Glossary
AI automation
Definition
What is AI automation?
AI automation is the use of machine learning models, most often large language models, to carry out business tasks that previously needed a person to read, decide or write. Unlike rule-based automation, it handles unstructured input such as emails, calls and documents, and makes judgement calls within limits you define.
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How it differs from classic automation
Classic automation follows fixed rules: if a form field equals X, do Y. It breaks the moment the input changes shape. AI automation reads the input the way a person would, so a badly formatted invoice or a rambling voicemail still gets processed.
The trade-off is that AI output is probabilistic. Good implementations pair the model with validation, confidence thresholds and a human review step for anything uncertain.
Where it pays off first
The best first projects are high-volume, repetitive and already documented: inbound calls, invoice entry, lead replies, support triage. A process that runs 50 times a week with a clear input and output is a better candidate than a rare, complex one.
Frequently asked questions
Is AI automation the same as a chatbot?
No. A chatbot is one possible interface. AI automation covers any task where a model reads, decides or writes on your behalf, including back-office work nobody chats with.
How long does a first AI automation take to build?
A scoped first version typically goes live in two to three weeks, provided the process is documented and the tools it touches have APIs.
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