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The saving from automating junior work shows up this year. The cost shows up in five, as a missing layer of experienced people, in a different budget and often under a different chief executive. No single report shows both, which is why it's easy to miss. It is avoidable: decide which work people keep because it teaches, and the line doesn't have to bend.
Most automation decisions sort tasks by what the output is worth. Sort them by what doing the task taught as well, and every junior task lands in one of four places. Automate what taught nothing. Where the task was how people learned, let the software draft and keep a person deciding, or keep a share of the volume for people. The right-hand column is where the learning shock happens.
Once a person is past about seventy per cent busy, the exceptions waiting for them pile up faster than they can clear them, and most plans staff supervisors towards a hundred. The more reliable the automation, the worse people get at stepping in when it fails. Most plans assume one person can run far more agents than they can.
Along the bottom, how much your agents do without asking. Up the side, how much evidence you hold that they should. Most businesses are piloting, which is a fine place to start. The dangerous businesses are the ones that have granted autonomy without the evidence behind it. To reach "earned", move up before you move across: get the evidence, then grant the autonomy.
Buy the models and swap them when something better passes your tests. Route each step to the cheapest model that passes. Own the layer underneath: one connected picture of your clients, your work and your decisions, a register of every agent with a named person against it, and a test set made from your own cases. The decision a client relies on stays with a person.
Take a customer's contract renewal that runs seventy days from start to finish, with only about four of them spent on the work. The rest is waiting on figures before and going round again after. Automating the work saves days; removing the waiting saves most of the seventy.
One workflow at a time, through five stages, with a decision to carry on or stop between each, taken on measured evidence against criteria written down first. AI makes every stage faster. It doesn't remove a gate.
