How Cyber Command is building its AI cyber war playbook

• Cyber Command is largely sidestepping that debate — building infrastructure designed to swap between models regardless of vendor or origin.
• "To survive anywhere, just in case our operators want an open-source made-in-China model or something very boutique, we have to create the infrastructure and that ability to be agile — no politics," Brig. Gen. Reid Novotny, chief AI officer at Cyber Command, told Axios.
• "Our operators are very well set for what they need right now."

State of play: The White House is still negotiating access to Anthropic's Mythos Preview, which the company has held back due to its hacking capabilities. Now, only a patchwork of agencies — including the National Security Agency and the Department of Commerce's AI testing institute, but not CISA — have access to the model.

• Meanwhile, OpenAI is capitalizing on the confusion and quickly engaging with federal, state and international government offices to deploy its competing product, GPT-5.4-Cyber.

What they're saying: "I'm zero percent concerned about politics," Novotny told Axios at the SANS AI Cybersecurity Summit in Arlington.

• "There are so many things we can do in the space right now: adopting newer technologies, going after companies that are model agnostic," he said.

Driving the news: 2026 marks the first year Cyber Command has dedicated funding for AI programs, after years of lead time inside the Pentagon and Congress.

• The command is using that funding to pilot commercial AI capabilities while building underlying infrastructure that allows operators to switch between models as technology evolves.
• Novotny said that flexibility extends even to models developed outside the U.S.

The big picture: Novotny — the first AI officer at Cyber Command — is tasked with integrating AI into both offensive and defensive cyber operations.

• That includes using models to accelerate operations and process large volumes of intelligence data, but also embracing a level of risk inherent in military missions.
• "The true point of our military, at some scope and scale, is to be less secure and a little bit more dangerous," he said during a panel.

Zoom in: A major concern externally is whether AI systems could misidentify or improperly target civilian infrastructure. But Novotny said those risks are governed by existing military rules, not new AI-specific policies.

• "If we train a model to go hack an entire country, we know going in about hospitals, schools and so on," he said.
• "We know what we need to do and not do, and then we prove it out, making sure the model is doing what we say," Novotny said. "I don't want to say we're not worried about it, but we know how to apply our morals and our laws when we adopt a new technology."

Reality check: Cyber Command is testing varying levels of human oversight, but fully autonomous deployment is off the table.

• "We would never unleash a human-out-of-the-loop tool and then be like, 'Oops, we just turned something on,'" Novotny said.

Between the lines: Former military leaders and industry operators say the bigger challenge is how quickly the command can put AI models to use.

• Lt. Gen. Lori Reynolds, former head of the Marine Corps Forces Cyberspace Command, said last week during Vanderbilt University's Asness Summit on Modern Conflict and Emerging Threats that AI is likely to strain the military's "persistent engagement" model, which was built around a small number of sophisticated adversaries.
• "It's insufficient by itself," Reynolds said. "We have to learn to fight hurt, we have to learn to trust our data, but we should be doing everything we can to constantly be sparring as far away from our territory as we can."

What to watch: AI's role in cyber warfare is expanding as vendors race to secure Pentagon contracts and adversaries like China integrate AI into their operations.

• Google has signed a deal with the Pentagon to use Gemini in classified government operations, according to The Information. Anthropic was first into the classified space, followed by OpenAI earlier this year.

Go deeper: The age of AI asymmetry