Defining Execution Boundaries: The Foundation for Responsible AI

As AI systems increasingly operate in the physical world, the challenge shifts from building capable models to ensuring decisions remain traceable and responsibility boundaries stay explicit. This design framework proposes declaring execution limits first, then expanding autonomy only where human oversight is maintained. By systematically separating intent, state, and effect, organizations can preserve control while enabling more effective and trustworthy AI deployment.