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AI glossary · Foundations

Artificial intelligence (AI)

Artificial intelligence (AI): Artificial intelligence (AI) is software that performs tasks that normally need human judgment: understanding language, recognizing images, making predictions, or generating text. Today it usually means systems built with machine learning.

AI is an umbrella term, not one product. It covers the spam filter in your inbox, the route suggestions in your maps app, the fraud check on your credit card, and the chat assistant that drafts your emails. What they share is that the software was not hand-coded with every rule. It learned patterns from data.

For most of the field's history, AI meant narrow tools built for one job. Since late 2022, when ChatGPT put a general-purpose language model in front of the public, the word has come to mean generative AI: models that produce text, images, code, and audio on request. When a coworker says 'let's use AI for this,' that is almost always what they mean.

It helps to hold two facts at once. These systems are genuinely useful for drafting, summarizing, analyzing, and brainstorming. They are also pattern-matchers with no built-in sense of truth, so they can be confidently wrong. Treat the output like a capable junior colleague's first draft: worth having, always worth checking.

Example at work

A regional insurance agency uses AI three ways in one afternoon: the office manager pastes a 40-page policy update into a chat assistant and asks for a one-page summary of what changed, a producer has it draft three versions of a renewal email, and the claims team runs a tool that flags unusual claims for review. Each result gets a human read before anything goes out.

Why it matters

You do not need to understand the math to use AI well, but you do need a working mental model. Knowing that these tools learn from data, predict rather than know, and improve with clear instructions is the difference between getting reliable help and getting burned by a confident mistake.

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