A prototype utilizing artificial intelligence to function as a “digital concierge” for the workforce is set to undergo a pilot test by the Defense Information Systems Agency (DISA), as disclosed by an agency official today.
DISA’s Chief Technology Officer and Director of the Emerging Technology Directorate, Steve Wallace, highlighted the potential of an AI digital manager to interact with Controlled Unclassified Information (CUI) documents and various sources. By integrating these into a seller database, the large language model can be leveraged to provide users with relevant answers.
Wallace first introduced the concept of employing AI as a “digital manager” during a press briefing in November at the DISA Forecast to Industry event. He emphasized the broad utility of big language models in enhancing various aspects of job functions within the organization.
Addressing the functionality of the AI concierge, Wallace explained that DISA personnel would be able to inquire about standard documents, facilitating knowledge-sharing and streamlining information access among users.
While Wallace foresees the prototype commencing its trial phase in the first quarter of this year, the agency is currently addressing certain safety concerns before full implementation can proceed. He expressed optimism about the potential timeline, aiming for a launch ideally by June, contingent upon the resolution of ongoing issues.
In a previous statement to reporters, DISA’s Software Executive Officer for Cyber, Brian Hermann, underscored the role of AI in supporting defense cyber operator analysts. Hermann indicated that AI could automate a significant portion of the information reviewed by analysts, allowing them to focus on more complex challenges efficiently.
As DISA explores the integration of AI technologies, the Department of Defense (DoD) has been actively promoting responsible AI adoption. The DoD’s Data, Analytics, and AI Adoption Strategy, released in November, aims to accelerate the implementation of AI capabilities across the department, emphasizing the significance of large language models in this strategic endeavor.
