Sea-Air-Space 2025: The Shift from Hull Autonomy to Swarm AI

Abstract: At the 2025 Sea-Air-Space Exposition, the U.S. Navy unveiled significant updates to Task Force 59's unmanned systems operations, marking a strategic inflection point from platform-centric autonomy to swarm-based AI orchestration. This shift represents not just a technological evolution, but a fundamental rethinking of how unmanned systems deliver operational value at the tactical edge.

Introduction

The Navy's approach to unmanned systems has reached a critical juncture. After years of investing in autonomous capabilities for individual platforms—from unmanned surface vessels (USVs) to autonomous underwater vehicles (AUVs)—the focus at Sea-Air-Space 2025 revealed a profound shift in thinking. The discussion is no longer about how smart individual hulls can be, but rather how effectively they can coordinate as an intelligent collective.

Task Force 59, the Navy's dedicated unmanned systems integration unit operating primarily in the Fifth Fleet area of operations, presented updates that signal this transition. The challenge is clear: individual autonomous platforms, no matter how sophisticated, cannot match the operational effectiveness of coordinated swarms leveraging distributed intelligence and edge computing.

For those of us who've watched Navy systems evolve—from traditional manned platforms to early autonomous experimentation—this represents a maturation of the unmanned systems concept. It's the difference between having smart tools and having a smart team.

From Individual Hull Autonomy to Collective Intelligence

The Limitations of Platform-Centric Autonomy

Early unmanned systems development focused on making individual platforms autonomous—teaching a single USV to navigate, avoid obstacles, conduct basic ISR (Intelligence, Surveillance, Reconnaissance), and return to base. This was a necessary first step, but it revealed fundamental limitations:

• Limited Operational Impact: A single autonomous platform, regardless of its sophistication, covers limited area and provides narrow situational awareness
• Vulnerability: Individual platforms are susceptible to detection, jamming, and neutralization
• Redundancy Gaps: Single-point failures eliminate the capability entirely
• Scaling Challenges: Adding more individual platforms doesn't create emergent capabilities—just more of the same

The Navy recognized these constraints. The question became: how do we move beyond simply deploying smart individual platforms to creating a coordinated system that's greater than the sum of its parts?

The Swarm Intelligence Paradigm

Swarm AI represents the shift from individual autonomous agents to coordinated collective behavior. In nature, swarms—whether bees, birds, or fish—exhibit emergent intelligence through simple rules and local interactions. No single agent needs to understand the entire mission; instead, collective behavior emerges from distributed decision-making.

For naval operations, swarm AI offers transformative capabilities:

• Distributed Sensing: Multiple platforms create a networked sensor web, dramatically expanding coverage and persistence
• Adaptive Formations: Swarms dynamically reconfigure based on threat environment and mission requirements
• Resilience: Loss of individual platforms doesn't degrade the swarm's overall effectiveness
• Coordinated Action: Platforms can execute synchronized maneuvers—surrounding, tracking, or overwhelming targets

Task Force 59's updates indicate that the Navy is moving toward this model, where unmanned platforms operate not as isolated agents but as nodes in a coordinated network.

The Edge Computing Imperative

Why Centralized Control Doesn't Scale

Traditional unmanned systems relied on centralized command and control—human operators making decisions remotely, often with significant latency. This model breaks down at scale for several reasons:

• Bandwidth Constraints: Transmitting high-fidelity sensor data from dozens of platforms saturates communications links
• Latency Issues: Decision loops measured in seconds or minutes are too slow for dynamic threat environments
• Operator Saturation: Human operators can't process information from and coordinate dozens of platforms simultaneously
• Communications Vulnerability: Adversaries can jam, intercept, or disrupt links, rendering centrally-controlled swarms ineffective

The solution? Push intelligence to the edge—equipping platforms themselves with the computational power to make coordinated decisions locally, without constant human intervention or centralized coordination.

Edge AI Architecture for Naval Swarms

Effective swarm orchestration requires a distributed AI architecture where:

1. Local Decision-Making: Individual platforms process sensor data and make tactical decisions autonomously
2. Peer-to-Peer Coordination: Platforms communicate directly with nearby units to coordinate behavior
3. Hierarchical Aggregation: Local coordination rolls up to higher-level mission objectives without requiring centralized control
4. Human-on-the-Loop: Operators set high-level objectives and rules of engagement; platforms handle execution

This architecture demands significant edge computing capability—ruggedized, power-efficient hardware capable of running sophisticated AI models in harsh maritime environments. It's a non-trivial engineering challenge, but one the Navy is actively addressing.

Communications-Denied Operations

Perhaps the most compelling argument for edge AI is the ability to operate in communications-denied or degraded environments. In contested waters, adversaries will attempt to jam GPS, disrupt satellite links, and interfere with radio communications. Swarms relying on centralized control become ineffective; swarms with distributed intelligence continue operating autonomously.

