AI & The Future of Modern Warfare

Panelists and Core Missions:

• Adam Brie (Skydio): Co-founder/CEO focused on AI-powered small, light drones for consumers, enterprise infrastructure inspection, public safety, and DoD; has delivered thousands of systems to the U.S. Army, Marines, and allies, with hundreds active daily in Ukraine.
• Brandon Tsang (Shield AI): Former Navy SEAL/President/Co-founder building the world's "best AI pilot" to enable aircraft operation without GPS, communications, or in swarms; currently deploying on small quadcopters, medium "V-BAT" UAVs, and fighter-type aircraft.
• Brian Schimpf (Anduril): Co-founder/CEO of Anduril, focusing on counter-drone systems and unmanned platforms; aims to simplify operator lives through applied AI while anticipating the next 20–30 years of defense.

Strategic Gaps and Priorities for Military AI:

• Scale and Mass: Brian Schimpf identifies automation of repetitive tasks (mission planning, image analysis) as the primary immediate need to achieve scale and mass, moving beyond manpower-limited models to handle high-volume, high-speed warfare.
• OODA Loop Acceleration: Brandon Tsang emphasizes AI's role in compressing the "Observe, Orient, Decide, Act" loop, a critical factor for winning future conflicts against adversaries like China and Russia.
• Four Critical Growth Areas: Tsang outlines four pillars where AI is essential:
  • Autonomy: Essential for operating in contested electronic warfare environments where GPS and communications are jammed.
  • Battle Management: Creating decision engines to manage assets and munitions at speed and scale.
  • Hypersonics & Space: Leveraging AI to offset the "tyranny of distance" and collect intelligence rapidly.
• Human-AI Synergy: Adam Brie argues AI should not replace human judgment but rather leverage it, shifting the operator-to-drone ratio from teams of 5–10 to 1 operator controlling 100+ systems.

Commercial-Government Dynamics and Procurement:

• Adoption Friction: Brian Schimpf notes the U.S. government's software-to-hardware spend ratio is inverted compared to the private sector (e.g., Tesla, Google), with weapon programs often restricted to niche roles and long refresh cycles (15+ years).
• Model Shift Required: Successfully integrating AI requires a holistic shift in hardware composition, sensor integration, training, and development processes to match Silicon Valley's rapid iteration capabilities.
• Procurement Evolution: The Department of Defense is shifting from debating if to adopt these technologies to how to implement them, with recent success in bridging civilian tech (e.g., Skydio) to defense via the Defense Innovation Unit.

Ukraine Conflict as a Real-World Laboratory:

• Contested Electromagnetic Environment: Ukraine has demonstrated that constant radio and GPS jamming renders traditional drone reliance ineffective, forcing rapid innovation in autonomous navigation and reduced signal signatures.
• Asymmetric Cost-Benefit: The conflict revealed that distributed, low-cost assets (drones) can effectively neutralize high-value traditional assets (helicopters), driving international partners to reconsider force structures toward mass over single-platform reliance.
• Supply Chain Security: The conflict highlighted critical security risks of using commercial hardware like DJI, which Russian forces exploited to locate, track, and target Ukrainian positions, validating concerns over data integrity and hardware origins in national security contexts.