Framework for AI-Led Communications Evaluation
The International Association for the Measurement and Evaluation of Communication (AMEC) launched the GEO Principles in Dublin on 20th May. These principles provide a responsible framework for AI-led communications measurement.
AMEC’s GEO Principles and the accompanying resource ‘A Practitioner’s Guide to GEO Measurement’ are designed to help communications professionals understand the impact of AI-generated discovery and search technologies. These resources address the evolving information ecosystem shaped by AI-generated summaries and conversational search.
James Crawford, managing director of PR Agency One and AMEC Board Director, commented, “Anyone working in PR or communication will know how quickly clients and boards have started asking how GEO and LLM outputs should be measured.”
Development and Key Areas
Collaborative efforts among AMEC’s Agency Group, board members, academics, vendors, and practitioners over more than six months resulted in the development of the GEO Principles. Feedback and iterative testing were integral to this process.
The principles focus on three areas: upstream reputation signals, search and content readiness, and downstream AI outputs. They emphasise transparency by requiring documented methods, repeatable prompts, and clear limitations, ensuring AI outputs are treated as directional evidence rather than absolute truth.
Johna Burke, CEO and Global Managing Director of AMEC, stated, “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 Global Summit in Dublin featured the launch. A panel chaired by Rayna Grudova-de Lange, Founder and CEO of InsightHQ, highlighted the need for rigorous, transparent, and ethical evaluation in the evolving AI landscape.
Baseline evidence requirements introduced by the GEO Principles include repeatable prompts, documented methods, transparent assumptions, and clear limitations, reinforcing that AI outputs should be treated as directional evidence rather than absolute truth.
The work was led by contributors such as 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. Input was also provided by AMEC’s Academic Advisory Group and wider members.
