Can You Use AI in a Technical Interview?

The answer to “Can you use AI in a technical interview?” is not a universal yes or no. It depends on the employer, the interview stage, the assessment format, and the instructions you receive. ChatGPT, GitHub Copilot, code-completion features, browser search, and even built-in meeting tools may be treated differently from one another.

The safest principle is simple: do not assume that a tool is permitted because it is technically available. Preparation and evaluation are separate activities. You may be allowed to use AI to practise before an interview while being expected to complete the live interview, coding test, or take-home assessment independently. ServiceNow makes that distinction explicitly, and McKinsey similarly separates preparation support from assessments intended to evaluate job-related skills such as problem-solving and coding (ServiceNow Careers; McKinsey & Company).

This guide uses a practical three-mode framework: no-AI, AI-optional, and AI-required. The labels are a decision aid, not an official industry standard. Your employer’s written instructions take priority.

First, identify the mode before you open a tool

Start by identifying exactly what you are being asked to do. “Technical interview” can mean a live coding conversation, an online test, a system-design session, a debugging exercise, a portfolio review, or a take-home project. A company may set different rules for each stage.

Read the invitation, assessment landing page, candidate agreement, and tool instructions. Look for direct wording about external websites, generative AI, code assistants, browser tabs, recording, collaboration, or use of reference materials. If the instructions mention only a specific integrated assistant, do not treat that as permission to use a separate chatbot. If they say “open book,” ask whether that includes generative tools.

The employer landscape is genuinely mixed. A 2026 CoderPad survey reported that 34% of surveyed hiring teams banned AI in technical assessments, 46% allowed it either broadly or with constraints, and 20% decided case by case (CoderPad State of Tech Hiring 2026). These are vendor-survey results, not universal labor-market benchmarks, but they are a useful reason to ask rather than guess.

The important boundary is between permission and convenience. A tool being available in your browser does not establish permission. Conversely, if an interviewer explicitly says that an assistant is allowed, avoiding it is not automatically more ethical or more impressive. In that mode, the evaluation may include your ability to use the tool critically.

How to ask without sounding difficult

A clarification question is part of responsible preparation. Ask the recruiter or assessment contact before the evaluation, not after you have already used a tool. Be specific enough that the answer cannot be misunderstood.

You can send this message:

Hi [Name], I’m preparing for the [stage name] on [date]. Could you confirm whether generative AI or code-completion tools are permitted during this stage? If they are allowed, which tools are approved, and do I need to disclose or share my usage? I will follow the stated policy and complete any unapproved portion independently. Thank you.

For a live interview, ask at the start if you did not receive a clear answer: “Before we begin, may I confirm the tool policy? Should I use only the coding environment and documentation you provide, or is an AI assistant permitted?” Then wait for a clear response.

If the answer is vague—“Use your judgment,” “It should be fine,” or “We do not really police it”—ask a second question: “To make sure I follow the evaluation rules, should I treat AI as allowed, restricted to a named tool, or not allowed for this exercise?” If you still cannot get a clear answer, choose the conservative option: do not use AI during the assessment and document that you requested clarification.

Also ask about adjacent tools. A policy may allow an approved assistant but prohibit recording. ServiceNow, for example, states that candidates may use AI for preparation but expects interviews, online tests, technical challenges, and other evaluations to be completed independently unless AI is explicitly permitted; it also prohibits recording interviews (ServiceNow Careers). Do not record a session, capture the interviewer’s screen, or paste confidential prompts into an external service unless you have explicit authorization.

Prepare for all three modes

Your preparation should make you capable without AI and articulate when AI is permitted. That combination protects you from a policy surprise and gives an interviewer evidence of judgment rather than tool dependence.

Mode one: practise for a no-AI assessment

Rehearse under conditions that remove the usual shortcuts. Choose representative problems, set a time limit, and solve them in a plain editor or the platform you expect to use. Narrate your reasoning: clarify the input, state assumptions, propose a simple approach, consider complexity, code in small steps, and test edge cases.

• Solve at least some problems without autocomplete, search, ChatGPT, or Copilot.
• Practise recovering from a blank start: write a small example, identify the invariant, and build from there.
• Test boundary cases deliberately, including empty input, duplicate values, large values, and invalid input when relevant.
• After each attempt, record the first incorrect assumption or missed case instead of only checking whether the final answer passed.
• Rehearse explaining a trade-off in plain language, such as readability versus a more optimized data structure.

