Introducing the AIVO Operational AI Reliance Observation Protocol

Introducing the AIVO Operational AI Reliance Observation Protocol
This is infrastructure, not opinion.

AI systems increasingly generate explanations, comparisons, and summaries that are relied upon operationally by teams across marketing, communications, product, and risk. In many cases, these outputs function as external representations of companies, products, or events.

What has been missing is not intelligence, but record-keeping.

Most AI interfaces do not preserve a durable, replayable record of what was presented at the moment it was consumed. Screenshots are incomplete. Citations are unstable. Outputs vary across time, prompts, interfaces, and users. When questions arise later — about what was said, when, and under what conditions — there is often no authoritative artefact to point to.

AIVO exists to address that evidentiary gap.

Today we are publishing the AIVO Operational AI Reliance Observation Protocol (v1.0), now available as a permanent, citable reference on Zenodo.

This protocol defines how AIVO records AI-generated representations without influencing, optimizing, or altering them. It is deliberately procedural, conservative, and limited in scope. Its purpose is not to evaluate quality or correctness, but to preserve an immutable record of what an AI system presented at a specific moment in time.

What the protocol does

The protocol establishes:

  • Fixed prompt observation rules
  • Declared scope and execution conditions
  • Verbatim capture of AI outputs
  • Time-stamped, versioned evidence artefacts
  • Explicit treatment of omission, substitution, and generalization

It applies to operational reliance contexts, including AI-mediated discovery and explanation, where AI outputs increasingly replace traditional, traceable interfaces.

What the protocol does not do

The protocol does not:

  • Optimize AI outputs
  • Recommend content or prompt changes
  • Score performance or visibility
  • Assert causality, intent, or future behavior

These boundaries are explicit and intentional. AIVO’s role is observational. Interpretation and action belong elsewhere.

Why publish this now

As AI systems become embedded in everyday workflows, the absence of a record is no longer a theoretical concern. It is an operational one.

Publishing the protocol serves three purposes:

  1. It establishes methodological clarity and independence
  2. It provides a stable reference for internal and external scrutiny
  3. It defines what AIVO evidence can — and cannot — be used to claim

This is infrastructure, not opinion.

Canonical reference

The full protocol, including its non-optimization clarification and prompt selection appendix, is published as a single, versioned document on Zenodo and should be treated as the authoritative reference.

Future applications, case work, and analyses conducted by AIVO will explicitly reference this protocol version.


Evidence precedes interpretation.
Records precede disputes.

— AIVO Journal


AIVO Standard Operational AI Reliance Observation Protocol
This protocol defines the procedures by which AIVO records and preserves evidence of AI-generated representations at the moment of observation. Its purpose is to establish a defensible, replayable record of what an AI system presented to a user under defined conditions, without influencing, optimizing, or altering the system’s behavior. This protocol applies to operational AI reliance contexts, including but not limited to AI-mediated discovery, explanation, comparison, and summarization interfaces.