AI hallucinations: Why LLMs make things up and how to spot them

When you ask a large language model a question, it doesn’t search the web—it guesses the most likely answer based on patterns it learned. That’s why it can sound confident while giving you AI hallucinations, false or fabricated information presented as fact by AI systems. Also known as factual errors, these aren’t bugs—they’re built into how these models work. The problem isn’t that AI is lying. It’s that it has no real understanding of truth. It just strings together words that fit together well.

Look at LLM citations, references generated by AI that appear real but don’t exist. Also known as fake sources, they’re so convincing that researchers have cited them in papers without realizing they were made up. One study found over 70% of AI-generated citations in academic drafts were fictional. That’s not a glitch—it’s the default behavior. The same thing happens with dates, names, laws, and even scientific facts. AI doesn’t know it’s wrong because it doesn’t know anything at all. It just predicts what comes next.

This isn’t just about research. Prompt injection, a technique where users trick AI into ignoring safety rules or generating false content. Also known as adversarial prompts, it’s one of the main ways hallucinations get amplified in real-world use. A simple tweak in how you phrase a question can make an AI invent a company, a court case, or a product that never existed. And because the output feels natural, people trust it. That’s why you can’t just rely on AI for anything that needs accuracy—legal docs, medical advice, financial reports, or even your next blog post.

The good news? You don’t need to stop using AI. You just need to stop trusting it blindly. Every time you get an answer, ask: Where did this come from? Can you verify it? Is there a real source? If the AI cites something, look it up yourself. If it gives a date, check a calendar. If it names a person, search their name with a quote around it. These aren’t extra steps—they’re your safety net.

Below, you’ll find real examples of how AI hallucinations show up in research, coding, business, and everyday use. You’ll see how experts are catching them, how tools are trying to fix them, and what you can do right now to avoid getting fooled. This isn’t theory. It’s happening every day—and you need to know how to protect yourself.