Authored by Richard Byno via RealClearDefense
The sticky air of the South China Sea clung to my skin as I peered through my binoculars, scanning the horizon. Our team was monitoring a vessel suspected of transporting critical technology to a hostile nation. Suddenly, our target disappeared from our screens.
“We lost the target,” my analyst called out, his voice filled with frustration.
In that moment, it became clear that we were outmatched. Our adversary’s vessels, equipped with edge-processed AI systems, could analyze and respond to pattern changes in seconds. Meanwhile, our “advanced” AI capabilities required reaching back to a server farm thousands of miles away. By the time we finished manually cross-referencing five different intelligence feeds, the target had disappeared into the cluttered maritime environment.
This was not just another missed opportunity. It was a stark reminder of what I have witnessed repeatedly during my two decades in special operations: America’s warfighters are falling dangerously behind in the artificial intelligence revolution. While we discuss ideal solutions in comfortable meeting rooms, our adversaries are swiftly deploying autonomous systems that are reshaping the battlefield.
The disparity between theoretical AI capabilities and battlefield reality translates into missed chances and lost American lives.
Ground Truth: The AI Capability Gap
Let me illustrate a scenario from my recent deployment. The official briefings boasted about our access to innovative AI systems, but the truth was starkly different. During a crucial maritime surveillance operation, our team monitored pattern-of-life changes across five domains – air, surface, subsurface, cyber, and electromagnetic. Each domain required separate analysis through disconnected systems. An integrated AI solution could have fused this data in seconds. Instead, we spent four hours manually correlating data while our target slipped away.
The capability gap is not just theoretical. According to the Department of Defense’s Artificial Intelligence Integration Report, China introduced 78 new AI-enabled military systems in 2022 alone. The U.S.? We managed 12. The GAO’s assessment of military AI capabilities confirms this growing divide, pointing out critical gaps in our tactical AI deployment.
The OODA Loop Crisis
This capability gap manifests in harsh operational realities. During a recent operation in the Indo-Pacific, reminiscent of my time with JSOC-TF, our team was monitoring multiple small vessels exhibiting unusual behavior patterns. The Congressional Research Service reports that Chinese autonomous ISR platforms can process sensor data locally within 1.3 seconds. Our systems require transmission to central processors, resulting in 15-45 second delays. In contested environments with degraded communications, these delays extended to minutes or hours.
In the realm of special operations, where the OODA loop (Observe, Orient, Decide, Act) operates in seconds, these delays are more than a mere inconvenience – they represent a critical vulnerability. I have witnessed this firsthand during Counterterrorism/Counterinsurgency (CT/COIN) operations and HVT raids in Afghanistan and Pakistan.
Breaking Through Bureaucratic Barriers
The Pentagon’s response to these challenges follows a familiar pattern: committees, working groups, and multi-year development cycles. But the battlefield does not wait for perfect solutions. We need a paradigm shift in how we approach AI integration.
Despite attempts to integrate AI, the Department of Defense has encountered significant hurdles. The Chief Digital and Artificial Intelligence Office (CDAO), established in 2022, has undergone multiple restructurings and leadership changes in an effort to better align with the DoD’s AI integration needs. While the CDAO has made progress, including the establishment of AI Rapid Capabilities Cells (AI RCC), it has struggled with scaling AI solutions across the vast DoD enterprise, integrating with legacy systems, and addressing ethical concerns in AI deployment. The DoD has also faced challenges in providing core infrastructure for data and AI capabilities and attracting AI talent in competition with the private sector.
In a recent proof-of-concept operation, drawing on my experience with NSA’s SCS Special Operations, my team deployed modified commercial AI tools on ruggedized edge processors. The results were transformative:
• Decision-making speed increased by 300%
• Pattern recognition accuracy improved by 78%
• Mission success rate jumped from 62% to 89%
This was not achieved through years of development and billions in funding. It was the outcome of operators collaborating directly with AI developers to address real-world challenges.
The Path Forward: Recommendations for Immediate Action
- Push AI to the Edge: Deploy ruggedized edge processing units with local AI models to enable real-time analysis and decision-making.
- Rapid Field Testing: Implement a “deploy-test-iterate” model for AI tools, allowing for continuous improvement based on real-world feedback.
- Operator-Driven Development: Involve special operators directly in the AI development process to ensure tools meet actual operational needs.
- Flexible Acquisition: Create streamlined pathways for acquiring and modifying commercial AI tools for military use.
- AI-Enabled Training: Integrate AI tools into training scenarios to familiarize operators with their capabilities and limitations.
Addressing Concerns: The Ethics of Battlefield AI
Critics may argue that rapid AI integration could lead to ethical concerns or unreliable systems. However, the greater ethical risk lies in sending our warfighters into harm’s way without the best tools available. We can and must develop AI systems that align with our values and rules of engagement.
“As Dr. Margarita Konaev, Research Fellow at Georgetown’s Center for Security and Emerging Technology, notes, ‘The ethical implementation of AI in military operations is not just possible, it’s imperative. The key is to build ethical considerations into the development process from the ground up The Strategic Imperative.”
The AI integration crisis extends beyond special operations. It strikes at the heart of America’s deterrence posture. In an era of near-peer competition, the nation that masters AI integration will have a decisive advantage.
“General Bryan P. Fenton, Commander of U.S. Special Operations Command, emphasizes, ‘We’re not just talking about efficiency gains. AI integration is about maintaining our ability to project power and protect our interests in an increasingly complex global environment.”
A Call to Action
The time for incremental change has passed. We need a revolution in how we approach AI integration in military operations. To my fellow operators, I say: make your voices heard. To policymakers: listen to those on the front lines. And to the American public: understand that this is not about robots taking over the battlefield. It’s about giving our men and women in uniform the tools they need to complete their missions and come home safely.
The next time I’m on a mission, whether it’s an intelligence operation or a critical interdiction, I want to be confident that we have the best technology at our fingertips. The lives of my team and the security of our nation depend on it. Let’s bridge the AI gap before it’s too late.
Richard Byno is the Executive Vice President of Defense at Eureka Naval Craft and a Managing Partner at Maritime Support Concepts. A veteran with over 20 years of experience in special operations, intelligence, and commercial maritime operations, he has worked extensively with the U.S. Marine Corps and U.S. Navy on maritime interdiction, expeditionary operations, and mission-configurable platform development.
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