AMEC has waded into the generative search measurement land grab. The International Association for the Measurement and Evaluation of Communication launched its GEO Principles plus a companion resource, A Practitioner's Guide to GEO Measurement, at the AMEC Global Summit in Dublin on 20 May.

The timing is no accident. Clients and boards are already demanding answers on how their organisations show up in AI-generated responses, and a cottage industry of vendors is rushing to sell them scores. AMEC's move is a direct, if diplomatically worded, response to that chaos.

GEO — Generative Engine Optimisation — is the label increasingly attached to how organisations appear in AI-generated answers and discovery environments. The problem for practitioners: nobody has agreed on how to measure it. The new principles try to fix that without collapsing into the very thing AMEC warns against — simplistic rankings, vanity metrics and opaque single-tool scores.

Who built it, and how

The principles took more than six months to develop, moving through the AMEC Agency Group, board review, academic scrutiny, vendor and practitioner feedback, and iterative testing. Six primary contributors led the work: James Crawford of PR Agency One, Mary Elizabeth Germaine of Ketchum, Ben Levine of FleishmanHillard TRUE Global Intelligence, Matt Oakley of Hotwire Global, Amber Daugherty of Big Valley Marketing, and Rob Key of Converseon. AMEC's Academic Advisory Group and wider membership also weighed in.

Rayna Grudova-de Lange, founder and CEO of InsightHQ, chaired the Dublin launch panel.

A three-part framework

The principles lay out a practical measurement structure across three connected areas:

• Upstream reputation signals — earned coverage, third-party commentary, reviews, expert content and owned assets.
• Search and content readiness — whether an organisation's digital presence is credible, accessible and structured for interpretation by search engines and AI systems.
• Downstream AI outputs — how an organisation appears in AI-generated answers, citations, framing, omissions and potential reputational risk.

That last category is where reputational risk lives: what the machines omit can matter as much as what they say.

The principles also set baseline evidence requirements. Repeated prompts. Documented methods. Transparent assumptions. Clear limitations. And a firm stance that AI outputs count as directional evidence, not absolute truth — with an explicit caution against relying on any single score, platform or tool. That caution lands squarely at the feet of the measurement vendors currently marketing GEO indices with little methodological disclosure.

Crawford: the industry is asking, the answers are uneven

James Crawford, managing director of PR Agency One and an AMEC board director, was blunt about the state of the market.

"Anyone working in PR or communication will know how quickly clients and boards have started asking how GEO and LLM outputs should be measured. There is excellent innovation taking place, but there are also uneven standards, overclaiming, vanity metrics and methodologies that are not always transparent enough.

"AMEC has a responsibility to bring discipline to that conversation. These principles give the industry a more rigorous way of looking at AI-led discovery: one that recognises its importance, but also its limits. The most useful measurement will come from triangulating evidence: the reputation signals that feed the information environment, whether organisations are technically and editorially discoverable, and what AI systems then present to users."

The triangulation argument is the heart of the framework. No single data point — not a share-of-voice figure in ChatGPT, not a citation count in an AI overview — tells the story on its own.

Burke: transparency or bust

AMEC CEO and global managing director Johna Burke framed the initiative as an accountability exercise for the whole industry.

"As AI increasingly shapes what people see, trust and act upon, the communication industry must hold itself to higher levels of transparency, evidence and accountability.

"The AMEC GEO Principles were built through global collaboration across agencies, practitioners, academics, technology leaders and AMEC's international community because no single organisation, platform or perspective can fully define or measure AI-driven discovery alone.

"This initiative reflects the collective expertise, scrutiny and commitment of professionals across regions who understand that rigorous, transparent and ethical evaluation is essential to maintaining trust in the AI era."

What it means for practitioners

The context driving all this: AI-generated summaries, conversational search and zero-click discovery are reshaping how organisations, brands and issues get found, understood and trusted online. Comms teams that built their measurement programmes around clip counts and reach now face a discovery layer they can't see with legacy tools.

The AMEC framework gives practitioners a defensible answer when a client asks for "our GEO score." The honest response, per the principles: show your prompts, document your method, state your limitations, triangulate across upstream signals, readiness and downstream outputs — and treat whatever number emerges as directional, not gospel.

Whether vendors racing to monetise GEO measurement will adopt the evidence requirements is another question. The principles carry industry weight, not enforcement power. But for measurement teams under pressure to produce AI numbers yesterday, they now have a standard to point to — and a reason to push back on black-box scores.