Seven Steps to Prepare for AI Compliance in Hiring
More than a half dozen state and local AI laws governing hiring and employment decisions are already in effect, with additional regulations on the way. Employers need to act now to build compliance strategies that work across multiple jurisdictions.
The requirements vary by law, but foundational practices apply broadly. Organizations that move early will reduce legal risk, strengthen their defensibility, and avoid reactive scrambling when new rules take effect.
1. Involve the right stakeholders from the start
Bring together legal counsel, talent acquisition leaders, business decision-makers, AI developers, and experts in selection practices and adverse impact analysis. Industrial/Organizational psychologists are particularly valuable for this work.
2. Inventory all selection procedures
Document every selection tool currently in use. Note which jobs use each procedure and in which jurisdictions they operate. This process also reveals gaps in documentation-critical information to address before compliance audits begin.
3. Understand how each procedure works
You need to know the model's development and training process, the data it uses, the specific features or components it relies on, and how those features connect to job requirements. Understand how the system scores inputs and generates outputs that influence hiring decisions.
This foundational knowledge determines which laws apply to a particular tool and where guardrails may be missing.
4. Know what each applicable law requires
Most state and local AI laws mandate one or more of these:
- Adverse impact analyses (often called "bias audits" or "impact assessments")
- Candidate notices about AI use in the selection process
- Reports to regulatory authorities or public disclosure on a set schedule, typically annually
Some laws also require evidence that selection procedures relate to job performance or offer safe harbor protections for organizations that identify and fix bias issues.
5. Determine if you need an independent auditor
Certain laws require third-party auditors. Even when not required, organizations often hire external auditors to ensure independence and add credibility to their compliance efforts. If you go this route, identify a qualified auditor and prepare the data and documentation the audit will need.
6. Consider a proactive audit
A voluntary internal or third-party audit before legal requirements kick in can surface problems early. Include both qualitative assessment-evaluating job relatedness, alignment with the Uniform Guidelines on Employee Selection Procedures, and potential bias sources-and quantitative adverse impact analysis where data allows.
Early detection lets you address issues before they become enforcement problems.
7. Gather validation evidence or plan validation work
If your validation evidence is limited, outdated, or weak, develop a plan to test whether your selection procedures actually work. This may involve updating job analyses, conducting validation studies, or researching whether a procedure functions as intended, remains transparent, and adds genuine value to hiring.
Validation work is especially important when audits uncover potential concerns. Strong validation evidence strengthens legal defensibility and supports ongoing compliance.
Build a foundation now
State and local AI regulation will continue changing. Organizations that take deliberate action early will deploy AI responsibly, manage risks, maintain operations, and adapt to future requirements. A strong compliance foundation now prevents costly last-minute fixes later.
For legal professionals managing employment law compliance, understanding AI for Legal teams is essential. Those overseeing HR technology may also benefit from resources like the AI Learning Path for CHROs.
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