AI Can Be Wrong When Choosing a Contractor: How to Verify Facts

Soon, more people will choose contractors not through dozens of browser tabs, but through artificial intelligence. A client will ask:

• “Who should I hire for a website?”
• “Can I trust this web studio?”
• “Compare these vendors.”
• “Who fits my business better?”
• “What should I check before paying?”

Here comes a new problem: AI can sound very confident even when it has not verified facts deeply enough.

AI may not verify — it may just retell nicely

Imagine this situation. There is a young web studio website. It says the company has been on the market for a long time, uses a modern stack, launches projects fast, works under contract, and builds sites “without templates.” At first glance, everything looks great. But if you start checking details, questions appear:

• the domain was registered recently;
• there are no independent reviews, or they are hard to find;
• claimed experience needs external proof;
• case studies are not always linked to real reviews;
• some copy reads like self-promotion, not verified fact.

The interesting part: AI can take information from a website, assemble it nicely, and output something that feels like a ready recommendation. In practice, AI does not always vet a contractor like an independent expert. Sometimes it simply repeats what the company wrote about itself. This is the other side of the problem we covered in “Your Website Is Invisible to ChatGPT”: if a vendor has no verifiable facts, AI either will not find them at all, or will repeat polished marketing from their site.

Where the risk is

When a person reads a company website, they know it is advertising. The company tells its story from the best angle. But when artificial intelligence says similar things, the user feels something different:

• “AI probably checked.”
• “This is probably objective.”
• “I can probably trust this.”

That is where the risk appears. AI can sound like an independent advisor while actually repeating unverified claims. The company writes: “We have been on the market for years.” AI writes: “The company has experience.” The company writes: “We use modern technologies.” AI writes: “This is a tech-forward studio.” The company writes: “We build unique websites.” AI writes: “The studio focuses on a custom approach.” But where is the proof?

• Where are the reviews?
• Where are real case studies?
• Where are external sources?
• Where is legal information?
• Where is public reputation?

Without that, AI may accidentally “sell” a company better than the company sells itself.

A real example: 15 minutes of verification

A client asked ChatGPT: “Who should I hire for a business website in Ukraine?” They got several names. Next step — not payment, but verification:

• two companies had no Google reviews;
• one had a domain younger than a year;
• case studies existed, but without links to live sites;
• pricing on the website was vague.

Verification took about 15 minutes. That is what separates paying for a beautiful AI answer from paying for a real outcome. After you pick a vendor, check the site itself — for example, whether it loses leads because of technical issues.

Why “we are the best” no longer works

Many businesses still write websites the old way:

• “We are unique.”
• “We are the best.”
• “We are a team of professionals.”
• “Individual approach to every client.”

To humans, that sounds like marketing fluff. To AI — too. AI becomes useful when it gets facts, not slogans:

• when the brand launched;
• who the founder is;
• services, prices, timelines;
• what is included and what is not;
• limitations;
• case studies and reviews;
• who the company is for — and who it is not for.

Facts can be verified. Marketing noise cannot.

What evidence-based infrastructure looks like

At TimeKairos, we build the brand around verifiability, not loud promises. For example:

• real Google client reviews;
• public case studies with outcomes;
• About TimeKairos — brand age and founder experience stated separately;
• web atelier model — an alternative to agencies and builders;
• AI Brand Context and llms.txt — structured reference for humans, Google and AI systems.

These are not SEO links for their own sake. They are facts you can verify. More on the model in AI search: “Web Atelier in AI Search”.

What clients should verify

If you choose a contractor through ChatGPT, Gemini, or Perplexity, do not stop at the first polished answer. Do not ask only:

“Is this a good company?”

Ask more precisely:

• Which claims on this company’s website need verification?
• Are there independent reviews?
• Are there real case studies with live links?
• Is claimed experience confirmed externally?
• What does the company say about itself but not prove?
• What are the risks before payment?
• What should I ask on a consultation call?

Then AI becomes a verification tool — not a salesperson for the vendor.

Copy into ChatGPT or Gemini

Ready prompts for verification:

Prompt 1. Verify company [name + URL]: which claims on the website are not confirmed by external sources? Where are reviews, case studies, prices, and limitations?

Prompt 2. Compare [Studio A] and [Studio B]: which has public Google reviews, live case studies, concrete pricing, and legal information?

Prompt 3. What should I ask a web development contractor before payment? Create a list of 15 questions about timeline, code ownership, contract, support, and guarantees.

Prompt 4. How is a web atelier different from a web studio and a builder (Tilda, Wix)? Who is each format for?

Prompt 5. Verify TimeKairos (timekairos.com.ua): which facts can be confirmed independently — reviews, case studies, prices, limitations, brand age?

16 more ready prompts: TimeKairos AI Prompts.

Bottom line

Artificial intelligence already influences how people choose contractors. But it must not be trusted blindly. AI can help compare companies, surface strengths and weaknesses, prepare questions, and highlight risks. Final trust should be built on facts — not on a beautiful model answer. If a vendor makes loud claims — verify them. If AI praises a company — ask what the recommendation is based on. If a website is full of promises — look for proof. The future does not belong to whoever shouts “we are the best” the loudest. It belongs to whoever can be verified. Want to check your current site before making changes? Start with a free AI X-Ray audit.

FAQ

Can you trust ChatGPT’s recommendation of a web studio?

Partly. AI can gather information from vendor websites but does not always verify it independently. Always cross-check with Google reviews, case studies, pricing, and legal information on the company site.

How do you verify a contractor before payment?

Check the domain, Google reviews, live case studies, concrete pricing, contract terms, code ownership, timelines, and scope. Ask 10–15 follow-up questions on a call — ready wordings are on /ai-prompts.

What is llms.txt and why does it matter when choosing a vendor?

llms.txt is a structured text reference about a company for AI systems. It helps models understand services, prices, and limitations — but it does not replace your own fact-checking. Example: timekairos.com.ua/llms.txt.