AIVO Journal

The Agent Decides

Every finding we've published so far assumes a person is still there. Someone opens a chat, asks a few questions, reads a recommendation, and either acts on it or doesn't. Even when a brand gets displaced at the third or fourth turn of that conversation, a

When Agents Want Things

A summer thought experiment for executives who think they've already priced in AI Every framework in this Journal so far assumes something convenient. It assumes the agent doing the recommending has no interests of its own. It ranks. It weighs context. It survives or doesn't survive

Recalled Is Not Recommended

Most of what gets published about AI brand visibility is vendor content wearing a research costume. This month, Harvard Business Review ran something different: a real study, credentialed authors, a methodology that holds up. It deserves a real response, not a dismissal. The research. John Gale, Luca Cian, and Luc

The Assistant Can't Keep a Secret

Luxury has spent a century teaching customers to read between the lines. A model built to answer questions plainly may be structurally unable to Take away the label and show a product against a blank, spacious background, more room than the object needs, nothing crowding it. To a human, that

The Committee You Can't See

Forrester's 2026 State of Business Buying report puts a number on something most vendors already suspected but couldn't prove. The typical B2B buying decision now involves 22 people: 13 internal stakeholders, nine external influencers. When the purchase includes genAI features, the buying group roughly doubles compared

Four Questions Worth Asking Before You Trust an AI Visibility Score

A public fight between two well-funded measurement companies revealed the real problem. It isn't the number either of them is defending. The CEO of a $19 million company told a few thousand marketers that a $1 billion competitor had a data problem. Brian Stempeck, who runs Evertune,

The Feed Is Becoming the Decision

Gen Alpha skipped the search box entirely. What replaced it may be the same gatekeeper problem, wearing a different interface A fourth grader in Colorado stands outside a Sephora, addressing a TikTok audience of strangers who've been debating whether she should be there at all. She walks the

What GEO Can and Can't Prove

A new academic survey of 45 studies checked the industry's most-cited claim against the evidence. It didn't hold up. The number shows up everywhere in GEO (Generative Engine Optimizaton) sales material: content optimized for AI search sees up to a 40% lift in visibility. It

Trust Breaks in Two Places, and Neither Is Visible

Why a recommendation can be trustworthy, sincere, and still not lead to a sale A bank can be validated early in a conversation with an AI system, recognized, credible, genuinely a contender, and still be quietly eliminated by the time the system reaches its final answer. That's not

The Zero-Click Blind Spot

Why the biggest source of AI-influenced revenue doesn't show up in any analytics dashboard, and what we're proposing to do about it A buyer asks an AI assistant for a recommendation. The assistant reasons through the comparison, names a brand, and the buyer, a few

What People Say About AI Recommendations, and What They Do

Two recent studies point in opposite directions, and the gap between them is the interesting part Ask travelers directly, and they say they don't trust AI to recommend where they should stay. A study published this month in Tourism Management, built on interviews, focus groups, and validated survey

Media Transparency Couldn't Be Delegated. Neither Can This.

Why GEO and AEO are necessary but insufficient, and why the decision belongs to the CMO, not the practitioner who built the current dashboard A decade ago, marketing leaders faced a version of this problem already, and most of them got it wrong for years before a handful of them

Recommended Is Not Booked

A question we're beginning to ask, not yet an answer we have An AI system reasons through a multi-turn conversation about a family trip. Dates, budget, a preference for all-inclusive, a location in Turkey. It compares options, weighs trade-offs, and lands on a recommendation. A

The Price Is Not Right

Why correct prices are becoming invisible to the systems now shopping on your buyers' behalf Zendesk's pricing page loads fine in a browser. Every plan, every tier, every number, all there. But when an AI agent tried to read that same page to answer a buyer'

Agentic Brand Control 101: What It Is, Why It Exists, and How It's Measured

Agentic Brand Control℠ is a brand's ability to survive an AI system's multi-turn reasoning process and remain the recommended choice at the point of final decision, not merely to be mentioned somewhere along the way. Most brand-AI measurement today stops at citation or visibility:

Procurement teams are learning a lesson brand teams already know

A Forbes Technology Council piece this month made a sharp observation about AI in procurement: the technology doesn't repair broken operations, it reveals them. Deploy AI across fragmented supplier data, siloed ERP systems, and inconsistent workflows, and the cracks don't disappear. They surface faster. Replace "

Profound's Own Report Proves the Wrong Point

“Christmas in July: How Retailers Win the AI Shelf” is careful, well-sourced work. Read closely, its own numbers argue against its own headline Profound published a report this month, “Christmas in July: How Retailers Win the AI Shelf,” on how retailers win what it calls the AI shelf. It

No One Is Watching the Purchase Order Fire

Consumer AI shopping still has a human in the loop. B2B procurement may already be past that point, and that changes what a displacement failure actually costs Nearly everything published about AI displacement, including our own research, has measured a world where a human still clicks confirm. That world is

A Standard Should Say When It Changes

brand.context v2.0 is live. Here is why it was revised, and what's actually changed in the market since April We published brand.context in April, a machine-readable standard for brands to declare purchase-decision evidence to AI systems. We're publishing version 2.0

It Already Knew

The market is done with diagnostics. It wants the gap closed, and closing it requires knowing exactly what kind of gap it is The head of GEO at one of the world's largest beauty companies said it to us directly. His management is done with diagnostics. Another dashboard,

The Decision-Maker Has Moved

Introducing the Agentic Shelf, and why twenty-five years of “get found” strategy no longer determines who gets chosen Tim de Rosen and Paul Sheals ·  July 2026 For twenty-five years, digital marketing rested on one assumption nobody said out loud: the customer was the one who decided. Every technology

Revenue at Risk from AI Displacement

A Methodology for Quantifying the Financial Exposure Created by Systematic Brand Displacement in AI Recommendation Flows  ABSTRACT  This working paper introduces Revenue at Risk from AI Displacement (RaR-AID) as a formally defined category of enterprise financial exposure and presents a structured methodology for its calculation. As AI systems become

The Cannes Reckoning - what the industry got right, what it missed, and what Q3 demands

THE CUTTING EDGE AI Brand Strategy   ·   June 2026   ·   Tim de Rosen, CEO AIVO Cannes Lions 2026 is over. The panels have packed up. The rosé has been cleared. And the marketing industry has arrived at a broad consensus: AI search is real, AI recommendation matters, and brands that do not

The Human Agentic Gap

STRATEGY · AGENTIC COMMERCE · BRAND PLANNING What removing humans from the shopping loop means for CMO and CDMO planning - and why most brand investment is being built for a world that is already disappearing. The consumer was never just a target. They were, unknowingly, a participant in the brand’s survival.

The model knows. It doesn't choose.

Introducing the Linkage Gap: the structural divide between AI knowledge and AI recommendation, measured across 1,427 brand probes in ten industries. AIVO Meridian Research  ·  doi.org/10.5281/zenodo.20761232 Across 1,427 brand probes spanning ten industries, 95.7% of brands are already recognised by large language models