Open dataset · CC BY 4.0 · free to download and cite

The AI Recommendation Audit 2026 (B2B / GTM)

Which B2B and GTM software the AI engines actually name, recorded per engine per query, with the divergence between them scored.

DOI
10.5281/zenodo.20767878
Published by
Lucreya
Category
AI · GTM
Last updated
2026-06-19

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Download the raw data (JSON)

https://lucreya.com/research/ai-recommendation-audit-2026/data.json

Read the study

The full method and findings, published on Lucreya.

This dataset is published as a structured report rather than a flat table. Its sections are: dataset, subtitle, author, license, licenseUrl, snapshotDate, captureWindow, measured, headlineFindings, engineTopByCategory, leaderboard, perCategory, sourceBias.

Cite this dataset

Released under CC BY 4.0. You may use it commercially and redistribute it. Attribution is the only condition.

Couey, V. W. (2026). The AI Recommendation Audit 2026 (B2B / GTM). Deep Synthesis. https://doi.org/10.5281/zenodo.20767878