The AI Leverage Ladder

The ladder is a way to see any AI capability as a position rather than a product. Every capability sits somewhere on four dials. As a practice climbs the ladder, all four dials move together, which is what a rung actually is.

The lower half, rungs one to three, is AI working beside a person on tasks they would rather not do themselves. Nothing there changes who is accountable. The upper half, rungs four to seven, is AI carrying a whole process from start to finish, with only the exceptions coming back to a person. The gains are larger in the upper half and so is the discipline required.

The point of naming the rungs is that most practices try to jump. They buy a rung six tool before rung one is working, and it sits idle because there was no agreed way of working for it to speed up. Climbing one rung at a time, and only when the current rung is solid, is the whole method.

• Triggered. Who starts the work: you, on demand, or the clock, on a schedule.
• Gets data. What it can see: only what you paste in, or your live systems.
• Memory. What it keeps between one run and the next: nothing, or a running record.
• Does. What it is allowed to do: suggest something, draft something, or act within a boundary you set.

Rung 0: write it down. No AI. The template, the checklist, the list of who owes what to whom. If a process cannot be filled in by hand, no model can fill it in either, because it has nothing to work from.

Rung 1: Ask. You paste something in and get a structured first draft back in your format, which you then edit. Dot points become a progress note. A rough situation becomes a carefully worded email. This is the cheapest rung to reach and, for many practices, the largest single time saving, because it is used the most often.

Rung 2: Ground. You load your templates, policies and worked examples into one project the assistant draws on every time, so you stop re-explaining yourself. A staff member asks a plain-English question and gets the answer with the source document named.

Rung 3: Connect. You give the assistant narrow access to a specific system: an inbox, a calendar, a folder. It reads a thread in context and drafts a reply for you to review. This is the first rung where client information can cross into a tool by design rather than by accident, so the privacy work matters from rung three up.

Rung 4: Extend. You package a process once so it runs the same way every time, whoever starts it. A whole team inherits a documentation structure with two or three gold-standard examples attached, and a new clinician produces consistent structure from day one. The gain here is consistency rather than speed.

Rung 5: Make. The output stops being a paragraph to edit and becomes a finished thing: a dashboard, a calculator, a small tool built from a de-identified export without a developer.

Rung 6: Delegate. You stop reviewing a draft and start reviewing a finished piece of work, with only the exceptions surfaced. Years of shared-drive files become a proposed reorganisation for you to approve before anything moves.

Rung 7: Automate. The trigger stops being a person. A recurring job is defined once and runs on schedule: a Friday summary of bookings, cancellations and overdue invoices that arrives on its own each week.

Find a task that currently routes through you. Name where it sits on the four dials now, and what the next rung would look like. Build that one rung, use it for a few weeks, and check that the practice is genuinely lighter rather than busier in a new way. Then look at the next task.

Risk does not simply rise as you climb. A scheduled report carries its biggest exposure at the top, in autonomy. A client report carries its sharpest risk in the middle, at the reasoning step, because a wrong report can leave the building on a tired signature. Name the dials, find where the risk actually sits for that task, and you have a build plan rather than a hype decision.

The pillar AI for OT practices in Australia uses this ladder as its spine, and the deep version with practice examples tagged to each rung is the AI for OTs guide. The privacy line that governs rungs three and up is in is it safe to use AI in an Australian OT practice. The rung-one and rung-two work for reports is in standardising report writing with an AI project.

General information for Australian OT practice owners. This is not legal or clinical advice. If you want a starting point, the Practice Health Check surfaces the tasks that route through you, which are the ones worth laddering first.