AI Interviewers Commoditize Expert Networks

AI interviewing will not be where expert networks win, because the software layer is becoming cheap while the hard part remains owning trusted supply and getting the right person to answer quickly. In practice, the moat sits in expert liquidity, scheduling, compliance, repeat participation, and in helping customers ask better questions. That is why Office Hours frames AI interview agents as a feature that expands usage, not as the durable advantage.

• Traditional expert networks have long burned labor on discovery and outreach. Tegus described analysts spending much of their time finding experts, contacting them, and pushing for conversion. If AI handles the interview itself, that removes only one step. The marketplace work of sourcing and activating the expert still determines speed and quality.
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• The buyer value is not just recording answers, it is getting nuanced answers from the right expert for a live thesis. Tegus found seeded or generic calls produced weak transcripts because the questions lacked context. Office Hours makes the same point from the other side, that many customers will want their own AI interviewer trained on their analysts' style rather than a network's default agent.
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• Pricing history shows why this feature commoditizes fast. Tegus already pushed call execution toward pass through cost, charging roughly $300 to $400 per call while monetizing the library separately, and GLG style calls were priced far higher. Once voice to AI tools are off the shelf, agent interviews follow the same path toward low differentiation and margin pressure.
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The next battleground is shifting from who can build an AI interviewer to who can turn human expertise into the fastest, most reusable workflow. That favors platforms that keep experts engaged, make matching instant, and package each interaction into follow on products like user research, mentorship, transcript search, and AI training data.