The traditional government model of setting a regulation and waiting years to assess it is obsolete for AI. A new approach is needed: a dynamic board of government, industry, and academic leaders collaborating to make and update rules in real-time.

Facing growing moral panic, the AI industry's plan appears to be moving so fast that regulation becomes impossible. By building data centers and deploying models at breakneck speed, companies aim to make their technology ubiquitous before any effective policy can form.

Formal standards development organizations (SDOs) like the ISO operate on a 12-24 month timeline. This deliberate, consensus-based process is too slow to keep pace with the rapid evolution of AI technology, creating a governance gap that requires more agile, iterative approaches.

Security leaders don't wait for government mandates; they adopt market-driven standards like SOC 2 to protect their business and customers. AI governance is following a similar path, with companies establishing robust practices out of necessity, not just for compliance.

Healthcare is a model for AI governance beyond its regulatory framework. The industry has a pre-existing infrastructure of trust, experience with diverse use cases, established practices for post-deployment monitoring, and a deep understanding of human-in-the-loop systems, all directly applicable to AI.

The initial thesis was that AI governance would mirror data governance, driven by regulations like GDPR. However, the field now resembles cybersecurity, characterized by incident response, technical assessments, and a constant battle between advancing AI capabilities and necessary oversight mechanisms.

Unlike traditional internet protocols that matured slowly, AI technologies are advancing at an exponential rate. An AI standards body must operate at a much higher velocity. The Agentic AI Foundation is structured to facilitate this rapid, "dog years" pace of development, which is essential to remain relevant.

Because AI is so new, there are no established best practices or regulations for its use. This creates a critical but temporary window where every organization's choices matter more. The precedents set now by early adopters in business, government, and education will significantly influence how AI is integrated into society.

The rapid pace of AI development has outstripped government's ability to regulate. In this vacuum, the idea of AI companies writing their own binding constitutions emerges. While not a substitute for democratic oversight, these frameworks are presented as a necessary, if imperfect, mechanism to impose limits on corporate power before formal legislation can catch up.