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Most critical software today works, maintained by talented engineers using testing, code review, and hard-won experience. The problem is not that everything is broken. It is that AI is changing the scale and speed of software production faster than our ability to verify it. What works at human pace may not survive AI pace.
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The Penn-Wharton model found in a preliminary analysis that AI could reduce deficits by $400 billion by 2035. But the Congressional Budget Office framed AI and associated investment as wild cards in determining the U.S. fiscal and economic outlook. While the CBO projects AI will enhance total productivity by 1% in the next decade, its most recent budget report conceded that this prediction was “highly uncertain.” If adoption is slow or costs higher than anticipated, it would significantly alter GDP growth and, consequently, government revenue.