Can Generative AI Replace Pilot Testing of a Research Interview Guide?

Can You Pilot Test an Interview Guide by Asking AI to Act as a Participant?

You have completed a semi-structured interview guide and want to determine whether its questions are clear, appropriately sequenced, and capable of encouraging meaningful responses.

Instead of recruiting someone for a pilot interview, you ask ChatGPT to act as a university instructor. You conduct a simulated interview, ask follow-up questions, and observe how the AI system responds.

The conversation appears successful. The simulated participant understands every question, provides detailed examples, and offers thoughtful reflections. You may even ask AI to evaluate the interview afterward and recommend improvements.

But does a successful simulated conversation demonstrate that the guide will work with actual participants? Or does it merely show that an AI system can generate plausible answers to the questions you prepared?

No, AI Simulation Cannot Replace Pilot Interviewing With Actual Participants

Why Pilot Interviewing Provides Evidence That AI Simulation Cannot

What Is Pilot Testing in Qualitative Interview Research?

Pilot interviewing involves trying out an interview guide and its associated procedures before the main data collection. Its purpose is to identify potential problems and determine whether revisions are needed.

Depending on the study, a pilot interview may examine whether participants understand the questions, whether the sequence supports conversation, whether probes encourage elaboration, and whether the anticipated interview duration is realistic.

It may also reveal practical issues involving recording, consent procedures, interview setting, and the interviewer's ability to respond to unexpected answers.

Kallio and colleagues (2016) identify pilot testing as one of five phases in their framework for developing a qualitative semi-structured interview guide. Castillo-Montoya (2016) similarly includes piloting within the Interview Protocol Refinement framework.

These frameworks treat piloting as part of systematic interview preparation rather than a formality conducted after the guide is already considered complete.

What Can AI Simulation Actually Test?

AI can generate hypothetical participant responses and allow researchers to rehearse how they might conduct an interview.

For example, the researcher may instruct the model to provide brief answers, express uncertainty, misunderstand a question, or introduce an unexpected topic.

Such simulations can help researchers recognize potential weaknesses in their interview technique or question design.

However, the model is following a generated scenario. Its responses do not establish how actual members of the target population understand the questions or what experiences they would describe.

The distinction is between testing the plausibility of an interview design and observing how that design functions with people.

Why AI Participants May Make a Weak Interview Guide Look Effective

Generative AI often produces coherent, articulate responses when asked to simulate an interview participant.

It may infer the intended meaning of an ambiguous question, supply examples that fit the research topic, and provide detailed explanations without requiring much probing.

Actual participants may respond differently. They may be unfamiliar with the researcher's terminology, struggle to recall a particular experience, answer briefly, or interpret a question in an unexpected way.

For example, consider the question: "How do you negotiate professional autonomy in AI-mediated instructional practices?"

An AI model may generate a sophisticated explanation involving institutional policy and professional discretion. A university instructor may instead ask what "AI-mediated" or "professional autonomy" means in the context of the interview.

A successful AI simulation may therefore conceal the very comprehension problems that pilot interviewing is intended to reveal.

Can AI Deliberately Simulate Confused or Reluctant Participants?

Yes. Researchers can ask AI to simulate participants who misunderstand questions, provide minimal responses, disagree with the interviewer, or have limited experience with the topic.

These exercises may help interviewers practice clarification, neutral probing, and conversational flexibility.

However, instructing AI to behave like a confused participant does not establish which questions actual participants will find confusing.

The simulation reflects the scenario supplied by the researcher and the model's generated behavior. It is not an observation of respondent comprehension.

Researchers should therefore distinguish rehearsal scenarios from findings obtained through genuine pilot interviews.

Why Actual Interview Interaction Matters

Qualitative interviewing is an interactional process. The interviewer and participant contribute to how the conversation develops, which experiences are discussed, and what meanings are clarified.

A participant may interpret a question differently from the researcher, introduce an unexpected distinction, or challenge the assumptions embedded in the interview guide.

For example, a researcher might ask instructors how they have incorporated generative AI into teaching. During piloting, a participant may explain that they deliberately avoid AI and find the question difficult to answer.

This observation could justify revising the opening question to accommodate both use and nonuse.

AI may anticipate this possibility, but it cannot establish how frequently or in what ways the issue arises among the intended participants.

DeJonckheere and Vaughn (2019) emphasize the relationship between conversational interaction and methodological rigor in semi-structured interviewing.

Pilot Interviews Can Reveal Problems With the Researcher's Assumptions

One important contribution of pilot interviewing is that participants may challenge assumptions the researcher did not recognize.

Suppose a study investigates university instructors' experiences with institutional AI policies. The interview guide assumes that every institution has a formal written policy.

