AI writing is usually fluent but not usually accurate, so you should fact-check any claim that could cost you something if it were wrong, while low-stakes wording and structure rarely need checking.
The short version: treat AI output as a confident first draft from a well-read stranger who never shows their sources. It gets tone, grammar and shape right almost every time. It gets specific facts right often enough to be dangerous.
Why AI sounds right even when it is wrong
A language model predicts the next likely word based on patterns in its training text. That process is very good at producing sentences that read like facts. It is not the same as looking a fact up.
So the model has no internal alarm that says "I am not sure about this date." It will write a made-up citation in the same calm tone it uses for a correct one. This is the single most important thing to understand as a beginner: fluency and accuracy are separate qualities, and AI is much stronger at the first.
The practical consequence is that you cannot judge reliability by how the text feels. A paragraph that flows beautifully can still contain a wrong number, a person who does not exist, or a law that was never passed.
What you must always check
Use this as a decision rule. Verify any output that contains: statistics or percentages; dates and timelines; names of people, companies or products; prices; quotes attributed to anyone; citations, studies or links; legal, medical or financial statements; and anything about recent events.
Those categories share one trait — they are the kind of claim where a small error causes real damage. If a chatbot tells you a medication interaction is safe, or that a contract clause means something it does not, the cost of being wrong is not embarrassment. It is harm.
Check those against a primary source: the vendor's own page, the statute, the peer-reviewed paper, the person's actual statement. For pricing specifically, our internal AI tool database snapshot lists Midjourney's Basic plan at $10/mo, but plans change often, so the vendor's own page is still the only source you should trust before you buy.
What you can usually skip
Not everything needs a citation. If you asked AI to reword a paragraph you wrote, tighten an email, turn your notes into bullet points, suggest headline options, or brainstorm ten angles for a blog post, the factual content came from you. There is nothing external to verify.
The same applies to formatting, tone shifts, and summarising text you pasted in yourself — though even there, spot-check that the summary did not quietly drop your main point. A useful middle ground: ask the tool to mark its own uncertainty. Prompts like "flag anything you are not certain about" or "only state facts you can attribute" reduce confident errors, but they do not eliminate them. Models can be uncertain and still sound certain.
A worked example
Say you run a small business and ask an AI tool to write a short explainer about your return policy for your website. The output reads cleanly. Now sort it.
The sentence "We accept returns within 30 days" is a claim about your business — you know the answer, so you check it against your own policy in seconds. The sentence "Consumer law requires a 30-day return window in all states" is a legal claim, and it must be verified against the actual statute, not accepted because it sounds plausible.
The sentence "Contact us at support@yourstore.com" is a detail you can confirm instantly. Reworded versions of your own sentences need no checking at all. In that one short piece, three different verification needs sit side by side, and only one of them is genuinely risky. That sorting habit is the whole skill.
Where this advice breaks down
Fact-checking has a cost, and it is time. Verifying every number in a long report can take longer than writing the report yourself, which defeats the purpose of using AI in the first place. So the rule is not "check everything."
It is "match the checking to the stakes." A brainstormed list of blog titles needs no verification. A patient-facing summary of a drug's side effects needs heavy verification, ideally by someone qualified.
Second limitation: you cannot fact-check what you do not know. If you have no background in tax law, you may not spot that an AI answer is subtly wrong — you will only catch the errors you already understand. For high-stakes topics in an unfamiliar field, the honest move is to get a human expert, not a better prompt.
Third, some errors are invisible even to careful readers: fabricated citations look exactly like real ones until you click the link. That is why the check has to be an actual click, not a gut feeling. If you want a broader starting point on what these tools can and cannot do, see What can I actually do with AI tools as a total beginner?.