The U.S. Department of the Navy has released an updated list of technology priorities for the next several years, outlining five broad categories it wants companies and investors to build around — a signal designed to steer private capital toward defense-relevant sectors before the Navy opens its checkbook.
Justin Fanelli, the Department of the Navy's chief technology officer, shared the document with TechCrunch, noting that its publication this year was partly a response to investor feedback. When the Navy first released a similar priorities list last year, he said, investors told him it changed how they thought about the Navy's buying plans.
The five categories are applied AI, quantum information science, advanced networking, electromagnetic spectrum operations, and digital engineering and interoperability. The document was jointly issued by Fanelli's office and the Portfolio Acquisition Executive for Mission Systems.
Applied AI covers machine learning and agentic software meant to convert raw data into decisions — including sensor fusion, targeting support, autonomous behavior, and cyber operations built on software rather than hardware. Quantum information science focuses less on owning quantum hardware and more on applying quantum or quantum-adjacent techniques to navigation, secure communication, and cryptography.
Advanced networking targets the secure movement of data across degraded or intermittent environments, whether on a ship at sea or across a coalition partner's network. Electromagnetic spectrum operations covers technology that can sense and manage the spectrum itself in contested conditions. Digital engineering and interoperability addresses the underlying plumbing: open APIs, model-based systems engineering, and zero-trust architecture meant to allow Navy systems to communicate without custom integration work each time.
The memo notes explicitly that none of the categories represent a funding commitment, that no individual programs are ranked, and that the priorities "will change based on emergent, near-term, and long-term needs."
Fanelli said the Navy spends "in the $150 billion range every year," though he distinguished that figure — total Navy purchasing — from narrower forms of direct investment. Taking an equity stake in a company, he said, remains rare; co-investment more often means the Navy waits for companies to mature a product commercially before buying it.
The stage of company the Navy targets has shifted accordingly. "We mostly buy Series D through F type companies," Fanelli said, adding that the Navy used to fund its own early-stage research to cover the seed-through-Series-B gap — a role it is now trying to hand to commercial investors.
Fanelli cited several recent contracts as illustrations of that approach. A $562 million contract was awarded this month for the MQ-25 Stingray, an autonomous refueling drone designed to extend the range of carrier-based fighter jets. The Navy has also purchased edge compute hardware from Armada, brought in Gecko Robotics for inspection work previously done manually, and contracted Domino Data Lab to run its machine learning pipeline.
In one case Fanelli highlighted, the Navy replaced a defense contractor's years-delayed shipboard camera system with commercial cameras paired with software from Applied Intuition, cutting roughly four years off the timeline and expanding deployment to more ships than originally planned.
The priorities document is this year's iteration of what Fanelli described as a "demand signal" — a roadmap companies and investors can use to align near-term product decisions with where Navy spending is likely to flow in a few years. Whether that signal translates into contracts still depends on whether new tools can replace or "turn off" something the Navy is already paying for, a dynamic Fanelli has previously described as the most common reason promising technologies fail inside the service.
Disclaimer