Simplify in 3: When your AI Lies to You

Simplify in 3: Three weekly tips to grow your business, stay organized, and save time without the overwhelm.

Before: You've started using ChatGPT, Claude, or another AI tool to save time for writing, research, or client work. It feels amazing… until you realize the "facts" it gave you don't exist.

That's an AI hallucination: when AI confidently invents something that sounds real but isn't.

After: By the end of this email you'll know how to spot hallucinations, how to use AI safely, and how to keep your business credible — even when your AI "assistant" goes rogue.

Hi [FIRST NAME GOES HERE],

I've been deep in generative AI since January 2024, testing almost every major tool for small-business use.

Originally, I started with ChatGPT, moved to Perplexity (you can test five models for the same $20/month), and tried you.com for its ease of use for non-techies.

Today, I use Claude (Max) and ChatGPT (Business) every day for research, editing my writing, and coding guidance.

I've logged more than 1,000 hours testing AI tools. That's over six months of full-time work.

Here's what that time taught me:

AI is a phenomenal copy editor and assistant, but a terrible fact-checker.

Your 3 Actions

🛠 1. Use AI for Research, but Always Verify

AI can save hours of research time by surfacing ideas, examples, and sources you might not find yourself.

But it doesn't know what's true. It predicts what's likely based on patterns, not facts. Some of what it gives you will be accurate, some won't.

Do this today:

• Use AI as a research assistant, not the final authority.
• ✅ Good: "Summarize current refund policy trends and share 3 sources to check."
• ❌ Risky: "What are the refund laws in California?" (without confirming them)
• Open every link and confirm it's from a credible, recent, and relevant source.
• When AI doesn't cite a source, ask: "Where did this come from?"
• Keep a quick list of trusted sites you use to double-check info (like official gov pages or known trade publications).

For credible information, use:

• Perplexity AI (shows clickable, sourced answers)
• ChatGPT and Claude can also provide sources when you ask for them
• Google Scholar (for studies and data)
• Official government or industry websites

💬 GenAI Prompt for Credible-Source-Only Research

"Use only credible, verifiable sources such as government sites, academic research, or major news outlets. Exclude blogs, Reddit, and opinion pieces. Cite the publication name and include a direct link for every fact."

🤔 2. Question Confident Answers Without Proof

AI often sounds completely sure of itself, even when it is wrong. The more polished and detailed the answer, the easier it is to believe.

Do this today:

• Watch for details with no evidence — numbers or dates with no sources.
• Ask follow-up questions like "Can you show your sources?" or "Where did that come from?"
• Compare results across tools. If the answers differ, something needs verification.
• Double-check anything important with a quick web search or credible database.
• Watch for links that don't work or don't go where claimed.
• Be skeptical of legal or medical advice with precise details but no citations.

Ask follow-up questions to test confidence:

• "Where did you get that statistic?"
• "Can you link to the original source?"
• "Are you sure this regulation exists?"

AI will often admit uncertainty when pressed.

Cross-reference everything important:

• Use multiple sources
• Check official websites
• Ask a human expert when stakes are high

Real example

For 8 weeks, I uploaded my Fantasy Football scoreboard asking for weekly analysis. Every week, AI confidently identified the "closest match" and "biggest blowout"… and got them wrong every single time. When I asked why, the response was "I didn't look carefully enough." The AI wasn't uncertain. It was wrong with confidence.

⚖️ 3. Match AI to the Right Tasks

AI is phenomenal at certain tasks and terrible at others. When you use AI appropriately, hallucinations are less dangerous. When you misuse it, you're asking for trouble.

Use AI for:

• Editing emails, blog posts, social media content
• Brainstorming ideas and options
• Summarizing text you provide
• Rewriting content in different tones
• Explaining concepts in simpler terms
• Creating templates and frameworks

Don't use AI for:

• Providing factual information without sources
• Legal or medical advice
• Math and calculations (it often gets these wrong)
• Citing academic sources accurately (without checking yourself)
• Anything where being wrong has serious consequences

Do this today — create your own "safe use" checklist:

Before using AI output, ask:

• ☐ Did I verify any factual claims?
• ☐ Are there consequences if this is wrong?
• ☐ Would I trust this if a stranger said it?
• ☐ Have I checked sources/links?

