Air Force looks to industry to provide AI ‘toolkit’ for cloud-based C2 capability
The Air Force is expanding its outreach to contractors to explore how different automation and AI technologies could be integrated into its command-and-control modernization efforts.
The service’s integrated program executive office for command, control, communications and battle management (C3BM) issued a sources-sought notice Monday on Sam.gov for an “artificial intelligence and machine learning toolkit” that could improve reaction times.
Specifically, the service wants to apply the so-called toolkit to its cloud-based command and control (CBC2) effort. The Air Force is casting a broad net for capabilities that could be included in the toolkit, underscoring that AI and ML technologies can be used for different applications and problems, according to the request for information.
“This effort shall be a collection of tools and technologies that improve tactical C2 software applications under development within multiple programs (e.g., Cloud-Based Command and Control) and reduce operational workflow timelines for C2,” the RFI stated.
CBC2 is a key component of the Air Force’s Advanced Battle Management System initiative and the Pentagon’s Joint All-Domain Command and Control (JADC2) effort. The warfighting concept aims to connect sensors and shooters from across the U.S. military and international partners under a single network, enabling faster and more effective decision-making and employment of forces.
The Air Force delivered an initial operating capability of CBC2 to the North American Aerospace Defense Command’s Eastern and Canadian air defense sector in October 2023. The service plans to continue scaling that capability to other air defense sectors throughout this year.
The platform integrates hundreds of critical air defense radar and data feeds under one cloud-based interface, then develops courses of action from which leaders can quickly make high-quality decisions. Artificial intelligence and machine learning are used to assist commanders in the decision-making process and help maintain situational awareness
Now, the RFI indicates that the Air Force is interested in incorporating other advanced and commercialized AI and ML technologies — including data collection and curation; machine-to-machine operations; large language models; and continuous and reinforced learning training models.
A full statement of objectives was not publicly available on Sam.gov because some of the information related to the notice was “controlled” access.
Responses to the RFI are due April 26.
