AI, automation and generative AI
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Artificial intelligence (AI) is a broad category of computer systems that perform tasks associated with perception, prediction, language or decision support. Traditional automation usually follows specific instructions: for example, a payroll spreadsheet applies a formula to calculate gross pay. A predictive model estimates a quantity from previous examples, such as forecast demand. Generative AI creates new text, images, code or other output in response to an instruction. The categories can overlap, but they are not interchangeable.
A text-based generative AI assistant predicts and generates useful language patterns from its training and supplied context. It does not inspect your workplace, know your private records or verify every answer unless it has been given appropriate access and sources. Fluent wording is not proof of accuracy. Treat the output as a draft produced by a powerful assistant, not as a signed expert opinion.
Worked example
A business needs a visitor welcome message. A fixed template would insert a name and visit date into approved text. A generative assistant could draft three friendly versions for different audiences. A human should confirm dates, safety instructions and site rules before sending any version.
Practice
Choose three tasks from daily life or work. Label each one fixed automation, prediction or generative assistance. Explain why a human review is or is not necessary. Start with fictional examples such as planning a family event, summarising a made-up meeting or designing a product description.
Key takeaway
Generative AI produces plausible new content. You remain responsible for deciding whether the content is correct and appropriate.
Generative AI output is best treated initially as what?
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