AI agents are easy to build. Accountability is harder.

A lot of the AI agent conversation right now is about capability. What can the agent do? How autonomous can it be? How many tasks can it complete end-to-end? Working on agent infrastructure for small business operations, I keep landing somewhere different. The hard problem is not what the agent can do. It is who stays accountable for what it does. In a restaurant, warehouse, or any operating business, every action has an owner. The labor decision belongs to the GM. The vendor escalation belongs to the operator. The food safety call belongs to whoever is on the floor. Authority is structural, not optional. An agent that takes action without preserving that structure does not reduce the operator’s load. It creates a new kind of uncertainty: Who is responsible when the agent gets it wrong? That is why I think the real design problem for small business agents is governance, not capability. Which actions can the agent take on its own? Which actions require operator confirmation? Which actions are off-limits regardless of confidence level? Who reviews what the agent did? How does the operator override or correct the system? Capability is the easier part. Bounded action, role-aware authority, and a clear human in the loop are what determine whether an operator actually trusts the system. For small businesses especially, the agent’s job is not to be more autonomous than the operator. It is to make the operator’s authority more leveraged. What is the most important action in your business that you would never want an agent to take without explicit human approval?