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Editorial Board

What an Evidentiary Control Mechanism Looks Like in Practice

What an Evidentiary Control Mechanism Looks Like in Practice

How regulated organizations make AI outputs reconstructable, reviewable, and defensible across functions Most discussions of AI governance focus on policies, accuracy, or model behavior. In regulated environments, those concerns rarely determine outcomes. What matters after reliance is whether an organization can reconstruct what an AI system produced, under what controls,

When AI Becomes a System of Record: Why Evidence, Not Accuracy, Will Define Liability

When AI Becomes a System of Record: Why Evidence, Not Accuracy, Will Define Liability

For most organizations, artificial intelligence is still described as a tool. An assistant. A productivity layer. Something advisory rather than authoritative. That description is already false. Across regulated and commercial environments, AI outputs are being copied into reports, summarized in emails, referenced in decision rationales, surfaced to customers, and relied

When AI Health Advice Fails, the Failure Is Not Accuracy. It Is Evidence.

When AI Health Advice Fails, the Failure Is Not Accuracy. It Is Evidence.

AIVO Journal — Governance Commentary On January 2, 2026, The Guardian reported multiple cases in which Google’s AI Overviews delivered misleading or potentially harmful health information to users. The examples were unexceptional: dietary guidance presented to pancreatic cancer patients, interpretations of liver test results, and descriptions of routine screening procedures.

The Moment Non-Monitoring Becomes Negligence

The Moment Non-Monitoring Becomes Negligence

When AI-mediated decisions can be reconstructed, failing to do so becomes a governance choice A routine incident A customer contacts support to challenge a recommendation they received from an AI assistant. The assistant had explained why a particular product was suitable, summarized key risks, and ruled out alternatives. The

When AI Advice Fails: How Reasoning Visibility Determines Defensibility

When AI Advice Fails: How Reasoning Visibility Determines Defensibility

AIVO Journal — Governance Case Study (2026) Executive summary By 2026, AI failures in regulated environments are no longer edge cases. They are operational facts. What distinguishes resilient organizations from exposed ones is not whether failures occur, but whether those failures are inspectable, attributable, and governable after the fact. This article

When AI Disclosure Arrives Before Evidence

When AI Disclosure Arrives Before Evidence

Why the SEC Investor Advisory Committee Has Created an Evidentiary Gap AIVO Journal — Governance Commentary On December 4, 2025, the SEC Investor Advisory Committee approved a recommendation urging the Commission to consider a disclosure framework addressing the impact of artificial intelligence on issuer operations. The recommendation is non-binding, but

AI as an Attributable Representation Channel

AI as an Attributable Representation Channel

When AI-Mediated Suitability Claims Become a Governance Failure AIVO Journal — Sector Governance Analysis (Financial Services) Executive Summary Public-facing AI assistants increasingly provide guidance to consumers on financial products, risks, suitability, and comparative options. These outputs often appear in high-intent contexts and are relied upon as synthesized judgments