New global principles and practitioner guide set out a responsible way
to measure how organisations are found, interpreted and represented in
AI-generated answers
AMEC, the International Association for the Measurement and Evaluation
of Communication, has launched the AMEC GEO Principles and a companion
resource, _A Practitioner’s Guide to GEO Measurement_, to help
communications professionals measure the growing influence of AI-led
discovery, generative search and large language models.
The resources respond to a fast-changing information environment in
which AI-generated summaries, conversational search and zero-click
discovery are increasingly shaping how organisations, brands and issues
are found, understood and trusted online.
GEO, or Generative Engine Optimisation, is increasingly used to describe
how organisations appear in AI-generated answers and discovery
environments. AMEC’s principles are designed to help practitioners
assess this responsibly, without reducing measurement to simplistic
rankings, vanity metrics or opaque scores from individual tools.
The principles were developed over more than six months through AMEC
Agency Group collaboration, AMEC board review, academic scrutiny, vendor
and practitioner feedback, and iterative testing. The work was led by
primary contributors James Crawford of PR Agency One [1], Mary Elizabeth
Germaine of Ketchum [2], Ben Levine of FleishmanHillard TRUE Global
Intelligence [3], Matt Oakley of Hotwire Global [4], Amber Daugherty of
Big Valley Marketing [5] and Rob Key of Converseon [6], with input from
AMEC’s Academic Advisory Group and wider AMEC members.
The resources were launched at the AMEC Global Summit in Dublin on 20
May, during a panel chaired by Rayna Grudova-de Lange, Founder and CEO
of InsightHQ [7].
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The AMEC GEO Principles set out a practical framework for measuring
AI-led discovery across three connected areas: upstream reputation
signals, including earned coverage, third-party commentary, reviews,
expert content and owned assets; search and content readiness, including
whether an organisation’s digital presence is credible, accessible and
structured for interpretation by search engines and AI systems; and
downstream AI outputs, including how an organisation appears in
AI-generated answers, citations, framing, omissions and potential
reputational risk.
The principles also introduce baseline evidence requirements, including
repeatable prompts, documented methods, transparent assumptions and
clear limitations. They reinforce that AI outputs should be treated as
directional evidence rather than absolute truth, and caution against
relying on any single score, platform or tool.
James Crawford, managing director of PR Agency One and AMEC Board
Director, said:
“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.”
Johna Burke, CEO and Global Managing Director of AMEC, said:
“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.”