When AI Gives a Wrong Answer: What to Say in Your Interview

Tell Me About a Time You Used AI and the Answer It Gave You Was Wrong: How to Ace This Interview Question

AI is awesome. It’s like having a super-intern who works at light speed and never asks for a coffee break. We use it at Wonsulting every single day to help underdogs land jobs at places like Google and Meta. But here’s the uncomfortable truth: sometimes, that super-intern gets a little confused.

We’ve all been there. You ask ChatGPT for a citation, and it invents a book that doesn't exist. You ask for a specific Excel formula, and it gives you syntax that breaks your spreadsheet. These moments are called "hallucinations," and while they can be annoying, they are actually gold mines for job interviews.

Increasingly, hiring managers are asking: "Tell me about a time you used AI and the answer it gave you was wrong. How did you handle it?"

They aren't asking this to hate on AI. They’re asking to see if you have the critical thinking skills to manage it. They want to know if you’re a "Human + AI" pro or just someone hitting copy-paste and hoping for the best.

Here is your complete guide on what to do when AI messes up, and exactly how to frame that experience to impress recruiters and land the offer.

Why Recruiters Love This Question

Before we dive into the answer script, you need to understand the why. When a hiring manager asks about AI mistakes, they are testing three specific competencies:

• Critical Thinking & Skepticism: Do you blindly trust technology, or do you vet your sources? In the corporate world, submitting bad data because "the bot told me to" is a career-ending move.
• Problem-Solving Agility: When the easy button (AI) fails, do you have a backup plan? Can you troubleshoot, pivot, or do the manual work required to get the job done?
• Integrity: Are you honest about using tools? Pretending you never use AI in 2024 is like a carpenter pretending they don't use power drills. It just sounds suspicious.

This question is your chance to prove that you are the pilot, and AI is just the co-pilot. You are still the one steering the ship.

The 3 Types of AI "Wrong" Answers

To answer this effectively, you need a specific scenario. Usually, AI errors fall into one of these three buckets. Pick one that resonates with your field for your interview story:

1. The Confident Hallucination

This is when the AI states a "fact" with 100% confidence, but it’s objectively false.

• Example: You ask for a case study on a competitor's marketing strategy, and the AI invents a campaign that never happened.
• The Fix: You fact-check against primary sources (Google, company filings, news reports).

2. The Logic Trap

This happens often in coding or data analysis. The AI writes code that looks correct syntactically but fails to execute the specific logic you requested.

• Example: You ask for a Python script to sort a list by date, but it sorts by string value instead.
• The Fix: You debug the code, identifying the logic error and rewriting the specific lines manually.

3. The Context Failure

The AI gives a generic answer that ignores the specific nuances of your prompt.

• Example: You ask for an email template for a conservative finance client, and it gives you a casual, emoji-filled draft suitable for a startup.
• The Fix: You refine your prompt with "constraints" (e.g., "Use formal tone, no emojis, under 100 words") or manually edit the tone.

How to Handle It: The "Trust But Verify" Framework

If you are currently facing an AI error in your daily work (or preparing for a technical assessment), here is the practical step-by-step process you should follow. This is also the "meat" of your interview answer.

Step 1: The Sanity Check

Never copy-paste directly from a chatbot into a final deliverable. Always read the output with a skeptic’s eye. Does the tone sound robotic? Do the facts align with your industry knowledge? If a statistic sounds too good to be true, it probably is.

Step 2: Cross-Referencing

If the AI provides data, dates, or quotes, treating it as a lead, not a source. Open a new tab and verify.

• For coding: Run the snippet in a sandbox environment first.
• For writing: Check proper nouns and dates via a search engine.
• For math: Do a quick mental estimation. If the AI says $10,000 + $5,000 = $50,000, you need to catch that immediately.

Step 3: The Iterative Fix (The "Human" Element)

This is where you show your value. You don't just throw your hands up; you guide the tool.

• Re-prompting: "That citation doesn't seem to exist. Please provide a real source or confirm you don't have access to it."
• Manual Intervention: Sometimes, it’s faster to rewrite the sentence or fix the code yourself than to argue with the bot.

