Reflections from the AMEC Global Summit 2026
Two years ago, Generative Engine Optimisation, or GEO, was still a side conversation in communications measurement. This year, at the AMEC Global Summit 2026 in Dublin, held from 19–20 May, it was firmly on the main agenda.
The Summit also marked AMEC’s 30th anniversary, a fitting moment to reflect on how far communications measurement has come, and how quickly it is being reshaped.
More than 300 delegates from 27 countries gathered for two days of discussion, bringing together communications practitioners, media intelligence specialists, researchers, academics and measurement leaders from around the world.
Across those conversations, one thing became clear. The industry is being pushed to rethink how visibility, trust and reputation are measured.
AI is no longer just a technology platform. It is changing how audiences search for brands, interpret information and, most importantly, how reputation is shaped.
These are the threads I took away from the Summit.
AI and GEO: PR's New Frontier
Greg Galant, Co-founder and CEO of Muck Rack, described this moment as “the era of answers.” It is a powerful phrase because it moves the conversation beyond traffic and rankings, and towards what people actually receive as the answer.
Muck Rack’s research, What is AI Reading?, found that around 84% of AI citations come from earned media, while only about 13% come from owned channels. As Greg put it, once you look at where AI gets its information, “it starts to feel a lot like PR.”
That should make communicators pay attention. Organic AI visibility cannot simply be bought. It has to be earned through credible, consistent and well-distributed information.
Jonny Bentwood, Global President, Data & Analytics at Golin, sharpened the point further: “We must market to machines just as much as we market to humans.” As zero-click search grows, communications teams need to understand not only what people see, but also what machines can find, read and cite.
Lou DeCosmo, Senior Director, Global Communications at PepsiCo, made the issue feel practical. For a company whose products are consumed roughly a billion times a day across more than 200 countries, GEO is not a niche experiment.
At that scale, AI platforms need to be treated as a new “tier one” alongside media and influencers. His advice was refreshingly practical: start small, find one advocate, work across teams and do not be precious about the first output.
The AMEC GEO Principles: Measuring Responsibly
AMEC's launch of its GEO Principles was the Summit's centre of gravity. Amid a gold-rush of GEO tools and bold vendor claims, AMEC stepped in to give practitioners a credible shared standard for measuring AI-led discovery responsibly.
Subsequently, this isn't a standalone novelty, it's the newest layer in a lineage that began with the Barcelona Principles in 2010, the industry's shared compass for measuring communication in a meaningful, transparent and outcome-driven way.
Refreshed roughly every five years, their fourth iteration, Barcelona Principles 4.0, unveiled in Vienna last year, brought AI, data integrity and ethics to the fore. The GEO Principles carry that same DNA into AI-led discovery, and the through-line is unmistakable: outcomes over outputs, quality over volume, transparency over black boxes.
The principles reframe what “good” looks like. GEO should not simply be about increasing visibility. It should assess whether stakeholders encounter information that is accurate, useful, current, credible and trustworthy.
That distinction matters.
At the heart of the principles is an ethical guardrail: improve the public information environment. Do not flood it with low-quality content. Do not disguise promotion as independent evidence. Do not treat AI outputs as fact without verification.
In a field moving this quickly, a responsible standard is not bureaucracy. It is what protects trust in the profession.
For practitioners who want to explore this further, AMEC has made the resources available to download: the AMEC GEO Principles, A Practitioner’s Guide to GEO Measurement, and the AMEC Data Quality Principles.
Reputation and Data Cannot Live in Silos
If one message ran through the Summit, it was this: data is the foundation, but it only creates value when it is connected.
Sandra Macleod, Group Chief Executive of Echo Research, made this point powerfully through the lens of reputation. Her recurring question: “reputation for what, among whom, for what purpose?”, is a reminder that numbers mean very little without context.
The challenge she sees, even in sophisticated organisations, is not always a lack of data. It is that the data is fragmented, trapped in silos and not speaking the board’s language.
But reputation does not sit neatly inside one function.
Sandra described reputation as a “team sport”: an enterprise-wide responsibility that requires cross-functional ownership. If a large share of an organisation’s value sits in its reputation, then the systems, resources and decision-making structures should reflect that.
Lauren Rosenberg,Vice President Analytics, Ketchum, showed what that connectivity can look like in practice. Her case study on building a communications intelligence platform focused on one source of truth for each data point, clear workflows and outputs designed around decisions.
Her warning was simple and important: “if intelligence does not reach the people making decisions, it dies.”
Quality and Narrative: The New Measurement Craft
Connected data still has to be good data, structured for meaning.
Matt Allison, Founder and CEO of Handraise pushed us past fragile citation-counting toward analysing the whole narrative landscape that trains the models. Executives increasingly want real-time judgement signals, not a report weeks after decisions have already been made.
That requires measurement to move beyond keyword mentions, volume and basic sentiment. Reputation is not formed by individual articles alone. Articles are signals. Narratives are the system.
Rob Key, Founder and CEO of Converseon was direct in conveying that "good enough is no longer good enough": sentiment at ~65% accuracy isn't fit for an AI world. "We don't have a hallucination problem, we have a confusion problem," he argued.
We are feeding models data that has not been structured with enough meaning. The fix is to become "context engineers" who build meaning into data before it reaches a dashboard or an LLM, with trust as the metric that matters most.
This is where communicators have an important role. We understand language, nuance, audience, context and framing. We should not only consume whatever comes out of a tool.
We need to help structure meaning into the data before it reaches a dashboard, a model or an AI-generated answer.
That is the new measurement craft.
The Human Job: Judgement, Context, Counsel
For all the discussion about AI, the strongest counterweight was the reminder that communications remains deeply human.
Professor Jim Macnamara (UTS) told a raw story of a restructure driven by an AI-led analysis that "didn't talk to anybody." The data told leaders what was happening; only humans, listening, could decide what to do and the plan that saved jobs came from talking to stakeholders.
"God is not in the machine," he reminded us, "you can't do communication from 30,000 feet."
Aaron Kwittken, Global Head of AI + Innovation of FGS Global, agreed, from optimism: "AI will write better than us, but it can't communicate." That line captures the distinction well. AI can draft, summarise, classify and process at speed.
But it does not replace judgement. It does not read the room. It does not understand when a message is technically accurate but emotionally wrong. It does not build relationships or carry lived experience.
Aaron’s human moat was judgement, expertise, lived experience and relationships. Sandra reinforced the same point from the boardroom: our job is to translate connected data into counsel that leaders can act on, in the language of value, risk and behaviour.
That is where communications adds its highest value.
Time to Elevate: Just Start
The Summit told one story: the profession is moving from counting to meaning, from visibility to trust, from outputs to outcomes - the very shift the Barcelona Principles have urged since 2010.
The fundamentals are not being replaced. They are being tested. And for those willing to lead, they are being rewarded.
But the loudest call to action was simpler than any framework: just start.
It echoed across the summit. Aaron put the stakes plainly: the risk of moving too slowly now outweighs the risk of moving imperfectly.
Communicators need to be bold enough to disrupt themselves before others do it for them. To claim a role in GEO rather than cede it entirely to another function. To connect data out of its silos. To help organisations row in the same direction. To be the AI optimists and evangelists their teams need. As Kwittken put it, optimism is a choice.
Thirty years on, AMEC’s community feels more necessary than ever. The tools are here. The principles are here. The opportunity is here.
The communicators who measure well, connect evidence, understand context and lead with both intelligence and humanity will define what comes next.
The only thing left is to start.
