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In a new podcast with biographer Walter Isaacson, Elon Musk admits his government efficiency drive couldn't cut spending and now argues only automation, not political will, can address the national debt.
Elon Musk has delivered his own postmortem on DOGE, and it is not flattering. The Department of Government Efficiency, which Musk led during the early months of the second Trump administration, was supposed to be a model for slashing federal waste. Instead, Musk now says, it proved the opposite: that meaningful deficit reduction cannot happen through the normal machinery of government at all.
"There's no way we were gonna solve the deficit from within the government," Musk told biographer Walter Isaacson in an interview for Isaacson's new podcast series, "The Builders," premiering Tuesday. His proposed substitute is not a political fix. It's technological. "The only way we're going to solve the national debt is with AI and robots," Musk said. "We're not gonna solve it by trying to save our way there."
That is a notable reversal in framing. DOGE was pitched as a government-wide austerity effort, built on the premise that enough bureaucratic trimming could bend the fiscal curve. Musk now argues the political system simply will not allow it. "The appetite is not there at the presidency, the House, the Senate or the judiciary," he said. "Basically, no one in authority in the government whatsoever, with maybe a few rare exceptions like the Rand Pauls of the world, actually wants to reduce spending."
He went further, suggesting the obstacle runs through the Oval Office itself. "Maybe if the president made that his primary goal, we could do that," Musk said. "If you try to solve the deficit and stop wasteful spending, you make a lot of enemies. President Trump likes to be liked. He doesn't like people calling him, being upset about some funding being stopped."
Musk's comments amount to an admission that DOGE, at least in its original form, was a flop. That matters for anyone tracking federal spending policy, because it closes the door on one high-profile attempt at deficit control while opening another. Musk is effectively betting that a future administration, armed with more capable AI systems and automation, will succeed where DOGE could not.
The scale of the problem gives that bet some context. Federal deficits have proven politically untouchable for decades regardless of which party holds power, and Musk's own frustration, that even a well-resourced outsider effort inside the executive branch could not move the needle, is a data point worth taking seriously. If the political incentives described by Musk are accurate, then any future deficit solution will need to route around elected officials rather than through them. AI and automation, in his telling, are that bypass.

Musk also used the interview to reflect on his own conduct during the DOGE period, offering a rare note of self-criticism. "I kinda got carried away, basically," he said, adding that he was "gone for too long" from his companies. He said he should have operated more quietly behind the scenes and limited his formal involvement to "a month or two" rather than the roughly four months he spent in the White House. "I should have gone back and focused on AI a little sooner than I did," he said.
Isaacson pressed him on whether the West Wing experience had been seductive. Musk did not deny it. "It was, a little bit," he said. "I mean, it was kinda cool 'cause I'm just there in the Oval Office while all these big momentous decisions are being made." Asked about brandishing a chainsaw onstage at the Conservative Political Action Conference a month into Trump's second term, a gift from Argentina's Javier Milei, Musk called it "a weird weekend" and declined to elaborate further, saying only, "Let's let sleeping dogs lie or whatever."
The broader context is Isaacson's own evolving view of the AI builders he has spent years chronicling. Isaacson, author of the definitive 2023 Musk biography, launched "The Builders" specifically to press figures like Musk on the risks embedded in the technology they are racing to deploy. In a new preface to an updated edition of his 2014 book "The Innovators," published this week, Isaacson warns that Steve Jobs and other architects of the personal computer era would have approached autonomous AI agents, particularly those not tightly bound to human oversight, with far more caution than today's builders are showing.
Isaacson's assessment of Musk specifically is a mix of admiration and wariness. "Musk is an amazing engineer who is pushing us forward with Starship, Starlink, Neuralink, and autonomous EVs," Isaacson said. "But as I describe in my biography, I think he is too prone to darkness and conspiracies when it comes to politics and people. His complexities come through in the interview, as I hope they do in the biography."
The podcast series, produced by media company Kaleidoscope, extends beyond Musk to a roster that includes Peter Thiel, Alex Karp, Fei-Fei Li, and Dario and Daniela Amodei. A preview describes conversations in which these figures "open up about their ambitions, what frightens them, how they think about humanity, and what drives them to build so big and so fast," promising exchanges that are "intimate, charming, and sometimes chilling."
Musk's admission that DOGE could not solve the deficit from inside government is a concession worth weighing against his pivot to AI and robotics as the real fix. Investors and policymakers tracking automation's role in public finance should treat this as a signal that the next serious deficit push, if there is one, may look less like a bureaucratic reform effort and more like a technology deployment program. Whether that framing survives contact with the same political incentives Musk just described is the open question.
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Exclusive: Musk tells Isaacson "AI and robots" will need to fix deficit
↗ https://www.axios.com/2026/10/17/elon-musk-doge-walter-isaacson-podcast
About the author
Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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18 October 2026
24 articles
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