US Navy’s Tech Wish List Points Founders Toward AI, Quantum and Defense Infrastructure

Navy CTO Justin Fanelli told TechCrunch the service is trying to make itself easier for startups to work with, moving away from a confusing set of entry points toward a more focused funnel. The updated priorities list is meant to help founders and investors understand where Navy demand may be headed over the next several years.

The key takeaway: this is less a promise of immediate funding than a market signal. Startups should treat it as guidance for product roadmaps, partner strategy and timing.

Fanelli said the Navy spends in the $150 billion range annually, while distinguishing total purchasing from direct equity investment. The service is trying to move toward co-investment alongside private capital, often waiting for companies to mature products commercially before buying them.

He said the Navy mostly buys from Series D through Series F-type companies, while looking to commercial investors to cover more of the earlier seed-through-Series-B gap. For founders, that points to a familiar defense-tech challenge: build something commercially credible before expecting large-scale adoption.

The examples cited include a $562 million MQ-25 Stingray autonomous refueling drone contract, edge compute hardware from Armada, inspection work from Gecko Robotics, and machine learning pipeline work from Domino Data Lab. Fanelli also described replacing a delayed shipboard camera system with commercial cameras and Applied Intuition software, cutting roughly four years from the timeline and expanding to more ships than expected.

These examples suggest the Navy is looking for technologies that solve operational problems, reduce timelines or replace harder manual processes. They also show that commercial tools can enter Navy workflows when they meet a clear need.

The Navy’s updated internal list identifies five broad priorities: applied AI, quantum information science, advanced networking, electromagnetic spectrum operations, and digital engineering and interoperability. Applied AI includes machine learning, agentic software, sensor fusion, targeting support, autonomous behavior and cyber operations.

Quantum priorities focus on navigation, secure communication and cryptography, while advanced networking targets secure data movement in degraded or intermittent environments. Digital engineering and interoperability covers open APIs, model-based systems engineering and zero-trust architecture.

The memo notes that the listed priorities are not funding commitments and do not rank individual programs. It also says priorities can change based on emergent, near-term and long-term needs.

That matters because Fanelli has previously said promising technologies often fail inside the Navy for budgetary reasons rather than technical ones. A tool is more likely to stick if it can replace or turn off something the Navy already pays for.