Voice AI Industry Survey 2026

Authentic insights from the Voice AI community, gathered through voice interviews with no compensation offered.

n = 0•Avg. 0 min interview•No compensation

Key Findings

0

Completed Interviews

Voluntary participants from the Voice AI community

n = 1

enquetor Voice AI Survey 2026 • No compensation was offered

0%

Completion Rate

Of started interviews completed in full

n = 1

enquetor Voice AI Survey 2026 • No compensation was offered

0 min

Average Duration

Time spent sharing authentic experiences

0

enquetor Voice AI Survey 2026 • No compensation was offered

Respondent Experience Levels

Respondents were classified into experience tiers based on their Voice AI usage patterns.

curious
0 (0%)
casual
0 (0%)
integrated
0 (0%)
builder
0 (0%)

Methodology

Research Approach

This research employed a voice-based interview methodology, using AI-powered conversational agents to conduct semi-structured interviews with Voice AI users. The approach was designed based on behavioral research principles from "The Mom Test" methodology, focusing on past behaviors and concrete experiences rather than hypothetical opinions.

Interview Design

Interviews were conducted by T-bot, a conversational AI agent built on RoomKit voice technology. The interview flow included:

  • Literacy screening to assign respondents to experience tiers
  • Tier-specific question sets adapted to respondent experience level
  • Adaptive follow-up questions based on response depth
  • Natural conversation flow with support for pauses and revisions

Sample Demographics

Total Interviews

0

Avg. Duration

0 min

Tier Distribution

curious
0 (0%)
casual
0 (0%)
integrated
0 (0%)
builder
0 (0%)

Hesitation Index Methodology

The Hesitation Index measures cognitive load by tracking pause duration during responses. Longer pauses may indicate topics requiring deeper thought, areas of uncertainty, or subjects where the industry lacks established conventions. Pauses exceeding 2 seconds are logged and aggregated per question to identify topics that provoke the most contemplation.

Revision Report Methodology

Respondents could revise previous answers at any point during the interview. Revisions are tracked to distinguish "first instinct" responses from "considered opinion" after further reflection. High revision rates on specific questions may indicate evolving thinking or complex trade-offs in that area.

Limitations

  • Self-selected sample - respondents chose to participate
  • Voice AI users interviewing about Voice AI may have selection bias
  • No compensation was offered, which may affect sample composition
  • Qualitative insights limited to interview transcript analysis

Compensation Statement

No financial or other compensation was offered to respondents. Participation was entirely voluntary, motivated by interest in contributing to industry research.

Cite This Report

apa

enquetor Research Team. (2026). Voice AI Industry Survey 2026. enquetor. https://enquetor.com/report

mla

enquetor Research Team. "Voice AI Industry Survey 2026." enquetor, March 1, 2026, https://enquetor.com/report.

chicago

enquetor Research Team. "Voice AI Industry Survey 2026." enquetor. March 1, 2026. https://enquetor.com/report.

Include "[Accessed: DATE]" when citing for academic work.

This research was conducted without compensation to respondents.

Questions? Contact the enquetor research team.