AI Solutions Sought to Boost Navy Maritime Operations Centers' Decision-Making and Situational Awareness
The Defense Innovation Unit seeks AI/ML solutions to boost Navy Maritime Operations Centers' data fusion and decision-making. Industry proposals are due by June 6.
AI DIU Advances Navy’s Maritime Operations Centers with New AI Capabilities
The Defense Innovation Unit (DIU), based in Silicon Valley, has released a new solicitation focused on artificial intelligence (AI) and machine learning (ML) solutions to enhance the Navy’s Maritime Operations Centers (MOCs). These centers play a crucial role in fleet-level command and control, serving as the hub for how sailors coordinate distributed operations in future maritime conflicts.
The Navy’s Chief of Naval Operations Navigation Plan highlights MOCs as pivotal in converting vast data into actionable intelligence that offers commanders a decisive edge. These centers must integrate seamlessly with joint forces, allies, and partners, linking fleet commanders to a network of sensors, shooters, and effectors across the battlespace. Recognizing MOCs as critical weapons systems, the Navy aims for all fleet headquarters—starting with the Pacific Fleet—to achieve certification in key command functions by 2027.
AI’s Role in Enhancing Decision-Making
Navy leadership identifies AI as a key enabler to improve decision-making within MOCs. Vice Adm. Michael Vernazza, commander of Naval Information Forces, emphasized the potential of AI to accelerate the fusion of vast, multi-source data into coherent operational pictures that align with commanders' timing and decision cycles. This capability supports faster, more accurate responses by compressing the Observe-Orient-Decide-Act (OODA) loop vital to maritime operations.
The SAILS Program: A Targeted AI Initiative
DIU’s latest outreach seeks commercial AI/ML applications under the Situational Awareness by Intelligent Learning Systems (SAILS) program. The challenge is managing and analyzing large volumes of diverse tactical data—from space-based, shipboard, and airborne sensors to unstructured inputs like intelligence reports and watch logs—to improve situational awareness and resource allocation decisions.
- Accelerate the convergence of multi-source data inputs, including intelligence reports, satellite data, and common operational picture tools
- Enhance situational awareness and optimize decision support through track confidence scoring and real-time recommendations
- Automate watchfloor workflows by integrating with third-party software and data platforms via APIs
- Generate sensor and resource allocation recommendations considering communication bandwidth, geographic constraints, sensor reliability, and watchstander availability
- Offer natural language interfaces that allow users to adjust model parameters interactively while keeping decision processes interpretable and explainable
Additional technical requirements include role-based access control, cross-domain data sharing capabilities, compliance with NIST 800-171 cybersecurity standards, and support for deployment across various classified environments and infrastructure setups.
Industry Participation and Next Steps
Industry partners interested in contributing AI/ML solutions to the Navy’s MOCs can respond to the solicitation by June 6. This initiative represents a focused effort to incorporate advanced AI tools in maritime command centers, thereby improving operational effectiveness and resource management in distributed fleet environments.
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