The critical national security risk for the U.S. isn't failing to invent frontier AI, but failing to integrate it. Like the French who invented the tank but lost to Germany's superior "Blitzkrieg" doctrine, the U.S. could lose its lead through slow operational adoption by its military and intelligence agencies.

A key threshold in AI-driven hacking has been crossed. Models can now autonomously chain multiple, distinct vulnerabilities together to execute complex, multi-step attacks—a capability they lacked just months ago. This significantly increases their potential as offensive cyber weapons.

Defenders of AI models are "fighting against infinity" because as model capabilities and complexity grow, the potential attack surface area expands faster than it can be secured. This gives attackers a persistent upper hand in the cat-and-mouse game of AI security.

The same AI technology amplifying cyber threats can also generate highly secure, formally verified code. This presents a historic opportunity for a society-wide effort to replace vulnerable legacy software in critical infrastructure, leading to a durable reduction in cyber risk. The main challenge is creating the motivation for this massive undertaking.

AI tools aren't just lowering the bar for novice hackers; they are making experts more effective, enabling attacks at a greater scale across all stages of the "cyber kill chain." AI is a universal force multiplier for offense, making even powerful reverse engineers shockingly more effective.

Securing a lead in computing power over rivals is not a victory in itself; it is a temporary advantage. If that time isn't used to master national security adoption and win global markets, the lead becomes worthless. Victory is not guaranteed by simply having more data centers.

AI tools drastically accelerate an attacker's ability to find weaknesses, breach systems, and steal data. The attack window has shrunk from days to as little as 23 minutes, making traditional, human-led response times obsolete and demanding automated, near-instantaneous defense.

The long-term trajectory for AI in cybersecurity might heavily favor defenders. If AI-powered vulnerability scanners become powerful enough to be integrated into coding environments, they could prevent insecure code from ever being deployed, creating a "defense-dominant" world.

The old security adage was to be better than your neighbor. AI attackers, however, will be numerous and automated, meaning companies can't just be slightly more secure than peers; they need robust defenses against a swarm of simultaneous threats.