AI assistants can draft an email in seconds, summarize a long report and explain a tricky concept in plain English. They can also state something completely wrong with total confidence. Researchers call these mistakes “hallucinations,” and anyone who uses AI regularly has run into one: a statistic that doesn’t exist, a quote nobody said, a feature a product never had.

The answer isn’t to stop using AI. It’s to build a quick, repeatable verification habit, so you keep the speed and lose the embarrassment. Here’s a six-step routine that works whether you use AI for work, school or everyday questions.

Why AI gets things wrong

Most AI chatbots are built on large language models, which generate text by predicting likely words based on patterns in their training data. That makes them excellent at producing fluent, natural-sounding answers, but fluency is not the same as accuracy. A model may have outdated information, may blend two similar facts together, or may fill a gap with something that simply sounds right.

Knowing this changes how you read AI output. Treat it like a smart first draft from a helpful colleague who sometimes misremembers details, not like a final, checked answer.

Step 1: Sort the claims by risk

Not every sentence needs the same scrutiny. Before you check anything, skim the response and mark what actually matters:

  • High risk: numbers, dates, names, quotes, prices, laws, medical or financial details, and anything you’ll publish or send to a client.
  • Medium risk: how-to steps, product features and technical instructions.
  • Low risk: brainstorming ideas, tone suggestions and rewording your own writing.

Spend your checking time on the high-risk items first. This keeps verification fast instead of exhausting.

Step 2: Ask the AI to show its work

Follow up with a simple prompt such as: “List each factual claim in your answer and tell me how confident you are in each one.” Many tools will flag their own weak spots when asked directly. If your AI tool can browse the web or cite sources, ask it to provide links for key facts. Then, and this part matters, actually open those links. AI tools can occasionally cite a source that doesn’t say what they claim.

Step 3: Go to the primary source

For anything important, find the original source rather than a summary of it. If a claim is about a company’s new product, check the company’s own announcement. If it’s about a regulation, look at the official government page. If it’s a statistic, find the study or agency that published it. Primary sources are slower to read, but they are where accuracy lives.

Step 4: Cross-check with a second, independent source

One source can be wrong or out of date. When a fact really matters, confirm it with a second reputable source that didn’t simply copy the first. If two independent sources agree, you can be far more confident. If they disagree, that’s your cue to dig deeper before using the information.

Step 5: Check the date

AI models have knowledge cutoffs, and even tools that search the web can surface older pages. Prices change, software updates roll out and rules get revised. For anything time-sensitive, confirm the information is current and note when it was last updated.

Step 6: Keep a simple verification log

If you use AI for recurring work, such as reports, newsletters or research, keep a short log of claims you checked and where you confirmed them. It takes a minute per task, it makes revisions easier, and over time it shows you which kinds of questions your AI tool handles well and where it tends to slip.

Make the habit stick

The easiest way to keep this routine is to bake it into your prompts. Try ending important requests with: “Flag any claims you are unsure about and suggest where I can verify them.” You can also ask the AI to separate facts from opinions or assumptions in its answer, which makes the risky parts easier to spot.

Learning to work with AI this way, quickly but carefully, is one of the most valuable skills you can build right now. If you want to keep sharpening it, the Hubactually AI community is a friendly place to swap prompts, compare tools and learn practical techniques with other people exploring AI.

The bottom line

AI is a powerful assistant, not an oracle. Sort claims by risk, ask the tool to show its work, check primary sources, confirm with a second source, watch the dates and keep a light log. Six steps, a few extra minutes, and your AI-assisted work becomes something you can genuinely stand behind.

Ready to go further with AI tools and skills? Join the Hubactually AI community at hubactually.com to learn alongside others, ask questions and stay current on what’s new in AI.

Image: Free magnifying glass newspaper photo via Rawpixel, CC0 1.0