When to Use AI (And When Not To)

Not every problem needs AI. Here's a practical framework.

The AI Decision Matrix

GREAT for AI ✅

• •Drafting: First drafts of emails, reports, content
• •Brainstorming: Generating ideas, alternatives, perspectives
• •Summarizing: Condensing long documents into key points
• •Explaining: Breaking down complex topics into simple terms
• •Reformatting: Converting data between formats
• •Research starting points: Getting an overview before deep diving
• •Repetitive text tasks: Form letters, templates, variations
• •Code scaffolding: Boilerplate code, common patterns

OKAY for AI (with verification) ⚠️

• •Factual research (always verify)
• •Technical documentation
• •Data analysis (check the math)
• •Translation (have a native speaker review)
• •Legal/medical information (always consult a professional)

NOT for AI ❌

• •Final decisions: AI can inform, not decide
• •Sensitive data processing: Don't paste passwords, private health info, or financial details into public AI tools
• •Emotional support replacement: AI can't truly empathize
• •Real-time information: Stock prices, live events, breaking news
• •Anything requiring accountability: If someone could get hurt, a human needs to be in the loop

The 10-Second Test

Before using AI, ask yourself:

1. 1.Would a wrong answer cause harm? If yes, verify everything.
2. 2.Does it need to be current? If yes, use AI + real-time sources.
3. 3.Is this sensitive data? If yes, use enterprise/private AI tools only.
4. 4.Am I replacing my judgment? If yes, step back.

The Sweet Spot

AI is best as a force multiplier — it makes you 2-10x faster at tasks you already know how to do. It's weakest when you're relying on it for tasks you can't evaluate yourself.

The best AI users aren't the ones who use it for everything. They're the ones who know exactly when to reach for it.