AI for government agencies, built to be authorized, accountable and useful
AI for government agencies has to earn an authorization to operate and the public's trust. We design AI platforms, governance and security for federal, state and local agencies that meet FedRAMP, NIST and OMB expectations and still ship useful services.
What is different about AI in the public sector
AI for government agencies starts from a different premise than commercial AI: the agency is accountable to the public, to oversight bodies and to law, not to a market. Decisions about benefits, enforcement, eligibility or services must be explainable, contestable and documented. That raises the bar for any AI that affects rights or safety.
Agencies also buy and deploy technology inside formal authorization processes. Cloud services generally need FedRAMP authorization at the right impact level for federal use, systems need an authorization to operate against NIST SP 800-53 controls, and state and local agencies increasingly apply similar frameworks. An AI tool that cannot fit that process does not reach production, however good the demo.
Current OMB guidance on federal AI use directs agencies to inventory AI use cases, designate accountable leadership and apply minimum risk management practices to AI that affects rights or safety. State governments have issued their own executive orders and policies. We design so those obligations are met by the architecture instead of by manual reporting.
Where AI earns its place
Constituent service and contact center support
Help residents find answers on benefits, permits, licensing and taxes in plain language, with citations to official guidance and clear handoff to staff. The assistant does not determine eligibility; it explains rules and routes cases, and every answer is logged.
Case file summarization for caseworkers
Summarize long case histories, correspondence and supporting documents so caseworkers and adjudicators spend time on judgment instead of reading. Summaries cite source pages, and the human decision-maker remains responsible for every determination.
Policy, regulation and grants knowledge
Retrieval over statutes, regulations, internal directives and grant guidance for program staff, with versioning so answers reflect rules in effect on the relevant date. Especially valuable where institutional knowledge is concentrated in retiring staff.
FOIA and public records processing
Assist records staff by identifying responsive documents, flagging likely exemptions and personal information for review, and tracking processing. Staff make every redaction and release decision, and the system keeps an audit trail suitable for appeals and litigation.
Acquisition and contract document drafting
Draft statements of work, market research summaries and evaluation documentation from templates and prior awards, and check drafts against applicable acquisition rules. Contracting officers retain authority, and procurement-sensitive data stays within the agency boundary.
IT modernization and legacy code understanding
Explain, document and help translate legacy code such as COBOL and aging batch systems, and generate tests before modernization. A lower-risk use case that proves the authorized platform and builds engineering confidence inside the agency.
The compliance and oversight constraints we design for
Public sector AI is shaped by authorization frameworks, civil rights obligations and records law. These are the constraints we plan for with federal, state and local agencies.
- FedRAMP and StateRAMP authorization
- Federal agencies generally need cloud and AI services with FedRAMP authorization at the appropriate impact level, and many states use StateRAMP or similar programs. We map each model, platform and data service to its authorization status and design around gaps rather than hoping they close.
- NIST SP 800-53 and the authorization to operate
- AI systems inherit the agency's security control baseline. We document how model gateways, retrieval stores and agent tools implement access control, audit, configuration management and incident response, so the ATO package reflects AI-specific risks instead of ignoring them.
- Current OMB guidance on federal AI use
- OMB guidance directs federal agencies to maintain AI use case inventories, name accountable AI leadership and apply minimum practices to high-impact AI, including testing, impact assessment and human oversight. OMB has revised this guidance across administrations, so we design for the version in force.
- CJIS Security Policy
- Any AI that touches criminal justice information must meet the FBI CJIS Security Policy, including personnel screening, advanced authentication, encryption and audit requirements. That usually limits which model endpoints and hosting options are eligible at all.
- Privacy, civil rights and due process
- The Privacy Act, privacy impact assessments, civil rights law and due process obligations apply when AI affects individuals. Rights-impacting uses need notice, explanation, human review and a way to contest outcomes, and those mechanisms must exist in the system design.
- Records management and accessibility
- AI prompts, outputs and generated documents may be federal or state records subject to retention schedules and public records requests. Public-facing AI must also meet Section 508 accessibility requirements. We design capture, retention and accessible interfaces from the start.
How we architect AI for government agencies
We begin with the authorization boundary. Which cloud environments, model services and data stores are already authorized at the needed impact level determines the realistic design space. We then build an AI platform inside that boundary: a gateway to approved models, retrieval over agency content, and the logging and monitoring the ATO requires.
Every use case is classified early by its impact on rights and safety. Internal productivity tools move through a lighter path. Uses that inform eligibility, enforcement or benefits decisions get impact assessments, pre-deployment testing, human review designed into the workflow and a documented appeal route, consistent with current OMB practices and state policy.
The architecture produces the reporting. Because every model call carries a use case identifier, the agency's AI use case inventory, usage metrics and incident records come from the platform rather than from annual data calls. That same telemetry supports inspectors general, auditors and legislative oversight when they ask how AI is being used.
We design for vendor portability. Agencies should not rebuild applications when a contract ends or a better authorized model becomes available, so applications call a stable internal interface and the gateway handles provider specifics. For AI for government agencies, portability is also a procurement protection.
AI in public sector: common questions
Can federal agencies use generative AI like ChatGPT or Claude?
Federal agencies can use generative AI services that meet their security and authorization requirements, typically offerings with FedRAMP authorization at the right impact level, deployed under agency agreements. Consumer versions used with agency data are generally inappropriate. Several major providers offer government cloud versions of their models, and availability at each impact level changes over time, so verify current authorization status.
What does OMB require of agencies using AI?
Current OMB guidance requires federal agencies to maintain an inventory of AI use cases, designate a Chief AI Officer or equivalent accountable leader, and apply minimum risk management practices to high-impact AI, such as testing, impact assessments, monitoring and human oversight. The specific memoranda have been revised across administrations, so agencies should confirm the version currently in force.
How do you get an ATO for an AI system?
An AI system gets an ATO the same way other systems do: categorize it, implement and document NIST SP 800-53 controls, assess them and accept residual risk. The AI-specific work is documenting model provenance, prompt and output logging, retrieval access controls, abuse testing such as prompt injection, and monitoring. Building on already authorized cloud and model services shortens the path considerably.
How should state and local governments start with AI?
State and local governments should start with an AI policy, an inventory of existing AI use including tools embedded in vendor software, and one or two internal use cases such as policy search or document summarization. Use an authorized or contractually protected platform, keep humans accountable for decisions affecting residents, and publish how AI is used to build public trust.
Other industries
- Financial Services
- Insurance
- Healthcare and Life Sciences
- Manufacturing
- Legal and Professional Services
- Technology and SaaS
In the capital region? We are based in Rockville, Maryland, and run architecture workshops in person. See enterprise AI consulting in Washington DC, Maryland and Virginia.
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