● Evidence-led guidance
A practical way to find the first useful AI improvement in your business
Examine one repeated task before choosing a tool: record its inputs, delays, judgement points and intended result, then score frequency, effort, commercial value, risk and ease of testing.
● Evidence-led guidance
Plan an automation that has an owner, evidence and a safe way to stop
Responsible automation starts with a documented workflow, explicit authority, human review points, an exception route, an audit record and a rollback method.
● Evidence-led guidance
How to avoid AI tool sprawl and choose one improvement you can actually measure
Separate the business problem from the software, define a small success measure before testing, and set a stop condition so experiments remain bounded and useful.