A former Tesla engineer, now serving as the director of Technology Transformation Services (TTS), has outlined an "AI-first strategy" for a US government department, according to a report from Wired. Thomas Shedd, a close ally of Elon Musk, presented the plan to run the office like a "startup software company" during a Monday meeting, citing the need for cost-cutting measures amid a potential 50% budget cut.

The TTS, a division of the General Services Administration, is tasked with helping federal agencies improve their technology practices. Shedd's proposal aims to build a centralized government contract database designed for AI analysis, which would enable the department to streamline operations and reduce costs. This approach sits comfortably at the intersection of smaller government and increased AI reliance, a mantra advocated by Silicon Valley investors and executives rising through the government ranks under the Trump administration.

The move comes as the department faces significant budget constraints, with The New York Times reporting that it is eyeing a 50% budget cut. In this context, Shedd's AI-first strategy is seen as a means to achieve cost savings while maintaining operational efficiency. However, the proposal also raises questions about the role of AI in government and the potential implications for jobs and decision-making processes.

The adoption of AI-centric approaches in government is not new, with various agencies exploring the use of machine learning and automation to improve services and reduce costs. However, Shedd's proposal marks a significant shift towards a more comprehensive AI-driven strategy, which could have far-reaching implications for the way government departments operate.

As the US government continues to grapple with the challenges of digital transformation, Shedd's AI-first strategy is likely to spark debate and discussion about the role of technology in government. While proponents argue that AI can bring about significant efficiencies and cost savings, critics raise concerns about job displacement, bias in decision-making, and the potential erosion of accountability.

As the details of Shedd's proposal continue to emerge, it remains to be seen how the US government will balance the benefits of AI-driven approaches with the need to ensure transparency, accountability, and fairness in its operations. One thing is clear, however: the integration of AI in government is an issue that will continue to shape the future of public administration in the years to come.