Terms managers encounter when a company starts implementing AI. Each is explained through practical experience: what it is, where people often go wrong, and what to decide in advance. The glossary is growing.
A process audit before AI implementation examines how work is actually done in a company: what people do, how long it takes, which data and tools they use, and where delays and errors occur. The findings show which steps are worth automating, where AI would only add work, and where a person is essential.
Read more →A process map shows how work actually moves through a department or company: who does what, in which order, what they pass on, where work waits, and where people bypass rules to get things done. It is built from what people actually do and helps decide what to automate and what to leave alone.
Read more →A pilot is a time-limited, small-scale launch of a solution using real data and real people, with success criteria written down in advance. Its results help decide whether to continue implementation, make changes, or stop.
Read more →An AI specification is a document that describes a task so a model or agent can perform it predictably and its output can be checked: what goes in, what comes out, which rules must not be broken, and how to tell when the work is done. It lives outside the chat and remains available across sessions.
Read more →Acceptance criteria are verifiable conditions used to decide whether work is complete. They are written before work begins so the client and contractor interpret them the same way and can check the result without a dispute.
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