New Guidelines Address AI-Led Discovery
AMEC, the International Association for the Measurement and Evaluation of Communication, launched the AMEC GEO Principles to enhance the rigour of AI-led communications measurement. This significant announcement took place on 20th May at the AMEC Global Summit in Dublin. The GEO Principles provide a responsible framework for assessing AI-generated content.
Addressing the increasing influence of AI, these new guidelines shape how organisations, brands, and issues are perceived online. GEO, or Generative Engine Optimisation, requires a focus on responsible assessment beyond simplistic rankings and vanity metrics.
James Crawford of PR Agency One, a primary contributor, expressed the urgency of the initiative: “Anyone working in PR or communication will know how quickly clients and boards have started asking how GEO and LLM outputs should be measured.”
Collaborative Development of the Principles
Over a six-month period, the principles were developed through collaboration with the AMEC Agency Group, academic review, and input from vendors and practitioners. Key contributors included 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.
Johna Burke, CEO of AMEC, highlighted the need for transparency: “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.”
Requirements for repeatable prompts, documented methods, and transparent assumptions are introduced by the GEO Principles. They advise against reliance on single scores or platforms, reinforcing that AI outputs should serve as directional evidence rather than absolute truth.
During the AMEC Global Summit in Dublin, the principles were launched, marking a collective effort to establish ethical evaluation standards in AI communications. Practitioners will find these guidelines helpful in navigating the complex landscape of AI-led discovery and measurement.
A practical framework is set out by the principles for measuring AI-led discovery across three interconnected areas: upstream reputation signals, search and content readiness, and downstream AI outputs. These areas encompass earned coverage, third-party commentary, reviews, expert content, and owned assets.
Baseline evidence requirements, such as repeatable prompts, documented methods, transparent assumptions, and clear limitations, are introduced by the AMEC GEO Principles. They reinforce that AI outputs should be treated as directional evidence rather than absolute truth.
James Crawford, Mary Elizabeth Germaine, Ben Levine, Matt Oakley, Amber Daugherty, and Rob Key led the work, supported by AMEC’s Academic Advisory Group and wider AMEC members.