Task Force 59's emphasis on edge computing reflects this operational reality: future naval operations will occur in environments where platforms must think and coordinate locally, not depend on constant connectivity to a central controller.

Operational Implications for the Navy

Enhanced ISR and Persistence

Swarm-based unmanned systems fundamentally change the ISR game:

• Wide-Area Coverage: Distributed platforms create persistent sensor networks spanning vast maritime areas
• Multi-Phenomenology Sensing: Different platforms can carry different sensors (EO/IR, radar, sonar, SIGINT), creating a fused intelligence picture
• Adaptive Deployment: Swarms reconfigure to focus on areas of interest or respond to emerging threats

This persistent, wide-area ISR capability is particularly valuable in regions like the Fifth Fleet AOR (Middle East), where monitoring critical shipping lanes, detecting threats, and maintaining maritime domain awareness are constant operational requirements.

Force Multiplication and Cost Effectiveness

One of the Navy's persistent challenges is maintaining presence with a constrained fleet. Unmanned swarms offer force multiplication:

• Low-Cost Platforms: Individual unmanned platforms cost orders of magnitude less than manned ships
• Acceptable Attrition: Loss of individual platforms doesn't risk human lives and is economically sustainable
• Scalable Presence: Deploy swarms for persistent operations that would be cost-prohibitive with manned assets

However, this only works if swarms are operationally effective—which requires the swarm AI and edge computing capabilities Task Force 59 is developing.

Challenges in Rules of Engagement and Human Control

The shift to swarm AI raises complex questions about human control and rules of engagement:

• Decision Authority: At what point does a swarm make kinetic decisions autonomously vs. requiring human authorization?
• Accountability: When coordinated swarm behavior leads to unintended outcomes, who is responsible?
• Escalation Management: How do swarms de-escalate or disengage when situations change?

The Navy's approach appears to be "human-on-the-loop" for swarm operations—humans set objectives and boundaries, AI handles tactical execution within those constraints. This balance between autonomy and control will continue evolving as operational experience grows.

Technical Challenges and Path Forward

Data Fusion and Sensor Integration

Effective swarm operations require fusing data from heterogeneous sensors across multiple platforms in real-time. This demands:

• Standardized Data Formats: Common protocols for sharing sensor data across different platform types
• Distributed Fusion Algorithms: AI models that can combine partial, noisy data from multiple sources into actionable intelligence
• Time Synchronization: Precise timing to correlate sensor readings across platforms

Task Force 59's experimentation in the Fifth Fleet provides the operational testbed for maturing these capabilities.

Machine Learning at the Edge

Training and deploying ML models for edge deployment poses unique challenges:

• Model Optimization: Large AI models must be compressed and optimized for resource-constrained edge hardware
• Continuous Learning: Swarms need to adapt to new threats and environments; this requires updating models without constant connectivity
• Adversarial Robustness: Enemy forces will attempt to fool or deceive swarm AI; models must be resistant to adversarial inputs

The Navy is investing in AI model compression, federated learning (where models train on decentralized data), and adversarial training to address these challenges.

Interoperability and Standards

As the unmanned systems ecosystem grows—incorporating platforms from different vendors with varying capabilities—interoperability becomes critical. The Navy needs:

• Open Architectures: Modular systems where components can be swapped or upgraded
• Common Control Interfaces: Standard protocols for tasking and coordinating diverse platforms
• Vendor Agnostic: Avoiding lock-in to single vendors; fostering competition and innovation

The progress Task Force 59 has made in integrating platforms from different sources suggests the Navy is taking interoperability seriously—a lesson learned from previous integration challenges.

Conclusion: The Future of Naval Unmanned Operations

The updates from Sea-Air-Space 2025 make clear that the Navy's unmanned systems strategy has matured beyond individual platform autonomy to swarm-based collective intelligence. This is the right evolution—individual autonomous platforms were a necessary stepping stone, but swarm AI represents the operational capability the Navy needs for contested environments.

Task Force 59's role as the operational laboratory for these concepts cannot be overstated. The Fifth Fleet AOR provides real-world operational conditions—complex maritime traffic, diverse threat environments, communications challenges—that allow the Navy to mature swarm AI capabilities under realistic conditions.

From my perspective, having worked on Navy systems and understanding both the operational requirements and technical constraints, this shift represents a convergence of necessity and feasibility. The operational need for distributed, resilient, scalable unmanned capabilities has existed for years; what's changed is that edge computing, AI, and distributed systems technologies have matured to the point where swarm orchestration is achievable.

The challenges ahead are non-trivial—technical hurdles around edge AI, data fusion, and communications; operational questions about human control and rules of engagement; and organizational challenges around doctrine and training. But the path is clear: the future of naval unmanned operations is collective, distributed, and intelligent at the edge.

As we move forward, the measure of success won't be how autonomous individual platforms are, but how effectively swarms coordinate to deliver operational effects. Task Force 59's updates at Sea-Air-Space 2025 signal that the Navy understands this—and is building toward it.

The era of swarm naval operations is beginning.