Managing regulatory change at AI speed

Managing regulatory change at AI speed

The compliance challenge for businesses has fundamentally changed. The challenge is not just about understanding, interpreting, and applying regulations: it is also about managing the speed and volume of regulatory change. So far this year through mid-summer, over 200 HR-related compliance laws have been enacted in the U.S., including several governing the use of artificial intelligence (AI) in the employment context. Just as employers begin to leverage AI to help drive efficiency, this increase in regulatory change is driving fragmentation at the federal, state, and local levels, making human capital management (HCM) even more complex.

At first glance, the opportunity for AI to help automate and manage compliance processes might seem unlimited. However, AI, while a valuable tool, is not a sole fix.

HR is a complex, intricate, detailed field. When it comes to paying people and managing HCM processes, all while staying compliant, AI-enabled processes must be paired with expert human judgment and accountability, ADP advises.

How regulatory change can differ by location or industry

Employers often face differing or conflicting requirements where their people work. While AI can help employers track regulatory changes, those changes often introduce ambiguity, and requirements that at first glance appear similar may be interpreted differently across different states, company sizes, or industries:

• AI in employment and workforce decisions: To promote fairness and transparency, a growing number of laws regulate the use of AI in employment-related decisions including hiring, promotion, compensation, performance management, and other workforce decisions. Companies may be required to disclose to employees and job candidates their use of AI to evaluate or recommend applicants, to conduct bias audits and risk assessments related to their use of such tools (including in some cases third-party validation), and include review by humans with the knowledge and means to identify and address violations as part of their processes. Complicating compliance efforts, state approaches continue to vary. Recent state activity illustrates this trend, with some states adopting broad AI governance frameworks and others focusing specifically on employment-related automated decision-making and associated notice, assessment, and oversight obligations.
• Pay transparency laws: The growing number of state and local laws requiring disclosure of employee pay rates vary widely in their specific requirements, even as they aim to provide transparency regarding pay ranges to job candidates.
• New tax rules for tips and overtime: Starting with the 2026 tax year, employers must report qualified tips and overtime on employees’ W-2 forms. Many states have adopted the federal reporting requirements for tips and overtime, while others have established their own tax reporting rules.
• Paid and protected leave: States continue to pass laws creating and expanding paid family leave and medical leave programs, requiring employers to navigate varying rules related to employee eligibility, payroll deductions and contributions, notice obligations and potential coordination with existing employer-provided leave benefits. Localities are passing paid leave programs as well, further adding to the regulations employers need to navigate.
• Multijurisdictional compliance: As companies expand into different jurisdictions, managing varying workforce compliance requirements becomes more complex.

Whether it's AI governance, pay transparency, tax reporting, or leave requirements, employers increasingly face different obligations depending on where employees work, how their workforce is structured, and even which technologies they use.

How to automate compliance without losing human oversight

To keep pace, leveraging AI-enabled HR systems can help by alerting employers of relevant changes in the rules for payroll (wage and hour laws), taxes (income and employment), health and disability insurance, workers compensation, unemployment insurance, and benefits. Automation can extend from identifying and isolating potential compliance risks to encouraging on-the-spot remediation through a combination of suggested actions and timely human intervention.

However, employers need accountability, not just information. While AI can surface a regulatory update, it cannot determine how that rule applies to a company’s unique workforce structure, operating footprint, or existing policies. For many employers, compliance risk is no longer created by a lack of awareness. It’s created by the growing gap between regulatory change and an organization’s ability to operationalize that change.

As AI accelerates business operations and regulatory change alike, employers need a new model for managing risk. Automation can provide visibility and speed, but compliance ultimately requires judgment, accountability, and expertise. An approach that combines the speed of intelligent technology with the judgment of trusted experts may become a defining advantage.

This story was produced by ADP and reviewed and distributed by Stacker.