---
id: "action-build-machine-readable-trust"
type: "action-item"
source_timestamps: ["§ Implications for Leaders"]
tags: ["operations", "data-strategy"]
related: ["concept-machine-readable-trust", "concept-agent-shelf"]
action: "Measure, improve, and structure operational reliability signals to ensure AI agents select your brand."
outcome: "Inclusion in the 'agent shelf' consideration set before human users see alternatives."
speakers: ["Mark J. Greeven", "Fabrice Beaulieu", "Wei Wei"]
sources: ["geo"]
sourceVaultSlug: "hbr-seg-geo"
originDay: 3
articleStem: "hbr-ext-15-china-ai-agents-commerce"
sourceUrl: "https://hbr.org/2026/04/research-what-chinas-ai-agents-reveal-about-the-future-of-commerce"
sourceTitle: "Research: What China’s AI Agents Reveal About the Future of Commerce"
---
# Build Machine-Readable Trust Signals

## Action
Treat operational **eligibility signals** as a core growth asset. Concretely:
- measure and improve **service-level performance**,
- track and reduce **dispute and refund rates**,
- ensure **policy clarity**,
- harden **exception-handling reliability**,
- make **product data highly structured** and easily parsed by AI agents.

## Outcome
Inclusion on the [[concept-agent-shelf]] — i.e., in the consideration set **before** human users see alternatives. This is the concrete expression of [[concept-machine-readable-trust]] and strategic move #1 in [[framework-strategic-implications-leaders]].

> Enrichment: necessary but not sufficient — pair with protocol adoption and commercial agreements (e.g. Stripe ACP-style interoperability) since visibility can also depend on platform access.


## Related across articles
- [[action-structure-content-machines]]
- [[concept-machine-readable-trust]]
- [[action-structure-machine-readable-data]]