Federal Government Artificial Intelligence Adoption: A Domain-Centric Approach for AI-Ready Agencies
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Your Leadership Has AI Mandates.
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Your Teams Have Operational Problems.
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This Is the Approach That Uses One to Solve the Other.
Learn more about the domain-centric approach that solves both enterprise-level strategy barriers and domain-led operational problems.
About The White Paper
AI Mandates Are Clear. Execution Isn’t. Federal agencies must adopt AI, yet leaders face a chasm: enterprise strategy hindered by the realities of workforce apprehension, structural silos, and policy friction.
AI Carries Greater Risk. The Solution Is Operational. The real challenge isn’t mastering the technology—it’s bridging AI capabilities with mission delivery. Without an approach, agencies risk stalled deployments, compliance delays, and missed opportunities to optomize public services.
The White Paper outlines a way forward. Grounded in federal agency experience, it introduces a domain-centric approach that:
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Builds adoption from the operational level up, using real workflows and mission needs.
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Establishes a bi-directional partnership between AI leadership and domain experts.
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Delivers targeted solutions: Domain-User Learning Journey for workforce readiness, AI Portfolio Strategy for cross-functional collaboration, and Domain-Specific Principles for accelerated, compliant deployment.
Why download it? Because every executive needs to do more than check the mandate compliance box. This white paper delivers practical guidance to ensure AI adoption strengthens mission delivery by bridging the chasm between policy intent and operational reality.
Get the White Paper: A practitioner-designed approach for turning mandates into measurable results.
About The Strategist
Tamara Alston
AI Strategist | Federal Policy Expert
Synthesizing policy and operations into actionable pathways for AI adoption.
When enterprise AI mandates arrived, I stepped forward to lead integration across the second-largest grants portfolio in the federal government, a landscape of complex regulations, siloed functions, and uncertain teams.
The traditional technology implementation model offered no playbook for this. AI is fundamentally different from other technologies and carries greater risk in the public sector. The path forward was not clear: how to bridge AI capabilities with mission delivery or engage domain experts as partners in the process.
I went to the source. Grounding myself in the executive orders and mandates, I developed a "clear way forward", drawing on over fifteen years of grants reform and streamlining experience: policy-grounded, user-forward, building from operations up.
This approach was codified in agency-level principles I authored for responsible AI use in grants management, later reinforced through MIT's AI leadership program.
This white paper's domain-centric framework builds on that methodology. The barriers I navigated include workforce apprehension, structural silos, and policy friction. These are the same barriers facing federal agencies today. This is the strategist's guide to bridging them.
