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Field analysis · Operations & review

Industry research in the AI era: separate samples, inference, and promotion

Industry surveys can map questions, but sample size, recruitment, and uncertainty must be reviewable. AI can organize open responses and surface themes; it should not turn opaque samples into precise market facts.

Editorial synthesisReviewed 2026-08-01Verify before action
DECISION BRIEF

Three points to take away

  1. 01

    Disclose sampling and exclusions first.

  2. 02

    Separate quantitative results from qualitative observations.

  3. 03

    Label AI-generated interpretation as inference.

01

Research record

Retain questionnaire version, recruitment channels, dates, deduplication, missing-data handling, and analysis code. Precise figures without a research record should not drive material decisions.

02

Where AI fits

Use models for theme coding, anomaly prompts, and summary drafts, with researcher sampling for consistency. A model must not invent motives respondents did not state.

VERIFY BEFORE ACTION

Verification checklist before action

  • Sample original responses to measure coding consistency and document disagreements.

  • Run a bounded trial with non-sensitive samples and retain successes, failures, and human corrections.

  • Before wider use, name an owner, data boundary, stop condition, and review date.

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