The Time Bomb in Federal AI Strategy: Why Caution Today Creates Danger Tomorrow
The U.S. government's deliberate pace in adopting artificial intelligence creates a dangerous paradox — the slower agencies integrate AI today, the more likely they'll be forced into a hasty, high-risk implementation during future crises, according to new research.
This counterintuitive "rushed adoption time bomb" represents one of the most significant overlooked risks in federal technology strategy, End of Miles reports, based on findings from a comprehensive study released this month.
The safety illusion of going slow
"Gradual adoption is significantly safer than a rapid scale-up," writes Lizka Vaintrob in the Forethought Research report titled "The AI Adoption Gap." Yet the security expert warns that what appears safer in the short term creates dangerous conditions later. "Moving slowly today raises the risk of rushed adoption later on. Pressure to automate will probably keep increasing."
"In a crisis — e.g. after a conspicuous failure, or a jump in the salience of AI adoption for the administration in power — agencies might cut corners and have less time for security measures, testing, in-house development." Forethought Research report
The policy analysis highlights how agencies that integrate AI systems gradually gain critical advantages: time to build internal expertise, develop proprietary tools, invest in appropriate safeguards, and test automation systems iteratively. These safety measures become impossible in emergency implementation scenarios.
A worsening landscape for late adopters
The research identifies three factors that make this time bomb increasingly dangerous as time passes. First, frontier AI development will likely concentrate in fewer companies, leaving government with diminishing bargaining power. Second, the technological gap between private companies and government agencies will grow wider, complicating oversight of private partners.
Most concerning, according to the report, advanced AI systems will become "more capable (and likely more agentic), making them more dangerous to deploy without robust testing and systems for managing their work."
"Background risks will increase over time... And a broadly more volatile international and economic environment may make failures especially costly. So earlier adoption seems safer." AI Adoption Gap study
Warning signs already visible
The analysis points to concerning evidence this scenario is already developing. Private-sector job listings are four times more likely to mention AI than public-sector listings, with the divide widening. Surveys show public-sector professionals report using AI significantly less than most Americans.
While some departments like Defense account for 70-90% of federal AI contracts, civilian agencies lag dramatically behind, setting up potential crisis scenarios when they attempt to catch up quickly.
The technology gap creates a ticking clock, the researcher warns. If agencies wait until advanced AI becomes indispensable for core government functions, they'll face impossible tradeoffs between functionality and safety.
Preparing for inevitable pressure
To defuse this time bomb, the report recommends building "emergency AI capacity" outside government, including standby response teams of AI experts who could be quickly seconded into government roles during crises.
The analysis also suggests developing standardized protocols for rapid but safer AI integration and creating specific tools that federal agencies could deploy quickly when needed.
"Hasty integration of AI in the US government would go better if we prepared for it in advance (even if that preparation happens outside the federal government)." Forethought Research
Without such preparation, the researcher concludes, the government risks a future where critical AI adoption happens under the worst possible conditions: maximum time pressure, minimal security infrastructure, and limited technical knowledge – a perfect storm for catastrophic implementation failures.
