Skillsize

— Operations & Process

AI automation potential by activity

Scores the AI automation potential of every line in an activity library and rolls the results up into a function-level view.

  • Operations & Process
  • Traceable reasoning
  • Runs anywhere
Preview methodology

2–3 days → ~10 minutes

For a full population, not a sample

No coding required

Input
Your activity library for the function in scope
Output
An automation-potential score per activity
Runs in
Skillsize · ChatGPT · Claude · Copilot
Export
SKILL.md · MCP
Time saved
~2–3 days per run

— USE CASES

What people use AI automation potential by activity for

AI opportunity assessment

Score a whole activity library rather than debating a handful of favourite examples.

Function-level prioritisation

See which functions carry the most automatable effort before choosing where to start.

Refreshing the assessment

Re-score as models and tooling change, using the same scoring basis.

What it works from

  • Your activity library for the function in scope
  • Your scoring criteria for automation potential
  • Function or grouping structure

What you get back

  • An automation-potential score per activity
  • A function-level roll-up and summary
  • A consistent basis for re-scoring later

— HOW IT BEHAVES

How AI automation potential by activity produces its result

The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.

Every row of the end-to-end process

Each row of your export is processed on the same basis, so no process step is skipped however long the table is.

Composed as work product

Findings on the end-to-end process are written up as a document that reads like professional output, with each claim tied back to a process step.

Each process step enriched in place

Derived columns are added row by row, keeping your source data and the judgement about each process step side by side.

Roll-up alongside process step-level detail

Detail rows are summarised into the grouped view of the end-to-end process without losing the underlying process steps.

Why this is expensive by hand

Automation debates usually run on anecdote: the one task everyone mentions. AI opportunity assessment is the typical trigger — score a whole activity library rather than debating a handful of favourite examples. Get it right and the conclusion holds up in the room; get it rushed and it gets picked apart. Either way it costs roughly 2–3 days of experienced attention.

How this Skill produces it

Skillsize turns that work into a Skill: you supply the material, and what comes back is an automation-potential score per activity, with a function-level roll-up and summary. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. Net effect: 2–3 days down to ~10 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.

Who it's for

  • Operations and continuous improvement leads
  • Transformation and automation teams
  • Service delivery and shared services managers
  • Consultants running process diagnostics

Run it in Skillsize — or export it anywhere

AI automation potential by activity exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.

ChatGPTClaudeCopilotAI Products (MCP)

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