Someone has to be on the hook

Picture a business development coordinator drowning in scheduling and inbox glue-work. The easy move is to hand her an agent and call the automation done. A better one is to spend a few weeks working out, together, what the agent should actually take over and what stays hers. She doesn't feel replaced. She feels free of the glue-work, ready to go after the role she actually wanted.

That only works because of what does not happen. The role does not disappear into a queue with no owner. Someone stays on the hook for it: first her, then a system built with her, reviewed by a person.

The model was never the hard part

In most enterprise AI rollouts, the technical staging — connecting the tools, wiring an MCP server into the ERP — is the easy phase. The hard phase is political: an AI-skeptic exec who needs proof before trusting the number, an IC doing the job twice as fast as anyone will admit because leaving it half-automated feels safer than naming what it replaced. Software does not resolve either. A person does, by being named, reachable, and accountable for what the software gets wrong.

Two failure modes, same cause

Automate a function with nobody accountable for the exception, and one of two things happens. The exception gets ignored: the miss nobody catches. Or the person whose job it was quietly keeps doing it in parallel, afraid to say so. Both come from the same gap: nobody wrote down who is on the hook when the routine case turns unusual.

What a named person actually buys you

Every Bonofici standard has one: a named person accountable for the exceptions and the review, in your Slack, not a support queue. When a job misses, it is redone free, because someone signed up to catch it before it reached you. That is the difference between an agent your team has to supervise and a function that runs without them in the middle.