Save your verified prompts:

• When you find a prompt that works well, save it.
• Build a library of prompts for tasks where AI consistently helps.
• Avoid one-off research queries — those are hallucination magnets.

⚠️ Real-World Hallucination Disasters

Want to see what happens when businesses don't check AI output? Four cautionary tales:

1. Deloitte's $18 Million AI Failure

One of the world's largest consulting firms had to refund a major client after AI-powered assurance work produced unreliable results. If Deloitte can get burned with unlimited resources and expertise, what chance does a small business have without safeguards?

Lesson: Even experts get this wrong. Build verification into your process from day one.

Read: Deloitte issued refund after AI assurance project failed →

2. Lawyer Sanctioned for Fake AI-Generated Cases

A lawyer submitted court documents citing legal precedents that didn't exist — all generated by ChatGPT. The cases looked legitimate with proper formatting, judge names, and case numbers. None of it was real. He faced sanctions and professional embarrassment.

Lesson: AI is exceptionally good at making fake things look real. Never trust legal, medical, or regulatory information from AI without verification.

Read: Michael Cohen used AI chatbot that cited bogus legal cases →

3. Courts Create New Rules to Combat AI Hallucinations

As more attorneys got caught submitting AI-generated fake cases, courts nationwide began tracking the problem. A database now shows 486 cases worldwide where lawyers cited hallucinated content, 324 of them in U.S. courts. In one Arizona case, 12 of the 19 cases cited were fabricated. The judge sanctioned the attorney, requiring her to notify three federal judges that she had attributed fictitious cases to them and send the sanctions order to every judge in any case where she serves as counsel.

Lesson: When AI hallucinations become common enough, entire industries create new safeguards. Don't wait for your industry to force compliance — build verification in now.

Read: As more lawyers fall for AI hallucinations, ChatGPT says: Check my work →

4. Google Faked Its Own AI Demo

Google showed Gemini analyzing a Super Bowl moment in real-time during their commercial. Turns out, the output was pre-scripted — not actually generated by AI. Even Google, which builds these systems, couldn't rely on AI to perform accurately in a high-stakes demo.

Lesson: If Google can't trust AI to work reliably in a controlled demo, you shouldn't trust it without safeguards.

Read: Google's Gemini AI demo at Super Bowl used fake output →

The Bottom Line

AI hallucinations aren't going away. They're part of how these tools work.

But that doesn't mean AI isn't useful. It means you need to use it strategically.

Think of AI like a brilliant intern: Great at drafting and brainstorming, but you wouldn't let them make important decisions or sign contracts without checking their work.

Your action this week:

Pick one way you currently use AI. Ask yourself: "What would happen if this information was wrong?" If the answer is "something bad," add a verification step today.

💼 Bonus: If You're Building AI into Your Business

If you're a consultant, developer, or business owner integrating AI into your services or products, here are the safeguards to implement:

✅ Require Human Review

• Any AI output driving decisions or customer-facing content needs human validation.
• Build this into your workflow. Don't make it optional.

✅ Use Retrieval-Augmented Generation (RAG)

• Anchor AI output to verifiable sources.
• Don't rely on "pure LLM output" for factual claims.
• Force the AI to cite where information came from.

✅ Track Everything

• Log: when AI was used, what prompt, what output, who validated.
• Creates accountability and helps spot patterns.
• Essential for European clients (GDPR compliance).

✅ Monitor for Hallucinations

• Track false positives, weird outputs, user complaints.
• Measure accuracy over time.
• Adjust processes based on findings.

✅ Label AI-Generated Content

• Be transparent that content is AI-assisted.
• Frame as "suggestions" not "truths."
• Protects you legally and sets proper expectations.

Stay sharp,

✉️ Know someone using ChatGPT or Claude for research? They need to see this. Forward it.

Anne-Cécile Guillot Bellisario
Your AI-Powered Business Coach
Founder of Simplify with digital and AI
Small Business Consultant

PS: If you found today's tips helpful, hit reply and tell me which one you're trying first — I read every message.

P.P.S. I'm building something new: Simplify AI Signal — a tool to help you grow your voice and engagement on LinkedIn. It researches articles based on your interests, helps you draft posts in your voice, and creates custom feeds (by person, company, or topic) so you see what matters to you — not what the algorithm wants you to see. We're building this to fight the algorithm and amplify underrepresented voices. Interested in early access? Reply with "Signal".