An AI system recommends an action. A person reviews the reasoning, considers the context and decides whether to proceed. That interaction captures one of the central questions facing organizations today: As AI moves from generating answers to taking action, how do we determine how much autonomy to give it? The
“It’s not a technology problem. It’s a process problem.” “It’s not an accuracy issue. It’s an adoption issue.” “It’s not the model. It’s the human.” Sound familiar? I hear these arguments all the time. But here’s the reality: generative AI has an accuracy problem. In fact, it is well documented
Much of the conversation around agentic AI focuses on autonomy. How much work can an agent complete on its own? How many decisions can it make? How far can organizations remove people from the process? Those questions make sense, but they can also obscure where businesses are finding value today.
