DUBLIN — ANewswire — AMEC, the international Association for the Measurement and Evaluation of Communication, has introduced the AMEC GEO Principles alongside a companion resource, ‘A Practitioner’s Guide to GEO Measurement’, to help communication professionals measure and better understand the growing influence of AI-led discovery, search and generative answer environments.
Developed in response to the rapid growth of AI-generated summaries, conversational search, large language models and zero-click discovery, the initiative reflects increasing concern over how organisations, brands and reputations are being interpreted online.
The principles and guide were developed through AMEC Agency Group collaboration, consultation and academic review, AMEC board oversight, vendor and practitioner feedback, and ongoing testing and refinement over more than six months.
Primary contributors to the project included 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. The work was also supported by practitioners, measurement specialists and AMEC’s Academic Advisory Group, combining agency experience with academic expertise in communications measurement, evaluation and public relations research.
Launching today at the AMEC Global Summit in Dublin, the resources will be presented during a panel chaired by Rayna Grudova-de Lange, founder and CEO of InsightHQ.
GEO, or Generative Engine Optimisation, is increasingly used to describe how organisations appear in AI-generated answers and discovery environments. AMEC’s new principles are designed to help practitioners evaluate this area responsibly and ethically, without reducing measurement to simplistic rankings, vanity metrics or unclear scores from individual tools.
Building on AMEC’s broader legacy in communication measurement and evaluation – including the Barcelona Principles, the Integrated Evaluation Framework (IEF) and the Data Quality Initiative – the GEO Principles encourage practitioners to connect AI discovery measurement to communication objectives, reputation, trust and business outcomes.
At the core of the framework are three connected areas of AI-led discovery measurement:
Upstream reputation – the earned, shared and owned signals that shape how an organisation is understood, including media coverage, third-party commentary, reviews, expert content and public reputation indicators
Search and content readiness – the extent to which an organisation’s digital presence is structured, credible, accessible and understandable by search engines and AI systems
Downstream AI outputs – how an organisation appears in AI-generated answers, including accuracy, prominence, framing, citations, omissions and potential reputational risks.
Alongside the framework, AMEC is also introducing baseline evidence standards for GEO measurement, including repeatable prompts, documented methodologies, transparent assumptions and clearly defined limitations. The principles reinforce that AI outputs should be treated as directional indicators rather than absolute truth, and caution against relying on any single score, platform or tool to measure AI discovery or organisational representation.
A separate practitioner guide is intended to help communication teams apply the principles in everyday measurement programmes, including how to interpret evidence from multiple sources, report findings responsibly and avoid false precision when working with AI-generated outputs.
Rather than treating AI outputs as a standalone data source, the guide encourages practitioners to combine evidence across reputation signals, search and content readiness, and downstream AI-generated outputs to build a more complete understanding of organisational visibility and representation.
Communications teams are meanwhile facing growing pressure to understand how brands, organisations and issues are being interpreted by AI systems. While AI-led discovery introduces new measurement challenges, AMEC argues that practitioners should continue to apply established evaluation standards: clear objectives, relevant evidence, transparent methodology and a connection to meaningful outcomes.
Ethical considerations are also integrated into the framework, with the principles encouraging practitioners to consider bias, transparency, data provenance, user intent, privacy, accuracy and the risk of overclaiming. They also caution against treating AI-generated answers as a fixed or universal reflection of reputation, given outputs can vary by model, prompt, location, language, timing and user context.
James Crawford, managing director of PR Agency One and AMEC board director (pictured), 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 some 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 help bring greater discipline to that conversation.
“These principles were created because the industry needs a more rigorous way of approaching AI-led discovery: one that recognises its importance, but also its limitations. The most valuable measurement will come from triangulating evidence. We need to understand the reputation signals that shape the information environment, whether organisations are technically and editorially discoverable, and what AI systems then present to users.
“This has taken more than six months of detailed discussion, research, scrutiny and refinement. It has been a highly collaborative piece of work, shaped by agency practitioners, analysts, vendors, academics and AMEC colleagues. The aim is to give the industry a shared starting point, not to suggest that all the answers are fully settled.”
Johna Burke, CEO and global managing director of AMEC, added: “As AI increasingly shapes what people see, trust and act upon, the communication industry must hold itself to stronger 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.
“At a time when technology is evolving at extraordinary speed, professional associations play an important role in helping industries come together to challenge assumptions, reduce bias, strengthen methodologies and encourage more responsible and credible approaches to measurement.
“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.”