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AIVO Standard™
Published June 26, 2026
| Version 1.0
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The Human Agentic Gap
Authors/Creators
de Rosen, Tim
Description
This article introduces the Human Agentic Gap - the divergence between a brand's performance in human-mediated AI purchase journeys and its performance in autonomous agent purchase journeys - and examines its implications for CMO and CDMO planning.
The argument builds on prior empirical work in the AIVO Standard working paper series, specifically the finding that 87.3% of brands explicitly present at the first turn of a human-prompted AI conversation are displaced by a competitor before the final recommendation at turn four (n=1,427, 95% CI 85.5–88.9%), and the two-regime model of foundation-model behaviour introduced in Beyond Visibility v1.1 (Sheals & de Rosen, 2026). The Human Agentic Gap is defined as the structural extension of these findings into autonomous agent flows, where the three mechanisms that allow brand recovery in human-mediated journeys — recovery opportunities, diagnostic signal, and time - are simultaneously removed.
The article develops the commercial implications of this structural shift for marketing planning, measurement infrastructure, and budget allocation, and proposes four diagnostic questions for the CMO and CDMO planning cycle. It does not present new empirical data. The Human Agentic Gap is introduced as a named phenomenon and a research agenda; empirical measurement of brand performance divergence between human-prompted and autonomous agent flows constitutes the next phase of the AIVO research programme.
Intended for chief marketing officers, chief digital and marketing officers, and the agency and consulting teams that serve them.
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AIVO_Journal_Human_Agentic_Gap_July2026.pdf
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Keywords and subjects
Keywords
Human Agentic Gap
Agentic Commerce
AI Agent
AIVO Meridian
The Linkage Gap
CMO
CMDO
AI Purchase Journeys
AI Activation
Layer 3 Activation
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DOI
10.5281/zenodo.20920098
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[](https://doi.org/10.5281/zenodo.20920098)
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Resource type<br>Journal article
Publisher<br>Zenodo
Published in<br>AIVO Journal (https://aivojournal.org), 2026.
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English
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Creative Commons Attribution 4.0 International
The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited.
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Copyright 2026 AIVO Standard
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Created
June 26, 2026
Modified
June 26, 2026
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