Artificial Intelligence (AI) has rapidly transformed the talent acquisition landscape, offering unprecedented efficiencies in sourcing, writing, screening, and assessment. Yet, with this innovation comes a critical responsibility: ensuring ethical deployment and robust compliance. For Talent Acquisition (TA) and TA Operations Leaders, and Recruiters, understanding the evolving patchwork of AI regulations is no longer optional; it is paramount to mitigating risk, fostering fair practices, and building trust. This isn’t just about avoiding penalties; it’s about building a transparent and equitable hiring process.
Compliance, whether it is Pay Transparency or AI, is no longer the sole responsibility of Legal departments. Everyone involved in hiring should work to stay up to date with the evolving hiring regulations. To help, here’s a summary of the key legislative frameworks you need to be aware of, designed to help you stay compliant and competitive while smartly and safely embracing AI.
The European Union’s comprehensive framework
The European Union has emerged as a global frontrunner in AI regulation with its groundbreaking EU AI Act, which largely became effective on August 1, 2024. This market-wide framework provides comprehensive guidance and regulations for AI systems across various sectors, pioneering a risk-based classification system based on the potential harm an AI system can cause.
A “High-Risk” Designation for Hiring AI: Critically for talent professionals and employers, common AI use-cases in the employment context are explicitly categorized as “high-risk” due to their potential impact on individuals’ access to employment and their future careers. This includes:
- CV-sorting and screening systems: AI used to rank or filter job applications, determining who progresses in the hiring pipeline.
- Systems for managing workers: AI influencing decisions about work assignments, performance evaluations, promotion opportunities, or even termination.
- Tools influencing access to self-employment: AI used in platforms connecting individuals to gig work or independent contractor roles, effectively acting as gatekeepers to economic opportunities.
This “high-risk” classification triggers a comprehensive set of stringent obligations for both the providers (developers) who build these AI systems and the deployers (users) who implement them in their hiring processes. These obligations aim to ensure algorithmic fairness, accountability, and transparency, and include, but are not limited to:
- Robust risk management systems to identify and mitigate potential harms.
- Strong data governance practices, including data quality management to prevent bias.
- Meaningful human oversight capabilities, ensuring human intervention and override are possible.
- Enhanced transparency and explainability for AI decisions, allowing individuals to understand how decisions are made.
- Thorough documentation and logging of AI system activities for audit trails.
- Ensuring high levels of accuracy and security of the AI systems.
- Conducting Fundamental Rights Impact Assessments (FRIAs) to systematically evaluate and address potential biases or discriminatory impacts on fundamental rights.
The EU AI Act sets a global precedent for global and regional AI governance, signaling a future where algorithmic fairness and accountability are legally mandated in employment practices. If you want to go in-depth, you can read more about the EU AI act.
North American patchwork regulations
While the EU takes a broad approach, the countries in North America have not yet pursued a similar approach. Instead, various cities and regions are implementing their own specific regulations influencing hiring practices at local levels. These regulations often focus on transparency, notification, and bias mitigation, and while they share some elements, they vary in their application.
- New York City (Effective July 5, 2023):
- Regulated AI: Automated Employment Decision Tools (AEDTs), defined as any computational process that issues a simplified output (e.g., score, classification, recommendation) which significantly assists or replaces discretionary employment decisions.
- Key Regulations: Employers using AEDTs must provide clear notification to candidates with key details about the tool’s use, offer alternative process options that don’t use the AEDT, and, crucially, perform and publicly publish the results of independent bias audits annually. If you want to go in-depth, you can read more about NYC Local Law 144.
- Illinois (Effective January 1, 2020):
- Regulated AI: AI used to analyze video interviews of job applicants.
- Key Regulations: Mandates explicit notification and consent from the applicant for AI analysis of their video interview. Furthermore, it requires employers to collect and report race/ethnicity data of rejected applicants to the Department of Labor, aiming to monitor for discriminatory patterns. If you want to go in-depth, you can read more about Illinois Artificial Intelligence Video Interview Act (820 ILCS 42/5).
- California (Effective October 1, 2025):
- Regulated AI: Automated Employment Decision Tools (AEDTs).
- Key Regulations: Requires employers to maintain comprehensive employment records, including detailed automated-decision data, for at least four years. This record-keeping requirement aims to facilitate accountability and oversight of AI in hiring decisions. If you want to go in-depth, you can read more from California Civil Rights Department (CRD) regarding employment discrimination, including updates on regulations related to Automated Employment Decision Tools (AEDT).
- Colorado (Effective February 1, 2026):
- Regulated AI: High-risk AI systems that make “consequential decisions” regarding employment, echoing the EU’s risk-based approach.
- Key Regulations: Requires employers to implement a robust risk management policy for these systems, provide notification to affected individuals about AI use, establish a clear appeal process for AI-driven decisions, and publish a public summary of their AI usage in employment. If you want to go in-depth, you can read more about Colorado’s AI employment law (SB24-205, “Consumer Protections for Artificial Intelligence”).
- Ontario (Canada – Effective 2024):
- Regulated AI: AI used to screen, assess, or select applicants.
- Key Regulations: While specific details are still emerging, initial discussions suggest that disclosure of AI usage in job posts or during the application process may be required, emphasizing transparency from the outset of recruitment. If you want to go in-depth, you can read more from Ontatio’s Ministry of Labour.
- Quebec (Canada – Effective 2022):
- Regulated AI: Decisions made exclusively by automated processing (AI) that significantly affect an individual.
- Key Regulations: Employers need to inform the individual that AI is making the decision, offer a mechanism for human review, and, crucially, individuals have the right to know what data was used, the key factors considered in the automated decision, and to request correction of their personal data. If you want to go in-depth, you can read more from the Commission d’accès à l’information du Québec (CAI).
Navigating AI compliance for TA leaders
The landscape of AI regulation in hiring is rapidly expanding, characterized by both comprehensive frameworks like the EU AI Act and granular, region-specific rules. For TA and TA Ops Leaders, and Recruiters, staying ahead means:
- Vigilance: Continuously monitoring new and updated regulations across all relevant jurisdictions where you hire. Compliance is an ongoing process, not a one-time fix.
- Transparency: Being upfront with candidates about AI usage in the hiring process builds trust and meets legal requirements.
- Accountability: Understanding how your AI tools work, regularly auditing them for potential bias, and ensuring meaningful human oversight are non-negotiable. Consider this advice from our Responsible AI blog, “At Datapeople, we approach AI development with excitement but also with an awareness of the risks and challenges it poses.”
- Proactive Adaptation: Updating internal policies, procedures, and training for your hiring teams to align with compliance requirements before effective dates is crucial.
Beyond understanding the regulations, proactive measures are key to establishing a robust AI compliance strategy. This includes rigorous due diligence when selecting AI vendors, ensuring their tools are built with compliance in mind, are regularly audited, and can provide necessary documentation for your own audits. Establishing internal governance frameworks to oversee the adoption, usage, and continuous monitoring of AI tools in your hiring process will also be crucial for long-term adherence and ethical deployment.
The shift towards regulated AI in hiring is a clear signal that fairness, equity, and transparency are non-negotiable. By embracing these regulations and implementing proactive best practices, organizations can not only avoid costly penalties and legal challenges but also build more ethical, robust, and trustworthy hiring practices that benefit both employers and candidates, ultimately strengthening their employer brand in a competitive market.
Curious to learn more about how others have made the leap? We’d love to share their approach!