Positive Ratings, Hidden Concerns: Employee Voice Disclosure in AI-Mediated Organizational Listening
Summary
A field study inside a global consulting firm examines how conversational AI voice interviews paired with surveys shape what employees disclose, finding that 20-41% of sessions paired favorable ratings with substantive concerns and developing a grounded model of 'bounded disclosure'.
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# Positive Ratings, Hidden Concerns: Employee Voice Disclosure in AI-Mediated Organizational Listening Source: [https://arxiv.org/abs/2609.38788](https://arxiv.org/abs/2609.38788) [View PDF](https://arxiv.org/pdf/2609.38788) > Abstract:Organizations started listening to employees through conversational AI agents alongside structured surveys\. Little is known about what these channels change in what employees say when disclosure carries hierarchical risk\. We report a field study inside a global management consulting firm whose process pairs a pre\-survey with an adaptive AI voice interview on the same themes within one session\. Across 44 first\-session interviews \(132 matched theme observations\), 20\-41% of sessions showed a favorable rating co\-occurring with a substantive concern voiced later, depending on the favorability threshold\. The Gioia analysis drew on 158 protective quotes from 65 eligible sessions\. Disclosure rarely arrived unguarded: employees softened concerns, deflected accountability, and bounded how far they went, and this protective work tracked the perceived legitimacy of the listening structure\. We develop a grounded model of bounded disclosure and derive four propositions for voice, channel and listening research\. Silence, we argue, can persist inside expression\. ## Submission history From: Thilo Tamme \[[view email](https://arxiv.org/show-email/52a24a10/2609.38788)\] **\[v1\]**Wed, 30 Sep 2026 02:18:14 UTC \(1,020 KB\)
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