.”

Key laws reshaping staffing agency compliance

NYC Local Law 144

Local Law 144 applies when an employer or employment agency uses a tool that meets the law’s definition of an automated employment decision tool (AEDT) in connection with covered employment decisions. Not every AI-assisted recruiting feature or workflow automatically qualifies.

When covered use applies, the law may require:

• Bias audit: A recent independent bias audit of the tool, with results documented.
• Public availability of audit information: Required audit summary information must be publicly available.
• Candidate notice: Required notices to candidates or employees about the use of the tool.

This is not a complete legal checklist. The law’s full requirements, definitions, and enforcement details are available from the NYC Department of Consumer and Worker Protection AEDT page.

Penalties for non-compliance can reach $500 per violation, per day. For a staffing agency processing hundreds of candidates, that adds up quickly.

EU AI Act

The EU AI Act entered into force in 2024, and its requirements apply in stages. Certain employment-related AI systems may be classified as high-risk depending on the system and its use. For systems classified as high-risk, the Act establishes requirements that may include:

• Technical and governance standards: High-risk AI systems must meet rigorous requirements around data quality, documentation, and risk management.
• Human oversight: Humans must remain in the loop for high-risk decisions. No fully automated hiring decisions.
• Transparency: Users and affected individuals must understand how the system works.
• Testing and monitoring: Ongoing testing for bias and discrimination may be required.

The EU AI Act applies in stages. Under Regulation (EU) 2026/1744, the relevant Chapter III requirements for AI systems classified as high-risk under Article 6(2) and Annex III are scheduled to apply from December 2, 2027. Other AI Act obligations may apply earlier, so organizations should assess the specific system, role, and use case. Working with an EU client or candidate does not, by itself, mean every AI Act requirement automatically applies in the same way. Organizations should review the official EUR-Lex text of the EU AI Act (Regulation 2024/1689) and the amending Regulation (EU) 2026/1744, and consult qualified counsel regarding their specific obligations.

State-level regulations

Beyond NYC and the EU, several US states are moving fast:

• California: Proposed regulations around algorithmic transparency in hiring.
• Illinois: The state has enacted multiple laws relevant to AI in hiring. The Illinois Artificial Intelligence Video Interview Act applies specifically when employers ask applicants to record video interviews and use AI to analyze those interviews. It does not apply to every AI-assisted recruiting workflow. Existing BIPA (Biometric Information Privacy Act) has also been interpreted to cover certain AI hiring tools that collect biometric data.
• Colorado, Connecticut, Utah: Privacy laws with implications for how candidate data is used in AI systems.

In addition, Illinois enacted Public Act 103-0804, effective January 1, 2026. This law amends the Illinois Human Rights Act to address the discriminatory use of AI in recruitment, hiring, promotion, and other employment decisions. It includes a notice requirement for covered AI use. Public Act 103-0804 is a separate law from the AI Video Interview Act and has a broader scope covering multiple stages of the employment lifecycle. Organizations should review the full text and consult qualified counsel; this summary is not a complete compliance checklist.

AI hiring rules are expanding across multiple jurisdictions. The pattern is clear: transparency and human oversight are becoming table stakes.

What these laws may require from your agency

Cutting through the legal language, here are areas staffing agencies should evaluate. This is not a complete compliance checklist, and requirements vary by jurisdiction, tool, and use case:

1. Audit your tools: If you use AI-powered screening or ranking software, determine whether a bias audit is required under applicable law. Document the results.
2. Notify candidates: When you use an automated tool to evaluate a candidate, applicable laws may require you to tell them and provide a way for them to request human review.
3. Explain your decisions: You may need to be able to articulate why a candidate was ranked, screened, or rejected. “The AI said so” is not an acceptable answer under most frameworks.
4. Keep humans in control: Automated tools should support recruiter judgment, not replace it. Recruiters should make the final hiring decisions.
5. Monitor for bias: Regularly check your hiring outcomes for disparate impact. Are certain groups being screened out at disproportionate rates?
6. Document everything: Keep records of audits, candidate notices, tool updates, and bias monitoring results. Regulators may ask for these.

Why black-box AI creates compliance risk

Here is the core problem with traditional AI screening tools: they often work like a black box. You feed in resumes and job descriptions, and out comes a score. But if a candidate asks “Why was I ranked lower than someone else?” or a regulator asks “How did your tool make that decision?”—you cannot give a clear answer.

