Government agencies are under pressure to explore AI, but many struggle to move beyond ad hoc employee use. Concerns around record retention, privacy, procurement, cybersecurity, transparency, and staff readiness often slow progress before implementation even begins.

This session introduces a decision framework called DIO — Detection, Impact, and Oversight — as a method for evaluating AI use cases, prioritizing automation opportunities, and determining the right level of human review to support responsible, defensible adoption.

Audience takeaways — You will be able to: 

• Understand why AI adoption in government often stalls across compliance, procurement, cybersecurity, workforce readiness, and public accountability.

• Apply the DIO framework to assess whether an AI use case is appropriate for automation based on detectability of errors and severity of consequences.

• Utilize a model for right-sizing oversight so agencies can move beyond blanket human-in-the-loop policies and apply review, sampling, or stricter controls based on actual risk.