Structuring Your Interview Answer (The STAR Method)

When the interviewer drops the question, use the STAR method (Situation, Task, Action, Result) to keep your answer tight and impactful.

Here is a template you can adapt:

The Setup (Situation & Task)

Start by setting the scene. Be specific about what you were trying to achieve.

"In my previous role as a Marketing Coordinator, I was tasked with researching 10 potential influencers for a new product launch. I decided to use ChatGPT to speed up the initial discovery phase by asking it to list influencers in the sustainable fashion niche with over 100k followers."

The Problem (The "Wrong" Answer)

Describe the error clearly.

"The list looked great at first glance. However, because I follow this industry closely, I recognized one of the names as a tech reviewer, not a fashion blogger. That raised a red flag. When I clicked through the links the AI provided for the others, two of the links were broken, and one influencer hadn't posted in three years."

The Solution (Action)

This is the most important part. Show your process.

"I realized I couldn't rely on the AI's database for real-time engagement metrics. I used the AI-generated list merely as a starting point for keyword ideas. I switched to a manual search using Instagram’s native search tools and verified each profile myself. I also refined my prompt to ask the AI for 'types of content' ideas rather than specific profile data, which it handled much better."

The Outcome (Result)

End on a high note.

"By combining the AI’s creative brainstorming with my manual verification, I built a verified list of 15 high-quality partners. The campaign we launched with them had a 20% higher engagement rate than our previous attempts. It taught me that AI is a powerful engine for ideas, but human verification is the steering wheel."

3 Examples of "Good" vs. "Bad" Answers

To make sure you nail this, let’s look at how not to answer versus how a pro does it.

Scenario: You used AI to write code.

❌ The Bad Answer: "Oh yeah, I asked it to write a SQL query and it was totally wrong. It was so annoying. I just ended up writing it myself because AI is kind of dumb sometimes."

• Why it fails: It sounds complain-y and dismissive. It doesn't show a process, just frustration.

✅ The Winning Answer: "I was using AI to generate a complex SQL query to join three different customer tables. The output looked clean, but when I reviewed the logic, I noticed it was using an 'INNER JOIN' where a 'LEFT JOIN' was necessary, which would have excluded valuable customer data. I manually corrected the join type and added a constraint the AI missed. It saved me about 20 minutes of typing boilerplate code, but catching that logic error ensured our report remained accurate."

• Why it works: It shows technical understanding ("Inner vs Left join"), efficiency ("saved 20 minutes"), and quality control.

Common Pitfalls to Avoid

When answering "tell me about a time you used AI and the answer it gave you was wrong," avoid these traps:

• The "I Don't Use AI" Defense: Saying you never use AI tools might make you look like a luddite or someone who resists innovation. Companies want tech-forward employees.
• Blaming the Tool: Don't trash the technology. Treat the AI like a junior colleague. If a junior colleague makes a mistake, you coach them (refine the prompt) or fix it. You don't just complain.
• Vague Stories: "One time it gave me bad info, so I fixed it" is too generic. Use specific details: what project, what error, and what fix?

The "Underdog" Advantage

At Wonsulting, we believe in turning underdogs into winners. Part of that transformation is mastering the tools of the trade. Whether you come from a non-target school, you're a career pivoter, or an international student racing against the clock, AI can be your equalizer, but only if you use it smartly.

When AI gives you the wrong answer, don't panic. View it as an opportunity to demonstrate your expertise. It proves that you are the expert, and the machine is just the tool.

Key Takeaways:

• Embrace the error: Use it to show your critical thinking.
• Verify everything: Treat AI outputs as drafts, not final products.
• Use the STAR method: Situation, Task, Action (Verification/Correction), Result.
• Be specific: Details make your story believable and impressive.

If you want to practice your interview answers, including the tough ones like this, check out InterviewAI. It listens to your answers and gives you real-time feedback on your content and delivery, so you can walk into that interview with confidence.

Remember: The tech might be artificial, but your intelligence is real. Show them that.