By Eric C.
Federal agencies have spent years automating repetitive tasks, modernizing applications, moving workloads to the cloud, improving data access, and implementing digital workflows. These investments have improved efficiency, but they also create the foundation for the next evolution of Federal IT: Agentic AI and Agentic Operations.
Traditional automation follows predefined rules and workflows. Generative AI expands these capabilities enabling users to interact with information using natural language, generate content, summarize complex data, and support decision-making. Agentic AI takes the next step. AI agents can be assigned a goal, determine the actions required, interact with authorized systems and data, execute multiple steps, evaluate results, and engage people when decisions are required.
Federal IT Is Moving Beyond Automation
Agentic AI is quickly moving from experimentation toward enterprise adoption. In February 2026, the National Institute of Standards and Technology (NIST) launched its AI Agent Standards Initiative, recognizing that AI agents capable of autonomous actions require standards that support secure operation and interoperability across the digital ecosystem. (NIST) The national security community is moving in the same direction. The June 2026 National Security Presidential Memorandum on AI directs the national security enterprise to accelerate AI adoption in mission areas where it can improve operational effectiveness, while emphasizing reliability, security, testing, interoperability, oversight, and accountability. (The White House)
Agentic Operations Build on the Modernization Journey
An AI agent operating inside a Federal enterprise needs more than a powerful model. It needs trusted data, secure access, APIs, identity and permissions, cloud infrastructure, workflows, cybersecurity controls, monitoring, auditability, and clearly defined human decision points.
ActioNet built data & cloud foundations for AI at Commerce leveraging AWS, EKS, Athena, RDS, Glue, Lambda, APIs, microservices, IaC, CI/CD, DevSecOps, & FinOps.
Agentic AI does not replace the Federal modernization journey—it builds on it.
Through the Data Ingest and Collection for the Enterprise (DICE) solution, ActioNet applied cloud-native architectures, AWS EKS-based microservices, Infrastructure-as-Code (IaC), automated CI/CD pipelines, security controls, and automated data-quality checks for the US Census Bureau. Capabilities have reduced system deployment time by 75 percent, while supporting 24/7 production operations and continuous security and compliance monitoring. Our Census Enterprise Data Lake (EDL) work extended that foundation through automated data migration, ETL and harmonization pipelines, role-based access, standards-based APIs, continuous monitoring, and FinOps. The result reduced computing infrastructure costs by 36 percent while maintaining 100 percent uptime for the EDL.
From Automated Workflows to Intelligent Workflows
ActioNet enabled Intelligent Enterprise Workflows for Federal customers at Commerce and State through managed services leveraging ServiceNow ITSM, ITOM, ITAM, workflows, KCS, automation, dashboards, & AI capabilities.
Consider a traditional IT service workflow, where automation can route an incident, notify the right support team, initiate an approval, provision a resource, or execute a predefined remediation. An AI-enabled environment can help analyze the incident, summarize relevant knowledge, recommend an action, and assist the technician.
An authorized agent could evaluate the request, gather information from multiple systems, identify the affected configuration items, review knowledge and prior incidents, execute approved diagnostic actions, coordinate supporting workflows, document the results, and escalate the issue when human judgment is required. Similar patterns can apply beyond IT service management—to cybersecurity, application development, data operations, cloud management, asset management, acquisition support, and mission business processes.
Governance Must Evolve With the Technology
This is a journey we discussed in a previous ActioNews article. Our ActioNet AI Intelligent Capability Lifecycle™ (ICL) treats AI as an evolving capability rather than a one-time technology implementation. It integrates program management, enterprise architecture, data strategy, Agile delivery, security, governance, operations, and continuous optimization. (ActioNet, Inc.)
Agentic Operations reinforce the need for our lifecycle. As agents gain access to enterprise systems and execute increasingly complex tasks, organizations need to understand what the agent is authorized to do, what data it can access, what decisions require human approval, how its actions are logged, how performance is measured, and how the capability is continuously tested and improved.
Automated Cybersecurity & Continuous Compliance at Dept. of State leveraging Splunk Enterprise, Cribl, Qmulos, Microsoft Defender, Oracle DBSAT, SCAP, compliance dashboards, & AI/ML pipelines.
NIST’s new AI Agent Standards reflect these same aspects, including secure interaction with external systems, interoperability, identity, authorization, and trustworthy agent behavior. (NIST)
Turning Today’s Operations Into Tomorrow’s Agentic Enterprise
The path to Agentic Operations does not require agencies to replace the investments they have. It requires connecting them. Cloud platforms provide scalable compute and data services. APIs allow systems to exchange information and execute functions. ITSM and workflow platforms orchestrate business processes. DevSecOps and Infrastructure-as-Code automate deployment. Zero Trust controls access to systems and data. Observability provides insight into operational performance. Continuous compliance ensures security control remains effective.
The Next Step in the Journey
Agentic AI will not transform Federal operations simply because increasingly capable models become available. The real transformation occurs when agencies connect AI to trusted data, secure architectures, enterprise workflows, mission systems, and people—and manage those capabilities throughout their lifecycle.