For a system-design or data-science interview, the same discipline applies. Sketch the requirements, identify constraints, explain your assumptions, and state what you would measure or validate. Do not memorise polished architecture diagrams that you cannot defend.

Mode two: practise for an AI-optional assessment

Use an assistant only as a collaborator, not as an invisible answer generator. A useful drill is to solve a problem yourself first, then ask AI for an alternative approach or a critique. Compare the outputs and test both. This reveals whether you can notice an incorrect complexity claim, a missing edge case, an unsafe dependency, or code that does not match the stated requirements.

Practise saying what you are doing while you work. For example: “I’ll ask for two approaches, but I’m going to choose between them based on memory use and ease of testing. I’ll run my own examples rather than assume the suggestion is correct.” If the tool produces code, inspect it line by line. Be prepared to explain every function, imported package, and error-handling decision.

A concise disclosure script can help: “I understand AI is allowed here. I’ll use it to explore options, but I’ll validate the output and explain every decision.” If the interviewer asks you to share the interaction, be ready to show the prompt, the response, the changes you made, and the tests that changed your mind.

Mode three: practise for an AI-required assessment

Treat the assistant as one component of an engineering process. Practise writing precise context, constraints, acceptance criteria, and examples. Then practise rejecting the first answer. A strong workflow might be: define the problem, request options, inspect the risks, implement a small slice, run tests, review the diff, and explain what remains uncertain.

The skill being demonstrated is not clever prompting alone. It is judgment. An interviewer may reasonably care whether you protect private data, detect hallucinated APIs, avoid unnecessary dependencies, preserve maintainability, and know when a manual solution is faster. Ask which tool and environment are approved before the exercise begins; do not substitute a personal account or unapproved service.

What to do when rules change during the interview

Sometimes an interviewer introduces a tool after the session has started. Pause and confirm the scope: “Is the assistant allowed for the rest of this problem, and should I disclose which suggestions I accept?” If the tool is offered only for documentation lookup, do not use it to generate the solution. If the interviewer says AI is not allowed after previously suggesting it was, follow the latest instruction and state that you will continue unaided.

If you accidentally use an unapproved tool, do not hide it. Stop, explain what happened, and ask how they want to proceed. The outcome is controlled by the employer, but transparent correction is safer than quietly building on unauthorized assistance. Avoid copying confidential interview questions, proprietary code, personal data, or internal documentation into a public model.

Keep a short policy note with the assessment invitation. Write down the date, the person who clarified the rule, the approved tools, whether disclosure is required, and any restrictions on recording or external references. This is especially useful when a process has several stages and different interviewers.

A final checklist for the day before

• Name the exact stage: live coding, online test, take-home, system design, debugging, or another format.
• Find the written AI, browser, collaboration, recording, and reference-material rules.
• Ask the recruiter about anything ambiguous and save the response.
• Prepare an unaided practice session, even if AI is expected or optional.
• If AI is allowed, confirm the approved tool, disclosure requirement, visibility, and data restrictions.
• Practise explaining your prompts, trade-offs, tests, corrections, and reasons for rejecting suggestions.
• Check your environment: editor, language version, authentication, permissions, and internet requirements.
• Prepare a sentence that states your tool use clearly without claiming more certainty than you have.

You can also use the broader technical coding interview preparation plan for problem practice, then add the AI-policy checks above. For the live format, review your video interview checklist, including the rule that recording should never be assumed to be acceptable.

The judgment interviewers are actually looking for

AI policy is not merely a test of whether you know where the chatbot button is. It tests whether you can read constraints, ask a precise question, protect information, and produce work you understand. In a no-AI assessment, that means demonstrating independent reasoning. In an AI-optional assessment, it means making the tool’s contribution visible and validating it. In an AI-required assessment, it means controlling the workflow rather than accepting plausible text on trust.

When the rules are unclear, asking first is the professional move. When AI is prohibited, prepare without it. When it is permitted, disclose and verify. When it is required, show how you turn generated suggestions into tested, maintainable engineering decisions. That approach will not guarantee a successful interview, but it gives the employer an accurate view of your skills while keeping your process within the stated rules.