Agentic AI in the Public Sector: Moving Beyond Knowledge Management to Autonomous Government Workflows

The Next Evolution: From Generative to Agentic AI

Federal agencies have made significant strides with generative AI—using it to power knowledge management, automate content creation, and enhance citizen services. But as the demands on government grow and the complexity of public sector operations increases, a new frontier is emerging: agentic AI. This next evolution moves beyond simply retrieving information or generating content. Agentic AI enables autonomous, multi-step workflows—automating entire government processes, making real-time decisions, and orchestrating actions across systems with minimal human intervention.

Generative AI vs. Agentic AI: What’s the Difference?

Generative AI excels at creating content, summarizing documents, and answering questions. Think of it as a highly capable assistant: it responds to prompts, drafts reports, and provides recommendations, but always waits for a human to take the next step.

Agentic AI, by contrast, is a proactive team member. It can:

This leap in autonomy means agentic AI can transform not just how information is accessed, but how government work actually gets done.

Real-World Examples: Agentic AI in Action

Automated Claims Processing

Imagine an AI agent that receives a benefits application, verifies eligibility by cross-referencing multiple databases, requests missing documentation, calculates entitlements, and issues a decision—all while flagging exceptions for human review. This isn’t a distant vision: agentic AI is already being piloted in highly regulated industries to streamline claims, reduce errors, and accelerate service delivery.

Fraud Detection and Prevention

Agentic AI can continuously monitor transactions, identify suspicious patterns, and autonomously trigger investigations or freeze payments. By integrating with financial, employment, and identity verification systems, these agents can reduce improper payments and protect public funds—freeing up human investigators for the most complex cases.

Workflow Orchestration Across Agencies

Consider disaster response: agentic AI can coordinate logistics, allocate resources, and communicate with citizens across multiple agencies and jurisdictions. By automating routine coordination tasks, these agents enable faster, more effective responses to emergencies and evolving public needs.

Roadmap: How Agencies Can Pilot and Scale Agentic AI

  1. Secure Leadership Buy-In and Define Strategic Value
    • Align stakeholders on the transformative potential of agentic AI—not just for efficiency, but for mission impact and citizen trust.
  2. Identify High-Impact, Multi-Step Use Cases
    • Start with processes that are rules-based, repetitive, and data-rich (e.g., claims, compliance checks, onboarding). Prioritize areas where automation can deliver measurable improvements in speed, accuracy, or cost.
  3. Assess Data and Integration Readiness
    • Map out data flows and integration points across legacy and modern systems. Agentic AI’s power lies in its ability to connect and act across silos—so interoperability is essential.
  4. Develop and Test Pilots with Human-in-the-Loop Oversight
    • Build small-scale pilots with clear guardrails. Ensure humans can intervene, audit, and continuously improve AI performance—especially for high-stakes decisions.
  5. Establish Robust Governance and Ethical Frameworks
    • Define policies for data use, model oversight, and responsible AI deployment. Address privacy, security, and bias from the outset.
  6. Invest in Change Management and Workforce Upskilling
    • Prepare staff for new roles in oversight, quality control, and creative problem-solving. Foster a culture of experimentation and continuous learning.
  7. Scale Successful Pilots and Optimize Continuously
    • Expand agentic AI to additional workflows, integrating feedback and lessons learned. Measure impact, refine processes, and adapt governance as needed.

Addressing Public Sector Challenges: Integration, Governance, and Change Management

Integration

Most government systems are fragmented and not designed for real-time, cross-agency automation. Agentic AI requires deep integration with core platforms (ERP, CRM, case management, etc.), robust APIs, and event-driven architectures. Agencies must invest in modernizing their tech stacks and breaking down data silos to unlock the full potential of agentic AI.

Governance and Risk Management

With greater autonomy comes greater responsibility. Agentic AI must operate within strict ethical, legal, and policy boundaries. Agencies need frameworks for:

Change Management

Agentic AI will reshape roles and workflows. Agencies must proactively manage change—communicating the benefits, addressing concerns, and equipping employees with the skills to supervise, interpret, and improve AI-driven processes. Upskilling is essential, as new roles emerge in AI oversight, prompt engineering, and data stewardship.

Why Publicis Sapient?

Publicis Sapient is a trusted partner for federal agencies navigating the next phase of digital transformation. Our proprietary solutions—like Sapient Slingshot—accelerate the integration and orchestration of agentic AI across complex, regulated environments. We bring:

Ready to Move from Pilots to Enterprise-Scale Transformation?

Agentic AI is not just the next step in automation—it’s a new paradigm for government work. Agencies that act now will lead in efficiency, resilience, and citizen impact. Publicis Sapient stands ready to help you pilot, scale, and govern agentic AI solutions that deliver real results for your mission and the people you serve.

Let’s start the conversation.