Artificial intelligence is quickly becoming a powerful force within U.S. national security agencies, streamlining time-consuming tasks and boosting efficiency—from document declassification to enterprise-level productivity enhancements.
“We have released tens of thousands of documents related to the assassinations of JFK and Senator Robert F. Kennedy, and we have been able to do that through the use of AI tools far more quickly than what was done previously, which is to have humans go through and look at every single one of these pages,” said Director of National Intelligence Tulsi Gabbard during the AWS Summit this week.
Gabbard noted that AI deployments are aligned with the agency’s broader objective: ensuring timely access to information. Besides declassification, she cited practical implementations of AI in functions like human resources and internal systems. Notably, an AI chatbot has been rolled out agency-wide, unlocking further possibilities for innovation.
“We’ve made progress, but there’s so much room for growth and more application of AI and machine learning,” Gabbard said.
Agencies remain cautious, however, implementing checks and human oversight to maintain accuracy, compliance, and effectiveness. While the technology shows great promise, it is still evolving, and leaders are aware of the risks tied to generative and autonomous AI tools.
“There are things to be concerned about,” said Lakshmi Raman, Director of AI at the Central Intelligence Agency, referring to potential issues like model or data drift, lack of tool explainability, and concerns around trust.
Private sector leaders share these concerns, according to a recent Cloudera survey. Respondents expressed a need for improved data privacy and security in current AI agents and noted integration and customization as ongoing challenges.
Despite these obstacles, AI adoption continues to rise. Across industries—from retail giants like Walmart to automotive leaders like Toyota—companies are turning to AI to supercharge operations.
In the intelligence space, similar excitement is brewing over agentic AI tools.
“With [concerns] in mind, being able to gather data from multiple spaces and leverage AI agents for cognitive aids is incredibly exciting,” Raman said.
The emergence of generative AI is also reshaping how agencies approach talent development and organizational transformation.
“We think of it at three different levels: our general workforce, which might be the most important user base with those people who are sitting side by side with AI practitioners,” Raman said. “Then we think about it for our practitioners, so they are really keeping up with the latest. And finally, our senior executives, who can think about how they can transform their organization with AI.”
She emphasized the need for talent that blends technological fluency with analytical skills.
“When we’re thinking about analysts, for example, we’re thinking about people who have critical thinking skills, who can demonstrate analytic rigor, who can think multiple steps ahead with incomplete information,” Raman said. “And we’re also looking for people who have digital acumen with understanding of cloud, cyber and AI.”
Gabbard added that this moment calls for employees to reassess existing procedures and identify areas for process improvement.
“A lot of this comes for some folks, who’ve been working in the community for a long time, with a change in culture and a change in … education,” Gabbard said.
One significant area of transformation is the accreditation and authorization process.
“You can imagine a cybersecurity analyst who traditionally has gone through network data very manually in order to block suspicious IP addresses or connections,” Raman explained. “Now, there’s an opportunity to do all of that really easily.”