Generative AI

What is Generative AI? A plain-English guide for leaders

Generative AI has quickly moved from a technology discussed mainly by developers and researchers to a business tool used by teams every day. Here is what it actually does, and what it does not.

Generative AI has quickly moved from a technology discussed mainly by developers and researchers to a business tool used by teams every day. It writes, summarizes, explains and drafts, and it does it in seconds rather than minutes.

What it is good at

Drafting and rewriting, summarizing long documents, answering questions against material you already have, and generating variations to choose from. Those are the tasks where a draft in a second is worth more than a perfect one in an hour.

The pattern is the same in every one of them: there is a rough version already, and the model makes it better in less time than you could. That is why adoption moved faster than most teams expected.

What it is not

It is not a database. It does not know your numbers, your policies or your customers unless it is given them, and it will answer confidently either way. That is why the projects that work are the ones where the model is wired to real data and a real gate, rather than left to answer from memory.

Where leaders should start

Pick one workflow that already has a person doing the same task twice. Give the model the context it is missing, keep a person on the approval, and measure the time it takes back. One workflow that holds up is worth more than a strategy document describing twenty.

  • Give it the material it would otherwise have to guess at, not a prompt asking it to remember.
  • Keep a person on the decision it influences, so a bad answer costs a minute rather than a customer.
  • Measure before and after, or the enthusiasm runs out before the evidence arrives.

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