TAMPA — The future of the US Intelligence Community is likely to involve networks of AI agents working amongst themselves — exchanging information, coordinating tasks and providing actionable intelligence, key officials said this week.
“Building agents, and then agents with agents, is the direction that we want to go,” Maj. Gen. Robert Kinney, chief artificial intelligence officer for the Defense Intelligence Agency, said during an AI panel at DIA’s DODIIS show on Wednesday. “We’re laying the foundation and the pipes, if you will, to get after building agents.”
The concept goes well beyond today’s chatbots, where a user asks a question and receives an answer. Kinney envisioned an AI agent that supports intelligence functions communicating with multiple other agents supporting operations, fires, logistics, communications and planning, creating an interconnected system able to help reason through complex mission problems.
The early challenges are figuring out the “tradecraft” piece, Kinney said: how to responsibly use agents to interact and control other agents, and how to deal with compliance, security and trust while those agents are being built.
Also still to be determined is how far the government should allow agents to operate without human intervention. Kinney suggested the answer will depend on the consequences of a decision. In potentially reversible mission areas, agencies could accept more risk and keep a human “on the loop,” while irreversible actions such as fires would require a human “in the loop.”
These are not theoretical concerns, as this discussion also comes against a newly urgent backdrop. In recent weeks, OpenAI and Anthropic have disclosed cases in which they say AI agents escaped intended containment during security tests and took unauthorized actions to hack into other network systems, raising fresh questions about how much autonomy such systems should be given as their capabilities grow.
Kinney said the agency is on a 90-day sprint to build its first enterprise AI platform service.
Another deliverable is the Modular Component Platform (MCP), which Kinney said is a “more universal way to be able to access our data.” He added that ChatDIA, which is deployed on the Joint Worldwide Intelligence Communication System (JWICS), is also being “retooled as a front end for MCP and agents.”
The National Geospatial-Intelligence Agency (NGA) is taking a similarly methodical approach.
Michelle Aten, NGA’s chief artificial intelligence officer, said the agency is developing an agentic framework built around individual tasks identified by subject matter experts, while working across the IC to avoid multiple organizations wasting money building the same agents. The goal is to make trusted agents broadly available and discoverable, then continuously monitor them for “anomalous or aberrant” behavior.
NGA has also stood up an AI task force to “aggressively” determine whether its investments are actually producing results. Aten said the effort consists of conducting data calls and interviews across the agency to inventory AI capabilities and their supporting data flows, establish performance and effectiveness measures, and compare programs to reduce redundant spending.
At the FBI, chief artificial intelligence officer Katie Noyes said the bureau’s initial agentic approach is being organized around specific roles. A counterterrorism analyst, for example, could have an agent pulling together open-source and intelligence collections, identifying correlations and suggesting what questions to ask next. A cyber analyst could use a similar framework to examine indicators of compromise against the FBI’s network traffic.
As with DIA and NGA, the focus for the FBI is developing infrastructure, governance and trust, the officials said. That will determine which agents to build, what they can access, how their performance will be measured, and, critically, when a human must remain in control.
