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Home » AI Agent & Copilot Podcast: CIO Perspective on DOGE Use of AI To Scrutinize Government Spending
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AI Agent & Copilot Podcast: CIO Perspective on DOGE Use of AI To Scrutinize Government Spending

Tom SmithBy Tom SmithFebruary 12, 2025Updated:September 29, 20252 Mins Read
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Welcome to the AI Copilot Podcast, analyzing the latest AI Copilot and agent developments from Microsoft and its partners, delving into customer use cases, and exploring how AI plus the Cloud helps customers reimagine their business. In this episode, Kenny Mullican, CIO at plastics manufacturer Paragon Films, discusses the use of AI in the new Department of Government Efficiency (DOGE) run by Elon Musk.

Highlights

AI Agent & Copilot Summit is an AI-first event to define opportunities, impact, and outcomes with Microsoft Copilot and agents. Building on its 2025 success, the 2026 event takes place March 17-19 in San Diego. Get more details.

AI in Government: Introduction and Report Overview (01:14)

A recent report stated that DOGE is using AI to analyze every dollar spent by the US Department of Education. Mullican notes the charged nature of AI discussions and the potential benefits of AI in financial analysis.

Commercial AI Applications and Data Security (03:02)

Mullican says the use of AI for financial data analysis is common, even before the advent of GenAI, noting the importance of security when using AI, particularly with sensitive financial data, and mentions the need for proper safeguards. The report identifies types of data being analyzed, including personally identifiable information (PII) and sensitive financial data.

Security and Privacy Concerns in AI Applications (08:07)

Mullican emphasizes the importance of proper setup and safeguards when it comes to using AI software. Mullican cites companies including Microsoft, whose Azure cloud service is reportedly being used by DOGE, and expresses confidence in its security based on his company’s evaluation. He points to the need for ethical and responsible AI use, particularly in sensitive areas like HR, to avoid introducing bias, as well as the importance of transparency, accountability, and proper oversight in AI applications.

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