Human capital management (HCM) professionals are witnessing a seismic transformation driven by advancements in technology. While artificial intelligence (AI) has existed for decades, the emergence of generative AI has accelerated innovation across human resources (HR) functions, including productivity, employee service, recruiting, payroll and more.
 

With evolving laws and practices, HR must navigate how AI contributes to employment decisions while ensuring compliance with new regulations.

Data Integrity and Compliance: A Critical Intersection

As AI becomes integrated into everyday tools, its value is determined by the quality of the data it uses. Key questions include: Who owns the data? Who can access and use it, and how? Much of the evolving AI legislation focuses on these issues. High-quality outputs require high-quality inputs, with large and diverse datasets ensuring better data integrity. Reliable data integrity not only enhances AI’s effectiveness but also helps ensure compliance with privacy regulations.

To maintain compliance, organizations must prioritize responsible data use. This involves evaluating what data is essential, masking or anonymizing sensitive information when possible, and adhering to data minimization principles. Transparency in data usage builds trust, which fosters greater permissions for data use and fuels actionable insights. Ultimately, this approach creates human-centered experiences rooted in ethical practices.

Staying Ahead in a Shifting Regulatory Landscape

New AI-related regulations emphasize critical themes, such as protecting individuals from algorithmic bias and ensuring transparency about AI’s role in decision-making. These legal developments can serve as a guide for HR to establish ethical principles around AI use.

Governance over data use is a shared responsibility among developers, suppliers and end-users. In 2019, ADP created an AI & Data Ethics Council, which is tasked with monitoring data permissions and ethical standards. Such governance ensures compliance and data privacy “by-design,” using minimal data for insights and partnering with vendors committed to rigorous compliance frameworks.

For organizations just beginning their AI journey, assembling a cross-functional team from IT, legal, security and HR is essential to address how laws impact operations. Tools like the National Institute for Standards and Technology’s AI Risk Management Framework and resources from the Future of Privacy Forum can guide responsible AI development and use.

Do not forget that existing laws on discrimination, pay, overtime and the Family and Medical Leave Act (FMLA) eligibility, for example, still apply in the AI world, but organizations like the U.S. Department of Labor and the Equal Employment Opportunity Commission (EEOC) are providing guidance on interpreting these laws in an AI context.

Additionally, new AI-specific legislation is emerging, such as in New York City, Colorado and the European Union. These regulations emphasize protecting people from bias in algorithms and ensuring transparency around AI use.

Adapting to Generative AI: HR’s Role in Change Management

Successful AI implementation requires thoughtful change management. Incremental progress, clear communication, and addressing employee concerns about unfamiliar technology are key. Organizations must acknowledge employees’ varying levels of familiarity with AI and guide them accordingly.

It is also vital to recognize that AI is a tool, not a solution. It complements human expertise rather than replacing it, enabling better decision-making and outcomes. Embracing this perspective can help organizations take their first steps into AI adoption.

Building Workforce Confidence Through AI Education

Building trust and equipping employees to use AI effectively are crucial for success. While employees may feel uncertain about how AI will impact their roles, AI can empower workers to focus on more strategic work and achieve greater goals. Specific, use-case-driven training can help ensure that employees understand how to leverage AI effectively while maintaining control over outcomes.

For example, when a recruiter uses AI to draft job descriptions, they still need to refine the output with their unique knowledge of the role and organization. This partnership between human expertise and AI capabilities drives better results. Training should also address AI’s limitations and risks, ensuring employees know how to verify outputs for accuracy, fairness and transparency.

Key Steps for HR Leaders

To harness AI’s potential while maintaining compliance, HR professionals should:
 

• Understand how technology providers use and secure data, ensuring alignment with global data privacy and AI regulations.
• Review AI applications within their organizations, determining where human oversight is necessary.
• Regularly monitor outcomes for bias in employment decisions, such as hiring, performance evaluations and promotions.

Generative AI is revealing efficiencies, creating productivity opportunities and introducing new ways of getting work done. But it is important to use AI safely and securely, and to monitor outcomes for bias to help clients, customers and employees get the best results.

Authors’ Bios

Jason Albert is Global Chief Privacy Officer at ADP, where he leads the company’s worldwide privacy compliance program, building on his more than 25 years of experience in legal and policy work in both the U.S. and Europe. Before joining ADP in 2021, he spent five years at Workday, where he led the company’s privacy legal and government affairs teams, and nearly a decade at Microsoft, where he was responsible for strategic projects related to the privacy of the company’s cloud computing offerings.

Helena Almeida is Vice President, Managing Counsel, at ADP. Helena has over 20 years of experience representing companies across various industries on issues involving enterprise-level risk. Helena is an active member of several non-profit organizations dedicated to ensuring equal opportunity and access to new lawyers.

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