Workforce Transparency Act of 2026

Artificial intelligence systems are already, as of the date of enactment of this Act, widely used by workers, employers, and consumers across sectors of the United States economy.

The most immediate labor-market effects of artificial intelligence are currently occurring at the task, skill, and workflow level, rather than through the wholesale elimination of occupations.

Research shows that artificial intelligence is also improving workforce productivity by accelerating routine cognitive tasks, enabling workers to focus on higher-value functions, and contributing positively to aggregate economic growth, even as adoption and impacts vary by sector and over time. Artificial intelligence also has the potential to create new roles, consistent with previous patterns in which technological change has led to significant changes in the types of jobs people do over time.

Policymakers, workers, educators, and employers lack timely and standardized information about how artificial intelligence systems are being used and how such use affects productivity, skills, and workforce outcomes.

Aggregated, privacy-preserving transparency, including information voluntarily shared by a covered AI system provider and complementary data published by the Federal Government, can meaningfully improve workforce development, education policy, and economic planning without revealing proprietary information, trade secrets, individual-level data, or other information that would undermine individual privacy.

A Federal transparency framework that encourages participation and supports modernization of government data systems can establish a consistent national baseline, reduce fragmentation across States, and provide a level playing field among covered AI system providers.

establish a Federal framework for aggregated, de-identified transparency or data-sharing regarding use of artificial intelligence systems relevant to workforce impacts;

support evidence-based workforce, education, and economic policymaking through both voluntary participation by a covered AI system provider and improved Federal labor-market data;

protect individual privacy, confidential business information, and competition; and

promote public trust through consistent, responsible, and privacy-preserving data-sharing.

is aggregated across users, accounts, interactions, or customers;

does not identify or reasonably permit the identification of a particular person, household, or employer; and

does not disclose—

designed and marketed by a person primarily for internal business use by the person;

used solely for academic or non-commercial research; or

designed for a narrow, discrete technical function without general-purpose capabilities.

Task or activity level use— Aggregated distribution of interactions across broad task or activity categories, such as writing, coding, research, analysis, translation, or job-related assistance (as established and periodically updated by the Secretary through notice and comment rulemaking under section 553 of title 5, United States Code).

Geographic distribution— Aggregated distribution of interactions across broad task or activity categories, by State or by metropolitan statistical area or comparable geographic unit.

Age ranges— Aggregated distribution of interactions across broad task or activity categories, by adult age ranges, as reasonably feasible and consistent with privacy safeguards or laws.

Temporal trends— Changes in usage patterns over time based on task or activity category.

personal data or information linked or reasonably linkable to an individual;

employer-specific, customer-specific, or individual-specific performance data;

trade secrets, proprietary algorithms, model weights, training datasets, or source code;

information that a participating entity is contractually prohibited from disclosing pursuant to agreements or terms with consumers, users, or enterprise, governmental, or institutional customers or that the participating entity otherwise commits to protecting from disclosure in policies or representations, including restrictions or commitments on data use, aggregation, or secondary disclosure; or

data in violation of a contract or other terms with an enterprise customer, consumer, or user, including contractual restrictions on data use, aggregation, disclosure, or secondary analysis.

standardized reporting formats and taxonomies for purposes of submissions under section 4(a);

acceptable aggregation, anonymization, and privacy-preserving methods for purposes of submissions under such section;

procedures to minimize reporting burden for purposes of such submissions, including alignment with existing Federal data-collection efforts; and

definitions and classifications for broad task or activity categories used in workforce-related artificial intelligence usage reporting.