The National Geospatial-Intelligence Agency (NGA) is implementing a comprehensive requirement for artificial intelligence and data management proficiency across its entire workforce, including all new hires and existing personnel. This agency-wide directive signifies a profound commitment to embedding AI as a foundational operational capability, essential for modernizing intelligence gathering and analysis. The initiative underscores the urgent need for advanced digital literacy within the defense intelligence sector to effectively harness emerging technological advantages.
This aggressive integration of AI reflects a wider strategic imperative across the U.S. intelligence apparatus, aiming to enhance decision-making speed, improve predictive analytics, and optimize resource allocation within an increasingly complex and data-rich global security environment.
As the National Geospatial-Intelligence Agency rebuilds its workforce after last year’s DOGE cuts, job applicants need to bring some AI proficiency, the agency’s associate operations director said Tuesday.
“We're hiring now, and every single new person we hire has to prove some capability of AI and data management,” Navy Rear Adm. Michael Baker said at the Defense One Tech Summit. “Every single new hire has to go through AI and data management training.”
It’s not just the new employees, Baker said: “Every single old hire has to go through AI training and data management so that all of us are operating inside of the reality of what this ecosystem is.”
NGA leaders have grand visions for weaving AI into the agency’s operations. For example, officials are exploring its use for human resources tasks, a move Baker said would take “the burden off of the operator.” (Recently, a deputy director of human development at NGA expressed fears that employees would get so dependent on AI that their skills would atrophy.)
Baker said he uses an AI agent at work.
“And a real ideal is, in the future, that agent is also helping to train me.” Baker said. “We're working together as we go back and forth to think through a problem. That's been the power of, really, this agentic AI, generative capabilities that you can have as you're thinking through things … In the past, maybe you are using the machine to help you understand history. We're moving to the place where I'm using the machine to help me try to predict and understand the future.”
The Navy admiral said AI agents might eventually be used for high-level strategic planning, and said it could be used to navigate the “insatiable requirements that the intelligence community” demands when calculating risk.
Baker said it’s a balancing act when adopting that technology, and said he wants the agency to rapidly innovate but also wants to be mindful of security and avoid “chaos.”
“That is the complex pace that we're in,” Baker said. “That's a really hard challenge for leaders, but it's a pretty fun space to be in.”
Editorial Analysis
The NGA's comprehensive AI mandate for both incoming and tenured personnel highlights a critical juncture for intelligence agencies: the necessity to not only acquire cutting-edge technology but also to cultivate a workforce capable of effectively deploying and integrating it. This initiative targets enhancing the agency's capacity for predictive intelligence, moving beyond descriptive analysis to leverage AI's potential for anticipating future events and informing high-level strategic decisions. The vision of AI agents collaborating with human analysts for complex problem-solving fundamentally redefines the operational workflow, promising accelerated analysis and a more comprehensive understanding of geopolitical landscapes for various defense stakeholders.
This aggressive push into AI reflects a broader trend within national security, where global adversaries are also investing heavily in similar capabilities, creating an imperative for rapid, secure innovation. Historically, intelligence agencies have adapted to technological shifts, from satellite imagery to cyber intelligence, but the pervasive nature of AI demands a more holistic human-machine teaming approach. Balancing this rapid innovation with robust security frameworks will be paramount to prevent data compromise or AI model manipulation, a challenge that will define the next decade for the security community.
