The modernization of employment records (ERs) has become a critical component of 21st-century labor market policy, economic mobility, and social inclusion. ERs are structured administrative data that document an individual’s employment history, including details such as job roles, employers, work locations, duration of employment, and outcomes. Globally, peer countries have developed integrated, real-time, and worker-centric ER systems that reduce administrative burdens and provide transformative insights for policy and practice. This report benchmarks a wide range of international practices to inform U.S. stakeholders pursuing modernization efforts.
While these initiatives build on the existing unemployment insurance wage record system, true modernization requires evolving toward a public-domain, worker-centered employment records infrastructure. This infrastructure should serve broader economic and inclusion goals. The United States currently maintains a wage records ecosystem primarily centered around state unemployment insurance (UI) systems. This system exhibits fragmentation and inconsistency across states, with limited scope and coverage that often excludes key data fields such as occupation, hours worked, work location, and employment tenure. These limitations impede labor market analysis and restrict the effectiveness of job matching, workforce training, education, and equity-focused interventions.
For instance, without occupation codes, states cannot identify regional skills gaps or match training investments to employer needs. Without data on hours worked, policy evaluations of workforce training programs cannot distinguish between a program that lands a participant in a stable full-time job rather than precarious part-time work. The data reporting lag of six to nine months also hinders timely policy responses.
A more modern ER system will become increasingly important as artificial intelligence (AI) spreads through the economy. As routine cognitive tasks become automated through AI, verified experience—documented through comprehensive ERs—will increase in value. Workers who can demonstrate successful adaptation, problem-solving, and skill application across multiple roles and contexts will have significant advantages in an AI-augmented economy.
Global Practices in Modernizing Employment Records Systems
This report examines global practices in modernizing employment records systems, offering insights that may inform U.S. discussions. Drawing on international cases, including real-time payroll integration models (U.K.’s RTI, Australia’s STP), social security-linked systems (Germany IEB), tax-based employment databases (New Zealand LEED), digital labor registries (Brazil’s eSocial), skills planning systems (South Africa), digital identity-enabled platforms (Estonia, India), and distributed credential frameworks (EU initiatives), these examples show how modern systems can improve labor market transparency, reduce employer burden, and empower workers through better data.
For workers, improved ER systems can streamline access to services, increase control over employment histories, and enhance career and education navigation. For businesses, they can reduce duplicate reporting and improve workforce planning through more precise, comprehensive, and timely labor market insights.
Path Ahead
Although governance models vary, international experience shows that standards, interoperability, and institutional capacity can be achieved through different routes, from strong national coordination to distributed architectures and trust frameworks. The path ahead involves complementing and informing important U.S. efforts already underway, including those led by the Jobs and Employment Data Exchange (JEDx), the National Governors Association (NGA), and the National Association of State Workforce Agencies (NASWA), as well as state UI modernization initiatives.
While creating a standalone, public-domain ER platform would eventually require new federal legislation and resources, the most viable short-term path involves concerted state-led innovations supported by voluntary collaboratives and federal technical guidance. Successful international models suggest that incremental adoption of shared data standards and interoperable technology, piloted at the state or regional level, can both generate early wins and provide a scalable template for possible future national infrastructure.
Core Practices in Modern ER Systems
Whether modernization results from state-led efforts or by way of federal legislation, the international examples described in this report elucidate common components of modern ER systems that are key to ensuring broad-based implementation. Across diverse systems, six core practices emerge:
1. Set standards nationally, implement locally: National technical standards ensure consistency while preserving operational autonomy. Common frameworks can achieve alignment across jurisdictions.
2. Pilot first, improve continuously: Phased rollouts and iterative refinement help manage complexity and build stakeholder support.
3. Build around unique identifiers and protect privacy: Stable, personal, and firm identifiers enable interoperability and integration across systems. Interoperability can coexist with selective disclosure and privacy-by-design.
4. Design for timeliness and reuse: Embedding reporting in payroll flows improves data timeliness and reduces burden. Verifiable-credential models allow information to be issued once and reused securely. Reusing records means that a single employer submission can be used across government agencies.
5. Empower workers through access and transparency: Tools enable individuals to verify employment histories, boosting data quality and trust.
6. Align incentives, avoid unintended consequences: Policy design must consider behavioral responses, as well-meaning initiatives can create unintended consequences when incentives are misaligned. For example, an initiative intended to formalize self-employment inadvertently allowed employers to reduce labor costs by misclassifying employees as contractors.
Estos lecciones indican que cualquier enfoque depende de inversiones enfocadas en una arquitectura común, definiciones de datos compartidas y la infraestructura conectiva necesaria para enlazar sistemas de datos. Finalmente, modernizar los registros de empleo debería permitir a cada trabajador acceder, verificar y compartir su historia laboral de manera segura – un bien público para una economía lista para la inteligencia artificial.