Black-box AI creates compliance risk because:

• You cannot explain decisions: If you cannot explain why a candidate was screened out, you cannot defend that decision to regulators or candidates.
• Bias is hidden: Without visibility into how the tool works, you cannot detect or fix bias. You only find out when a lawsuit happens.
• Audits are incomplete: Bias audits require understanding how a tool makes decisions. Black-box tools make audits superficial.
• Candidate trust erodes: Candidates increasingly expect transparency. A black-box score feels unfair, even if the outcome is correct.

“If you cannot explain why a candidate was screened out, you cannot defend that decision to regulators or candidates.”

Explainable AI supports transparency and human oversight

Explainable AI—where every ranking includes clear reasoning tied to the job description—directly supports the transparency and human oversight requirements that regulators are increasingly looking for. It does not, by itself, guarantee compliance with any specific law, but it addresses several of the core risks that regulations target.

With explainable AI, you can answer the questions regulators and candidates ask:

• “How was I evaluated?” You can show exactly which job requirements the candidate met, exceeded, or fell short on.
• “Why was I ranked lower?” You can point to specific gaps between the candidate’s resume and the job description.
• “Is this fair?” You can demonstrate that the same criteria were applied consistently to all candidates.

Explainable AI also keeps humans in the loop. The tool surfaces reasoning and gaps—but recruiters make the final decisions. This human-in-the-loop approach is exactly what regulators want to see.

And here is the bonus: explainable AI is more effective. When you can see why a candidate was ranked a certain way, you can validate the reasoning, catch mistakes, and make better hiring decisions faster.

How to build a compliant screening process

Compliance does not mean slowing down. It means being intentional about how you screen and rank candidates. Here are practical steps:

1. Audit your current tools

If you are using AI-powered screening software, determine whether a bias audit is required under applicable law. Look for:

• Disparate impact: Are certain demographic groups being screened out at higher rates?
• Explainability: Can the tool explain its decisions in human-readable terms?
• Human oversight: Does the tool support human review, or does it make final decisions automatically?

2. Choose tools with explainable reasoning

When evaluating candidate screening software—whether a new ATS, a dedicated screening tool, or an AI copilot—prioritize explainability. Ask vendors:

• “Can you show me how your tool explains its rankings?”
• “Does your tool flag gaps between the candidate and the job description?”
• “Can recruiters override or adjust the tool’s recommendations?”
• “Do you provide bias audit results?”

3. Document your process

Create a written policy for how you use AI in screening. Include:

• Which tools you use and why
• How you notify candidates that automated tools are involved
• How candidates can request human review
• How you monitor for bias
• How you keep humans in control of final decisions

4. Notify candidates

When you screen or rank a candidate using an automated tool, applicable laws may require you to tell them. This can be as simple as a line in your candidate communication: “Your application was evaluated using automated screening software. If you would like a human review, please contact us.”

5. Monitor outcomes

Regularly review your hiring outcomes. Are you screening out certain groups at disproportionate rates? If so, investigate why. It could be a tool issue, a job description issue, or a process issue—but you need to know.

6. Stay updated

AI hiring regulations are evolving fast. Subscribe to updates from your state’s labor department, industry associations, and your software vendors. Compliance is not a one-time project—it is an ongoing practice.

Official sources

For the most current and authoritative information on the laws discussed in this article, refer to:

• NYC Department of Consumer and Worker Protection — Automated Employment Decision Tools
• EUR-Lex — EU AI Act (Regulation 2024/1689)
• EUR-Lex — Regulation (EU) 2026/1744 (amending the EU AI Act Annex III timeline)
• Illinois General Assembly — Artificial Intelligence Video Interview Act
• Illinois General Assembly — Public Act 103-0804 (AI amendments to the Illinois Human Rights Act)

The bottom line

AI hiring compliance in 2026 is not about choosing between speed and fairness. It is about being transparent and intentional. Regulators want to see that you are using AI to support recruiter judgment, not replace it. Candidates want to understand how they were evaluated. And clients want to know that your screening process is defensible.

The staffing agencies that thrive in this new landscape will be the ones that embrace explainable AI—tools that show their work, keep humans in control, and make it easy to defend every hiring decision. That is not just good compliance practice. It is good recruiting.

Want to see how an ATS-agnostic copilot with explainable reasoning and structured review works in practice? Requivize surfaces clear reasoning for every candidate evaluation, keeps recruiters in control, provides gap analysis to identify what to validate, and generates candidate-specific interview questions. See how Requivize works or read about our security and data practices.