AI-Moderated Research

ChatGPT

ChatGPT

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Conveo automates video interviews to speed up decision-making.

Definition:

ChatGPT is a large language model-based chatbot developed by OpenAI, capable of generating fluent, contextually relevant text across a wide range of tasks. In the context of AI-moderated research, ChatGPT is sometimes used informally by insights teams to help analyse transcripts, draft discussion guides, or summarise findings. However, ChatGPT is a general-purpose tool rather than a purpose-built qualitative research platform. It lacks adaptive probing logic grounded in research methodology, has no participant recruitment or session management capability, and produces outputs that cannot be traced back to verified real participants. For enterprise research teams, this distinction matters significantly when research findings are expected to inform consequential business decisions.

How Conveo Does It

Conveo is built specifically for qualitative research, not adapted from a general-purpose chatbot. Teams can launch an AI-moderated video interview study in under 30 minutes, with adaptive probing that responds to what real participants actually say rather than following a rigid script. Results from real voice and video conversations are ready in days, not weeks. Every insight traces back to a verified participant, supported by verbatim quotes and video clips, giving enterprise teams findings they can present with confidence.

Related terms.
Frequently asked questions.
ChatGPT is a general-purpose conversational AI developed by OpenAI. Insights teams sometimes use it to help draft discussion guides, clean transcripts, or summarise findings. It is not a qualitative research platform and was not designed for structured moderation, participant recruitment, or traceable insight generation. Its value in a research workflow is limited to supporting tasks rather than running or moderating studies.
General-purpose AI like ChatGPT generates plausible text, but it cannot probe a participant based on hesitation, follow an unexpected thread in a live conversation, or verify that a response came from a real person. For research that informs product launches, brand strategy, or investment decisions, the methodology behind the AI matters as much as the output. Purpose-built research AI is designed around research discipline, not general language generation.
ChatGPT is a text generation tool. AI-moderated research platforms are built to run structured conversations with real participants, apply adaptive probing logic, manage recruitment and screening, and produce traceable, stakeholder-ready findings. ChatGPT can assist with peripheral research tasks such as drafting or summarising, but it cannot conduct a study, recruit participants, or guarantee that insights connect to verified human responses. The two serve fundamentally different functions in a research workflow.
General-purpose AI is becoming a standard productivity layer across research teams, useful for drafting, reformatting, and initial synthesis. At the same time, enterprise teams are recognising that research-grade AI requires more than language fluency. Platforms purpose-built for qualitative research embed methodology, participant verification, and adaptive moderation logic that general tools cannot replicate. The trend is toward using general AI for peripheral tasks and research-specific AI for the work that carries methodological accountability.
Many insights teams use ChatGPT for tasks adjacent to research: drafting screener questions, reformatting reports for different audiences, or generating initial thematic labels to pressure-test against actual findings. For the research itself, including moderation, participant recruitment, and traceable synthesis, they rely on purpose-built platforms. Keeping the two roles distinct protects the methodological integrity of findings while still capturing the productivity benefits of general-purpose AI in the surrounding workflow.
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