Priority 02
Remove inherited process, reporting, approval, and compliance burdens as services, roles, and controls are redesigned, instead of using new tools to accelerate old routines.
The case
An AI tool can make a task faster without making a service better. If staff still chase the same documents, move information between disconnected systems, or wait for the same approvals, the bottleneck may simply move. The larger opportunity is to ask which work is necessary, who should do it, and what a good outcome requires.
Right-sizing procedure does not mean abandoning public protections. It means distinguishing a legal obligation from the inherited routine used to meet it, then designing a less burdensome way to achieve the underlying purpose. Frontline staff, program leaders, lawyers, technologists, and the people using a service need to make those choices together.
What the agenda asks
Map a real service from the resident’s need to its resolution. Identify repeated information requests, handoffs, reports, and approvals; distinguish what can be removed now from what needs a policy change. Make simplification a funded part of modernization.
Give a multidisciplinary team authority to change roles, procedures, and tools together. Compare AI-assisted work with a simpler non-AI approach, and measure total time to resolution, staff effort, errors, and resident experience, including work pushed downstream.
Build appropriate human judgment, accessible alternatives, privacy safeguards, and ways to correct mistakes into the workflow. Test with affected staff and residents, monitor performance after launch, and stop or change tools that do not improve outcomes.
Across the field
This is a curated view of active work that advances the priority, not a claim that every organization shown has endorsed the full Agenda.
Research and policy development
Stanford RegLab is working with New York, California, and Maryland to inventory reporting requirements and examine what agencies produce, what it costs, and whether it is useful. The work uses AI to make accumulated procedure visible so officials can decide what to simplify or remove.
A cross-state effort to examine the work required, not just automate report writing
Piloting and evaluation
Nava Labs has released its Caseworker Empowerment Toolkit after testing benefit-navigation tools with government and community partners. Its tools support policy lookup, referrals, document processing, and form filling, with caseworkers reviewing information before acting. Public code and documentation give other teams a starting point for adaptation.
Toolkit released in April 2026, with public demos, code, and pilot results
Piloting and evaluation
U.S. Digital Response and Arizona’s Department of Economic Security co-designed an AI-assisted translation workflow using staff input, resident research, a SNAP glossary, reusable prompts, and evaluation. The pilot combines automation with human review and prepares the agency to maintain the approach itself.
A SNAP translation pilot that pairs reusable tools with staff review
Learn more
USDR: Arizona language-access pilotIn development
Public Policy Lab is developing AI-assisted SNAP notices with New Mexico and Oregon, supported by Center for Civic Futures’ Public Benefit Innovation Fund. The project targets the manual work of updating program notices, with clearer, more actionable communications as the intended result.
Two-year development award announced in December 2025
Research and policy development
The Federation of American Scientists is translating permitting practitioners’ experience into proposals for stronger interdisciplinary teams and better workflows. Its 2026 Permitting Corps proposal connects digital and AI skills with project management and scientific expertise, and calls for sharing effective tools and processes across agencies.
An August 2026 proposal informed by permitting practitioners’ experience
Learn more
FAS: We Need a U.S. Permitting CorpsWhat could happen next
These are possible next moves, not promises. Each one names what it could unlock and what is still needed to move it forward.
Scoping
Explore building a working Comprehensive Child Welfare Information System (CCWIS) with a state partner, using AI-assisted development and redesigning the practices and policies behind the software. Publish the code, architecture, and implementation playbook, then support a second state’s adoption so every state can build on the same foundation.
What would help
Bring together child welfare agencies, experienced delivery teams, federal partners, and funders to scope a first deployment, second-state adoption, and long-term stewardship. Explore this opportunityExploring
Explore whether congressional committees could pair embedded technical practitioners with serious model access and wraparound support to expand committee capacity and give staff firsthand experience of what AI makes possible.
What would help
Bring together committee leaders, technical practitioners, and support organizations to design a first placement. Explore this opportunityExploring
Explore a privacy-as-code demonstration in a real government data-sharing workflow. Translate approved rules on authority, purpose, access, data minimization, and retention into testable controls, then publish a reusable reference implementation and evidence of how it works.
What would help
Find an agency data-sharing use case and bring together legal, privacy, program, engineering, and oversight expertise to design and test a first implementation. Explore this opportunityHelp move this priority
The Workbench will provide a way to suggest work, correct a description, or help shape an opportunity. Recoding America will keep the public view selective and coherent.
Help shape the Agenda