This guide outlines key strategies, definitions, and procedures for improving SNAP payment accuracy and reducing quality control (QC) error rates across states.
This report examines how governments can effectively build, attract, and retain AI talent to responsibly integrate artificial intelligence into public service delivery.
This report outlines best practices for developing transparent, accessible, and standardized public sector AI use case inventories across federal, state, and local governments
This document provides two Spanish language templates for SNAP agencies to use to communicate SNAP work requirement changes to participants who are newly subject to requirements.
American Public Human Services Association (APHSA)
In this meeting we heard from Emma Braaten and Rachel Rosenbaum, on North Carolina Digital Skills Standards a statewide framework and recent work on digital identity design patterns for state benefits systems.
This site contains resources explaining the 2025 Working Families Tax Cut Act (WFTC) — formally Public Law 119-21, which changes eligibility, financing, and community-engagement requirements for Medicaid and Children’s Health Insurance Program (CHIP).
A case study describing how Massachusetts is building long-term public-sector capacity to deliver people-centered digital services by strengthening in-house expertise, shared tools, and agency-embedded support.
This publication explains the fundamentals of state IEE systems—including the technology, opportunities, risks, and stakeholders involved. It is a resource for state officials, advocates, funders, and tech partners working to implement these systems.
A blog post outlining key strategies states can use to lower SNAP payment error rates, a priority given new fiscal penalties tied to error rates under recent federal law.
