This report provides supplemental estimates on how Public Law 119-21—tied to H.R. 1—will affect SNAP participation, benefits, and state administrative costs over 2025–2034.
This report warns that federal data collection is being undermined by budget cuts, political interference, and leadership changes that threaten the reliability of core economic and social statistics.
This report provides detailed guidance for states on how to verify compliance with and exemptions from Medicaid work reporting requirements established under H.R. 1.
This guide outlines key strategies, definitions, and procedures for improving SNAP payment accuracy and reducing quality control (QC) error rates across states.
This framework provides a structured approach for ensuring responsible and transparent use of AI systems across government, emphasizing governance, data integrity, performance evaluation, and continuous monitoring.
This report outlines best practices for developing transparent, accessible, and standardized public sector AI use case inventories across federal, state, and local governments
Prepared by the Washington State Office of Financial Management’s State Human Resources Division under Executive Order No. 24-01, this report examines the potential effects of GenAI on state employees across sectors including education, IT, and law enforcement.
Washington State Office of Financial Management (OFM)
This report analyzes how administrative burdens in SNAP caused one in eight working-age adults to lose benefits in 2024, with future federal policy changes expected to worsen disruptions
A 2025 policy agenda outlining comprehensive federal and state recommendations to eliminate benefits cliffs and strengthen economic mobility for families transitioning off public assistance.
A detailed guide outlining how states can minimize coverage losses and administrative burden while implementing new Medicaid work requirements established under the 2025 federal reconciliation law.
A report that defines what effective “human oversight” of AI looks like in public benefits delivery and offers practical guidance for ensuring accountability, equity, and trust in algorithmic systems.
This publication summarizes a body of research about how state benefits administering agencies build and maintain integrated eligibility and enrollment (IEE) systems. It is an easy to reference guide for state administrators, legislators, advocates, and delivery partners.
