- DOW CDAO Cameron Stanley has cited new use cases for the AI-enabled Maven C2 system
- MSS has replaced numerous legacy IT tools used for military data analysis
- The 2026 Intel Summit will explore agentic AI, OSINT and quantum risk
Cameron Stanley, the Department of War’s chief digital and artificial intelligence officer and a 2026 Wash100 awardee, said DOW continues to identify additional uses for Maven Smart System, or MSS, including logistics, supply chain, force readiness and budgeting data, Defense One reported Wednesday.
As DOW expands AI-enabled platforms like MSS into new mission areas, government and industry leaders will gather to examine how AI is reshaping military intelligence operations. The Potomac Officers Club’s 2026 Intel Summit on Sept. 24 will feature a panel discussion on elevating intelligence operations with AI, alongside sessions on open source intelligence, agentic AI and quantum risk, cybersecurity in the agentic AI era, and more. Register now to join the conversation.
Speaking at a cybersecurity summit in Washington Tuesday, Stanley said MSS is expanding from its original intelligence-operations role into force disposition, modeling and simulation, part of what he called a “horizontal integration” of data across the department’s directorates. He added that the recent war with Iran highlighted the need for better visibility into the department’s munitions inventory.
What Is Maven Smart System?
Maven Smart System is the Pentagon’s AI-powered command-and-control system, developed under the Project Maven initiative launched in 2017. Palantir Technologies serves as the platform’s prime software integrator, fusing sensor and intelligence feeds into a single interface that lets users identify targets, weigh response options and track outcomes without switching systems. MSS is used across the Joint Staff, combatant commands and other department and intelligence community elements, supporting the Pentagon’s Combined Joint All-Domain Command and Control effort.
Stanley said MSS has already replaced “six, eight, ten” separate IT systems that military personnel previously relied on to analyze data, with the department working toward what he called a “golden thread” connecting sensor data, aggregation, visualization and decision-making.
What Did Stanley Say About GenAI.mil & Procurement Timelines?
Stanley also cited GenAI.mil, the department’s central AI tool portal, noting it recently added offerings from OpenAI and xAI alongside Google’s Gemini, calling it “real, no-kidding frontier AI algorithms, and the full user experience, inside of a government environment.”
On acquisition, he said use of other transaction authority and digital marketplaces has cut vendor selection timelines “from months to single-digit days.” He pointed to Tradewinds as a tool that “satisfies the competitive requirement” through short videos rather than lengthy requests for information and requests for proposals.
Stanley added that the department is piloting AI to help draft routine contract language, noting about 90 percent of terms in OTAs or Federal Acquisition Regulation-based agreements are standard. He also said authority-to-operate approvals, which can take up to 18 months, are under review to speed the process.
“Basically, we need to make better decisions faster with data,” Stanley said. “Everything seems confusing until you break it down to making better decisions faster.”
What Else Is the Pentagon Doing to Scale AI Across the Department?
Maven’s expansion is part of a broader shift CDAO Cameron Stanley has described as moving from strategic enablement to disciplined delivery, with the aim of getting AI tools to users across every workload rather than a handful of pilot programs.
That shift is showing up in how existing tools are organized. CDAO is relocating its GAMECHANGER policy search tool onto GenAI.mil, folding it into the department’s central AI platform rather than leaving it on a separate system.
On the autonomy side, the office has selected 25 companies for the Crucible 2 Swarm Forge event, part of an effort to test and field autonomous systems more quickly.
Stanley has also pressed industry to deliver faster and more effectively. Contracting activity has moved in step with that expectation, as Scale AI’s CDAO production OTA ceiling recently grew fivefold to $500 million.
