Transform Your Agency with AI Fluency

Executive Order 14110 (October 2023) establishes comprehensive requirements for federal AI use, including safety testing for high-risk systems, equity assessments, transparency requirements, and Chief AI Officer appointments. Agencies must inventory AI use cases, conduct impact assessments for rights-impacting systems, and implement NIST AI Risk Management Framework. DigiForm helps agencies navigate these requirements through governance framework development, risk assessment processes, and compliance documentation. We've guided federal contractors through EO 14110 compliance, ensuring AI deployments meet transparency, safety, and equity standards while maintaining mission effectiveness.

The NIST AI RMF (released January 2023) is a voluntary framework for managing AI risks across the lifecycle—from design to deployment to monitoring. OMB M-24-10 mandates federal agencies use NIST AI RMF for rights-impacting and safety-impacting AI systems. The framework includes four functions: Govern (establish AI governance), Map (understand AI context and risks), Measure (assess and benchmark AI performance), and Manage (prioritize and respond to risks). DigiForm implements NIST AI RMF by establishing governance structures, conducting risk assessments, defining metrics for bias and performance, and creating continuous monitoring processes. This ensures federal AI systems are trustworthy, transparent, and accountable.

FedRAMP authorization for AI-enabled cloud services typically takes 12-18 months for Agency Authorization and 18-24 months for JAB P-ATO (Provisional Authority to Operate). The timeline includes readiness assessment (2-3 months), documentation development (3-6 months), independent assessment (3-4 months), and authorization review (3-6 months). AI systems add complexity due to model transparency requirements, data provenance documentation, and algorithmic accountability controls. DigiForm accelerates FedRAMP timelines by implementing security controls early, automating compliance documentation, and preparing for Third Party Assessment Organization (3PAO) audits. We've helped federal contractors achieve FedRAMP authorization 20-30% faster through structured preparation and continuous monitoring.

Yes, but with modifications. State and local governments can adopt NIST AI RMF, but aren't bound by Executive Order 14110 or OMB M-24-10 (federal-only mandates). However, many states are developing their own AI regulations—California's AB 302 (AI accountability), Colorado's SB 24-205 (algorithmic discrimination), and New York City's Local Law 144 (automated employment decision tools) create state-specific requirements. DigiForm helps state/local agencies by adapting federal frameworks to state regulations, implementing governance structures appropriate to agency size, and ensuring compliance with both federal grant requirements and state laws. The key is building flexible governance that scales to agency resources while meeting applicable regulatory requirements.

Government AI fluency requires translating technical concepts into mission impact and policy implications. DigiForm's approach includes executive workshops focused on AI use cases for citizen services (not technical details), hands-on pilot project development where leaders identify AI opportunities in their programs, governance framework training to embed AI into strategic planning, and vendor evaluation frameworks to assess AI procurement proposals. We've trained leadership teams at federal agencies and state governments, enabling them to evaluate AI investments, challenge technical vendors, and make informed policy decisions. The goal isn't making executives into data scientists—it's building strategic decision-making capabilities for AI-enabled government services.

The highest-risk areas for government AI are algorithmic bias in citizen-facing decisions (benefits eligibility, criminal justice, hiring), privacy violations from surveillance or data aggregation, lack of transparency in automated decision-making (violates due process), security vulnerabilities in AI systems (adversarial attacks, data poisoning), and vendor lock-in with proprietary AI solutions. DigiForm mitigates these risks through bias testing and fairness metrics, privacy impact assessments and data minimization, explainability requirements for high-stakes decisions, security controls and adversarial testing, and open-source or multi-vendor AI architectures. We prioritize transparency, accountability, and citizen rights—ensuring AI enhances government services without eroding public trust.