AI in Employment: Navigating Anti-Discrimination and Compliance Obligations
Employers using AI throughout the employment lifecycle face liability under federal anti-discrimination laws, which apply to algorithmic tools just as they do to traditional tests. State and local AI laws add additional obligations. Employers must ensure AI tools are job-related and consistent with business necessity, and provide reasonable accommodations.
AI deployment now reaches well beyond applicant screening into onboarding, scheduling, performance reviews, and even separation procedures, meaning compliance failures can surface at any employment stage. Federal statutes treat algorithmic tools identically to traditional paper tests, so employers must demonstrate that any AI-driven criterion is job-related and necessary, while also ensuring accommodations exist for disabled applicants taking automated assessments.
The Mobley case illustrates the emerging agency theory of liability, where a plaintiff who received only automated responses after submitting over 150 applications successfully advanced claims against the software vendor itself. Courts permitted the suit to proceed in July 2024, signaling that vendors exercising delegated screening authority may face direct liability. Meanwhile, jurisdictions including California, Colorado, Illinois, and New York have enacted AI-specific laws imposing obligations beyond the federal baseline.
This legal landscape could significantly affect both job seekers and employers. Candidates may gain new avenues to challenge opaque automated decisions, particularly older workers and disabled applicants who face disproportionate screening barriers. Employers could face rising compliance costs, potentially slowing AI adoption in hiring. Smaller firms may struggle most with auditing requirements, while larger vendors like Workday could become litigation targets, reshaping how algorithmic tools are designed and marketed.