“Human in the Loop” (HITL) is considered a requirement for all current Generative AI models, since we cannot yet trust them enough to really perform actions fully independently. But the question is: what does “Human in the Loop” mean in practice?

This is not an easy question to answer, as reported by those currently integrating AI Agents in their business workflows (see for example here with some recent information from Amazon, Google, IBM and Microsoft). And possibly a better approach is to start from what can be called “Human Accountability end to end,” so that humans are accountable for the entire business workflow, including all steps performed autonomously by AI Agents but without the need to directly verify each single step of their actions.

Unfortunately, Accountability is not easy to manage either, and in some cases even to attribute.