Research Summary: Characterizing Agentic Flooding of Government Services

The integration of AI agents, particularly Large Language Models (LLMs), is enhancing public interaction with government services by simplifying applications, policy comprehension, and opinion submission. This improved accessibility, while beneficial, introduces a novel risk termed 'agentic flooding,' where AI-driven surges in demand could overwhelm unprepared government services. Research suggests this phenomenon is already occurring widely across various jurisdictions.

Why it matters

The proliferation of AI agents in public interaction with governmental bodies presents both opportunities for enhanced service delivery and significant risks of operational overload. Understanding and mitigating 'agentic flooding' is critical for maintaining service continuity, resource allocation efficiency, and public trust in digital government initiatives. Failure to address this could lead to service disruptions and increased operational costs.

Key insights

• AI agents facilitate public interaction with government services, improving accessibility for tasks like applying for benefits and understanding policies.
• This increased accessibility can lead to 'agentic flooding,' defined as surges in demand that strain government services.
• Agentic flooding is likely occurring widely today, primarily driven by the inexpensive generation of text by LLMs.
• A dataset of 84 potential flooding cases across 11 jurisdictions indicates the current prevalence of this issue.
• A risk matrix is being developed to evaluate the exposure of specific government services to agentic flooding.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.16603