If you're a business leader trying to make sense of AI, you've probably noticed two things: everyone has an opinion, and most of those opinions are trying to sell you something.
Here's what you actually need to know — stripped of the hype and the technical jargon.
What AI Is (In Plain Language)
AI is pattern recognition at scale. It looks at large amounts of data, finds patterns, and uses those patterns to make predictions or automate decisions. That's it. Everything else is implementation detail.
What AI Is Good At
- Repetitive tasks with clear rules (data entry, document classification, scheduling)
- Pattern recognition across large datasets (anomaly detection, trend analysis)
- Language tasks (summarization, translation, drafting)
- Prediction based on historical data (demand forecasting, risk assessment)
What AI Is Bad At
- Judgment calls that require context AI doesn't have
- Creative strategy (it can generate content, but not business strategy)
- Tasks with insufficient data (garbage in, garbage out still applies)
- Anything requiring accountability (AI can recommend, but a human should decide)
Three Questions Every Leader Should Ask
Before any AI investment, ask:
- What specific problem does this solve? If the answer is vague, walk away.
- How will we measure success? Define this before you start, not after.
- Can our team actually use this? Technical capability means nothing without adoption.
The leaders who get the most value from AI aren't the most technically sophisticated — they're the ones who ask the best questions.
The Bottom Line
You don't need to become an AI expert. You need to become a better buyer. Understand what AI can and can't do, ask the right questions, and partner with people who speak your language — not just the technology's.