Elon Musk said AI should be used to replace some inefficient functions carried out by US public-sector workers during the Milken Institute Global Conference.

An attendee reported that Musk characterized the US government as inefficient in a closed-door discussion with financier Michael Milken on May 4, 2025.

Musk also discussed developments at his brain-implant company Neuralink and space exploration firm SpaceX.

This conversation took place as he nears the conclusion of his role with the Department of Government Efficiency (DOGE), a project aimed at reducing the federal workforce and costs.

🔗 Source: Bloomberg

🧠 Food for thought

1️⃣ Modern government reform faces the same challenges as historical attempts

DOGE represents just the latest in a long line of efficiency initiatives dating back to the early 1900s, with at least 15 major reform attempts documented in U.S. history 1.

While DOGE claims to have saved approximately $160 billion by April 2025, this approach mirrors previous efforts like Reagan’s 1982 Grace Commission, which identified potential savings of $424 billion but struggled with implementation 2.

Historical evidence suggests the most successful reforms, such as the Clinton-Gore “Reinventing Government” initiative, succeeded by engaging federal employees rather than imposing top-down cuts 3.

DOGE’s unilateral approach contrasts with these collaborative models, raising questions about its long-term sustainability based on the mixed results of similar historical attempts.

The pattern across decades shows that effective government reform requires bipartisan support and buy-in from career civil servants, elements that appear to be missing from the current initiative 1.

2️⃣ AI’s government impact requires investment before savings

Musk’s call for AI to replace government workers aligns with research showing AI could automate over 40% of tasks performed by public-sector employees, potentially saving a fifth of their time 4.

However, experts estimate governments need substantial upfront investment, around £4 billion annually in the UK example, to implement AI effectively before realizing the projected £37 billion in annual savings 4.

The transition faces significant technical hurdles, as 77% of organizations are exploring AI implementation, but many government agencies struggle with outdated legacy systems and infrastructure limitations 56.