During a pilot interview, an instructor may explain that their department relies on informal expectations rather than a documented policy.

This distinction could be central to the study, yet it may be overlooked if AI was given a prompt that already assumed formal policies existed.

Researchers should remain attentive to the possibility that pilot participants reveal not only unclear wording but also weaknesses in how the phenomenon has been conceptualized.

How Should You Prompt AI for Preliminary Interview Rehearsal?

A useful prompt should clearly identify the interaction as a simulation and request feedback on potential interview problems without presenting the generated exchange as empirical evidence.

This approach can support interviewer preparation, particularly when researchers want to practice responding to unanticipated answers.

However, the researcher should not interpret the simulation's apparent realism as evidence that the model accurately represents the intended participant population.

Can AI Help Prepare a Pilot Interview Evaluation Form?

Yes. AI can help develop a structured record for documenting problems observed during pilot interviews.

The form might include the question identifier, observed difficulty, participant interpretation, interviewer observation, proposed revision, and decision following review.

For example, if a participant asks for clarification of the term "institutional AI governance," the researcher can record the problem and consider whether more accessible wording would preserve the intended inquiry.

AI may also help organize de-identified pilot notes or summarize documented feedback, provided the researcher verifies the output against the original material.

Such assistance concerns the organization of genuine evidence. It should not be confused with generating that evidence.

How Many Pilot Interviews Are Necessary?

There is no universally required number of pilot interviews for every qualitative study.

The appropriate extent of piloting depends on the complexity of the guide, methodological approach, participant diversity, and purpose of the evaluation.

A relatively straightforward guide involving a familiar participant group may require different preparation from a complex protocol involving several stakeholder groups or sensitive topics.

Researchers should justify the pilot approach in relation to the study rather than assume that a particular number automatically establishes interview quality.

Multiple rounds may be useful when consequential revisions are introduced. For example, a substantially rewritten guide may benefit from further piloting to determine whether the changes address the original concerns.

Should Pilot Participants Be Included in the Main Study?

The decision depends on the study design, the extent of guide revision, and the research protocol.

If the pilot interview uses a substantially different guide, combining its data with later interviews may create analytical inconsistencies.

Conversely, when changes are minor and the study design permits it, researchers may consider whether pilot material can contribute to the main dataset.

Such decisions should be justified and consistent with participant consent and institutional ethics approval.

Researchers should not automatically include or exclude pilot interviews solely because AI recommends doing so.

Can AI Replace Pilot Testing When the Guide Uses Established Questions?

Using questions from published qualitative studies may provide a useful starting point, but it does not guarantee that they are suitable for a new population or context.

For example, an interview question developed for instructors at institutions with established AI policies may be inappropriate for participants working where formal policies are absent.

AI can help identify potential contextual mismatches, but actual pilot interaction may reveal additional problems.

The need for piloting should reflect the degree of adaptation and the consequences of misunderstanding, rather than whether the questions were originally developed by humans or AI.

How Should Researchers Report AI Simulation and Pilot Testing?

Researchers should clearly distinguish simulated interview rehearsal from pilot interviewing involving actual participants.

For example, a methodology section may state that generative AI was used to review question wording and rehearse hypothetical interview scenarios before a pilot interview was conducted.

It should not state that the guide was pilot tested with participants if the only interaction involved an AI-generated persona.

If AI helped organize authentic pilot feedback, researchers should explain its role without attributing the participants' observations to the model.

The broader development of an AI-assisted interview guide should maintain this distinction between preparation and empirical evaluation.

When an AI Simulation Works but a Pilot Participant Finds the Question Confusing

The AI simulation produced a convincing answer, but the hypothetical pilot interview revealed a comprehension problem that the simulation had not exposed.

This illustrates why simulated conversations may support preparation but cannot establish how actual participants understand and respond to interview questions.

Common Misconceptions About AI and Interview Guide Pilot Testing

Use AI to Rehearse the Interview, Then Evaluate It With Real Participants

AI can be useful during early preparation, particularly when researchers want to practice asking questions, responding to brief answers, or recognizing potentially confusing terminology.

However, when the objective is to determine how the guide functions with the intended population, appropriate pilot interviewing remains necessary.

Document AI rehearsals separately from genuine pilot findings. Record the problems observed during actual interviews and explain consequential revisions.

The objective is not to demonstrate that AI can answer the questions convincingly. It is to determine whether the guide supports the kind of inquiry the researcher intends to conduct with actual participants.

Before Claiming That a Research Interview Guide Has Been Pilot Tested

Frequently Asked Questions About AI and Interview Guide Pilot Testing

AI Can Rehearse the Interview, but It Cannot Replace the Participant

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