When we first started using AI agents to moderate expert interviews, we focused on two questions:
- Do experts want to talk to an AI?
- Can an AI agent deliver the same level of insight as a strong human interviewer?
Our team brings experience from Blackstone, BCG, McKinsey, and Bain. We know that a good expert interview involves much more than reading questions from a discussion guide. The interviewer needs to listen, understand what matters, ask the right follow-up questions, and know when an answer is worth exploring further.
That is what our AI voice agents are designed to do. They are configured to conduct interviews like experienced strategy consultants, knowing where to probe, how to guide the expert, and when to steer the conversation back on track.
Experts prefer the experience
We collected feedback after 320 interviews that spanned 12 commercial due diligence projects and more than eight languages. At the end of each one, we asked the experts:
- How satisfied were you with the interview?
- How did it compare with a traditional human-led interview?
Of the 320 experts, 298 provided a numeric satisfaction score. For the comparison with human-led interviews, we included responses from 279 experts who had previously participated in traditional expert-network interviews.
The results were clear.
Of the experts who provided a satisfaction score, 91% rated the interview a 4 or 5 out of 5. Almost two-thirds, 63%, gave it the highest possible score.
Among experts with prior experience of traditional expert-network calls, 78% considered the AI-led experience the same as or better than a traditional human-led interview.
Satisfaction score
How satisfied were you with this interview, on a scale of 1 to 5?
- 5 — Very satisfied63%
- 428%
- 36%
- 23%
- 1 — Very dissatisfied0%
Against a human-led interview
Was this AI-led interview better, worse, or the same as a traditional human-led interview?
- Better46%
- Same32%
- Mixed5%
- Worse16%
Why experts value the experience
The largest positive theme, accounting for 36% of coded feedback mentions, was clear and well-structured questions. Experts valued questions that were precise, logical, and easy to understand.
Experts also highlighted that the interaction felt natural and conversational. The AI moderator listened, summarized their responses, and asked relevant follow-up questions.
Scheduling flexibility was another large benefit. Because there is no interviewer whose calendar needs to be coordinated, experts can complete the conversation when it suits them.
In summary, experts valued DiligenceSquared’s AI agent on the same fundamentals that make any interview good: clear questions, relevant follow-ups, active listening, and respect for their time.
“It did not feel like a robot or robotic voice to me. You were able to listen and also summarize well.”
“There's a lot less waffle with AI, so we get straight to the point. A one-hour interview reduced to 30 minutes.”
“I can be more open and honest when it’s AI-led. It takes out the nervousness.”
“You summarize very well. The fact that you reiterate my answers makes me feel heard.”
“I could do it in the evening, late at night. I could do it on my own terms.”
“The questions were insightful. They were very well put together, and the follow-ups were relevant.”
Local language changes the level of detail
One of the advantages of AI-moderated interviewing is the ability to conduct research in the expert’s local language.
The DiligenceSquared AI moderator currently supports more than 30 languages.
This matters because there is a significant difference between being able to answer a question in English and being able to explain a complex market in the language you use every day.
When experts speak in their local language, they can be more precise. They use the terminology that is common in their market, explain nuances more naturally, and spend less time translating their thoughts before answering.
This is difficult to replicate with a traditional consulting model.
Consider a European market study involving interviews in France, Germany, Spain, Italy, the Netherlands, and Sweden. Even the largest global consulting firms will rarely staff a team with native or fluent interviewers across every relevant language.
The practical solution is often to conduct most interviews in English. That may be sufficient for basic facts, but it can reduce the level of detail and exclude otherwise relevant experts who are less comfortable working in English.
Our study covered more than eight languages. The positive feedback was not limited to English-language interviews.
Why AI agents can produce better insights
AI has several structural advantages that make data gathering more efficient, consistent, and accurate.
People take time to learn about a new market. Their execution varies between interviews. They forget to collect data points and cannot retain large context across or even within long conversations.
An AI agent can ramp up on the content instantly, apply the same rigor to every interview, retain massive context, and identify contradictions live.
If one expert’s statement conflicts with an earlier interview, a datapoint, or another piece of research, the agent can recognize that conflict during the conversation and probe it immediately. A person may only discover the contradiction later, while reviewing notes or preparing the final analysis.
Where human-led interviews add the most value
At DiligenceSquared, we believe there is real value in the first few highly exploratory interviews being human-led.
At the beginning of a project, the team is not only looking for answers. It is learning which questions matter.
Clients who come to us have typically already run these interviews. Where they have not, we can run them at DiligenceSquared as well.
Either way, those conversations set the foundation for the broader interview program. Once there is an initial understanding of the market, our consultants translate the emerging hypotheses and research priorities into a clear brief for the AI moderator.
The right division of labor
Our AI moderator runs interviews from beginning to end. It works from the research brief, asks the questions, follows up on the answers, and conducts conversations across more than 30 languages.
That makes it possible to run more interviews with greater consistency and without the usual scheduling and language constraints. Research programs can extend to a scale that would rarely be practical with human interviewers.
The results from our study show that this scale does not come at the expense of the expert experience. Experts value the thoughtful questions, relevant follow-ups, strong comprehension, and control over their own time.
At the same time, the agent’s ability to retain context, apply consistent rigor, and identify contradictions live allows us to improve the quality and depth of the insights collected.
For systematic information gathering at scale, we believe AI agents are already better suited to the job.
Experts prefer the experience. The quality and depth of insights are higher. And the research can be conducted at a scale that was not previously possible.