Artificial intelligence (AI) is rapidly transforming how employers recruit, evaluate, monitor, and engage their workforce. From automating screening processes to analyzing productivity and generating employee communications, AI tools are reshaping nearly every stage of the employee lifecycle.
However, despite this growing reliance on AI, there is only a small but expanding patchwork of state laws governing how these technologies can or should be used in employment settings; furthermore, there remains no unified federal law. In the absence of AI-specific legislation, employers cannot assume that AI use exists in a legal vacuum. Instead, they must evaluate their use of AI systems through the lens of long-standing workplace laws that were not designed with AI in mind and never mention AI by name but still apply.
Statutes that prohibit discrimination, govern background screening, and protect health information can all be triggered by the deployment of AI. Overlooking these obligations could expose employers to significant compliance risk, even when the underlying technology appears to be neutral or beneficial.
Anti-discrimination and Equal Employment Opportunity
One of the most critical challenges of AI integration is maintaining compliance with federal anti-discrimination laws. This includes Title VII of the Civil Rights Act of 1964, which prohibits employment discrimination based on race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), and national origin. Employers must also navigate other anti-discrimination laws such as the Age Discrimination in Employment Act (ADEA), the Americans with Disabilities Act (ADA), and the Equal Pay Act and Fair Pay Act to ensure their systems do not create a disparate impact on protected groups. For instance, tools that penalize specific speech patterns or facial expressions can unfairly disadvantage neurodivergent candidates or those with physical disabilities.
This risk is compounded by the fact that many AI models operate as “black boxes,” which offer little visibility into how outcomes are reached. This lack of transparency becomes a major liability when regulatory agencies seek documentation or when employees challenge adverse decisions. Crucially, the Equal Employment Opportunity Commission (EEOC) has clarified that employers cannot shield themselves from liability by blaming a third-party software vendor. The legal responsibility for fair employment processes and equitable pay ultimately remains with the employer, regardless of the technology used. While these tools are modern, they must still operate within a well-established legal framework that carries significant enforcement consequences.
Avoiding Legal Risks During Background Checks
When AI is used to automate background checks, credit evaluations, or candidate scoring, employers must consider whether the Fair Credit Reporting Act (FCRA) applies. The FCRA imposes specific requirements when information is obtained from a third party and used to make employment decisions. This includes providing candidates with a clear, standalone disclosure and obtaining their written authorization before initiating a background screening.
Importantly, FCRA obligations may apply even when AI tools are not labeled as formal background screening services. If an employer uses AI-powered search tools, chatbots, or browser plug-ins to gather information about a candidate from online sources or public records, and that information informs a hiring decision, the tool may be considered a consumer reporting agency under the law. In these situations, the output may qualify as a consumer report, triggering the same compliance requirements.
Recent litigation has highlighted these risks. In one high-profile lawsuit, filed in January 2026 against Eightfold AI, job applicants are alleging that the talent platform generated behavioral scores and personality evaluations without providing legally required disclosures or adverse action notices. The applicants claim the tool violated the FCRA by producing reports used in hiring decisions without their knowledge or consent. This case underscores the growing legal exposure employers face when using automated systems to evaluate candidate traits, even if the data appears to be publicly available.
Managing Health Data
AI is increasingly used to analyze sensitive information collected through wellness programs, employee health portals, and behavioral health apps. In many cases, this data falls under the protections of the Health Insurance Portability and Accountability Act (HIPAA), which requires strict safeguards for protected health information. Even when this federal law does not apply directly, such as with data from general fitness trackers, the unauthorized access to or misuse of employee health information carries significant reputational and legal risks.
The legal landscape is particularly complex for self-insured employers who act as both the employer and the health plan administrator. Under federal law, these organizations must maintain a strict legal and digital firewall between their health plan functions and their employment functions. When self-insured entities use AI to analyze insurance claims data or pharmacy records, they must ensure the insights are used strictly for plan management such as identifying wellness trends or reducing costs.
If an employer uses AI-driven health insights to identify high-cost individuals and subsequently takes adverse action against them, they may violate the privacy rules of HIPAA and the anti-discrimination provisions of the ADA. Furthermore, the Genetic Information Nondiscrimination Act (GINA) strictly prohibits using any genetic information, which includes family medical history found in insurance claims, to make decisions about employment. For self-insured organizations, the hidden logic within these algorithms is especially dangerous because the employer must be able to prove that their employment decisions were made separate from any health data they possess.
Balancing Innovation with Privacy
Read the next blog in our series, titled “Think AI is Unregulated? Think Again – Part 2” (coming soon) for considerations regarding employee privacy and data rights, information security and retention, and transparency.
Next Steps for Employers
While AI-specific regulations continue to mature, employers cannot afford to wait for a unified federal statute. To reduce exposure, employers should take the following proactive steps:
- Conduct a Fair Credit Reporting Act Audit: AI “fit scores” or personality assessments are increasingly categorized as consumer reports. If your software gathers and analyzes data from the internet to rank candidates, you must follow the FRCA by providing specific notices and obtaining written authorization. Failure to do so is a common pitfall that can lead to class-action litigation.
- Formalize Rigorous Vendor Vetting and Bias Testing: With legal responsibility for non-discriminatory employment decisions falling squarely on the shoulders of the employer, not a third-party software vendor, vendor selection and monitoring is critical. Relying on a vendor to grade their own homework through internal assessments provides almost no legal shield if their algorithm produces biased outcomes. To meet compliance benchmarks, an auditor should be a neutral entity with no financial or developmental stake in the software’s success. If a vendor cannot provide a publicly available summary of an external bias audit conducted within the last year, their technology likely does not meet the minimum safety standards required for modern employment decisions. Furthermore, AI is subject to evolution as it learns. Instituting a regular cadence of bias testing using the employer’s workforce data ensures technology-based outcomes don’t stray from providing equal opportunity as time passes.
- Establish a “Human-in-the-Loop” Mandate: To satisfy federal expectations of “reasonableness,” AI should never be the sole decision-maker for adverse employment actions. Every AI-generated score or recommendation must undergo a meaningful human review. This ensures that a person remains accountable and can override the system if the AI’s logic appears flawed or biased.
How HR Works Can Help
HR Works will continue to provide tools, advice, insights, and other resources to guide HR professionals through these changes. In addition to these considerations, our downloadable checklist and bias testing services will steer you in the right direction. Don’t hesitate to contact us today if you’re seeking a partner to lead your HR department through AI adoption and governance with an approach that is manageable, compliant, and business-driven.
