In a Washington D.C. study, citizens expressed a desire for personal AI agents to help them navigate complex regulations and paperwork. This reveals a key user need: people want AI as a personal advocate against systemic complexity, not just as a tool for institutional optimization.

Historically, time and cost acted as a natural defense against overwhelming systems. AI agents can now execute millions of tasks—like filing legal motions or making lowball offers—for nearly free, threatening to collapse systems not built for this scale.

Processes like grant writing and college admissions rely on formulaic, 'bullshit work' that AI excels at. The inevitable flood of AI-generated 'slop' applications will make human review untenable, forcing these legacy systems to either fundamentally reform their evaluation criteria or collapse under the volume.

Contrary to expectations, the wealth of information from AI tools is not making governance easier. Leaders are experiencing information overload, which obscures rather than clarifies go/no-go decisions. The challenge is shifting from data generation to data synthesis and evaluation.

The current use of AI chatbots for advice is just the beginning. The next evolution, agentic AI, will act as autonomous 'butlers' that can not only draft but also file appeals and manage interactions on a user's behalf. Unlike humans, these agents will never get frustrated or give up, creating relentless pressure on government systems.

AI dramatically lowers the barrier for individuals to file professional, legally-sound complaints against corporations or government agencies. While empowering, this could swamp the "adversarial touchpoints"—the limited number of human reviewers—potentially degrading service quality and slowing down redress for everyone.

Current AI tools are empowering laypeople to generate a flood of low-quality legal filings. This 'sludge' overwhelms the courts and creates more work for skilled attorneys who must respond to the influx of meritless litigation, ironically boosting demand for the very profession AI is meant to disrupt.

While AI can identify legal technicalities to help individuals file lawsuits, the aggregate effect is a flood of litigation that bogs down the court system. This creates a negative second-order consequence that can outweigh the individual benefits.

An unintended consequence of AI is clients using it to fill out agency onboarding forms. Instead of providing genuine insights, they submit generic, AI-generated text. This 'slop' makes it harder for agencies to get real answers, undermining the efficiency AI was meant to create.