This episode argues that **AI resilience** in the public sector depends less on rapid adoption and more on the **strategic ability to exit** a service. Modern technology creates a **concentration risk** where various tools often rely on the same few underlying models or cloud infrastructures, making organisations vulnerable to single points of failure. To combat this, the author suggests that **model substitution** and **data portability** must be treated as essential architectural requirements rather than legal afterthoughts. True operational freedom requires that prompts, workflows, and institutional knowledge remain **transferable between vendors** to prevent total dependency. Furthermore, maintaining a **manual fallback** and understanding how to function during service degradation ensures that essential public services remain stable. Ultimately, designing for a potential exit ensures that government entities retain **long-term sovereignty** over their digital infrastructure.
Read the full article: https://www.linkedin.com/posts/parsonsc\_artificialintelligence-ai-publicsector-ugcPost-7487408952805163008-WIu8
Narrated by NotebookLM
