Term: Artificial intelligence (AI)
~5 min read
Estimated time: ~5 min read — for the in-app brief plus opening the primary source.
What this is
AI is software that finds patterns in data and uses them to predict, classify, recommend, or generate content. It is a tool with strengths and failure modes — not a person and not magic.
Everyday example
When email suggests a reply, a bank flags a suspicious transaction, or ChatGPT drafts a memo — those are all AI finding patterns and producing an output.
AI is a pattern engine you govern — not a colleague and not magic.
- It predicts, classifies, recommends, or generates from patterns in data.
- Two families you will hear: analytics AI (scores, forecasts) and generative AI (drafts, images, code).
- It can be highly useful and still fail in patterned ways.
- Your job is judgment: where it helps, who owns the outcome, what error rate you accept.
Next action: In your next AI discussion, name the task and the acceptable error — not the product brand.
What changes in how you lead
How decision rights, process, and ownership should change.
- Approve AI as a tool with an owner, not as a substitute for a role.
- Ask what the system is optimizing for before you ask which vendor.
Compare related ideas
Artificial intelligence (AI) vs LLM / ChatGPT-style tools
AI is the broad category. An LLM is one popular type of AI specialized in language. Not all AI is ChatGPT — forecasting fraud scores is also AI.
Open LLM / ChatGPT-style toolsDeep dive
Think 'pattern engine,' not 'digital employee.' AI can be extremely useful and still be wrong in patterned ways.
Most business tools fall into analytics AI (scores, forecasts, alerts) or generative AI (drafts text, images, code).
Your job as an executive is judgment: where it helps, who owns outcomes, and what error rate is acceptable.