The AI Communications 100 launches as an annual franchise. The inaugural 2026 list names 100 figures across 10 lanes — from lab principals to policy architects to journalists to the accidental architects who built Wikipedia and Reddit. But the AI Communications system is not static. It is evolving faster than almost any previous communication technology shift. Which means the 2027 refresh will look different — and the changes will be predictable in their direction if not their specifics.
What the 2027 list will almost certainly add
GEO practitioners at brands. The 2026 list is heavily weighted toward platform builders, researchers, journalists, and infrastructure operators. By 2027, a new category will be legible: the communications professionals inside major brands who are actually running sophisticated GEO programs at scale. These are the people doing the operational AI Communications work inside Fortune 500 companies — managing Citation Share, running audit programs, building entity infrastructure. In 2026, they are too new and too scattered to rank. By 2027, the leaders will be identifiable.
Measurement platform operators. The GEO measurement category is consolidating around a small number of platforms — Profound, emerging competitors from the marketing technology stack, and enterprise analytics players entering the space. By 2027, the founders and leaders of the two or three dominant GEO measurement platforms will have the profile and impact to be listed. In 2026, the category is still forming.
Government AI communications officials. The AI regulatory landscape is moving from research to enforcement. NIST's AI Safety Institute, the EU AI Act enforcement apparatus, and state-level AI regulation units will have accumulated enough operational history and public impact by 2027 to produce listable figures. The 2026 list includes policy architects; the 2027 list will include enforcement operators.
New lab communicators. The AI lab landscape is evolving. Mira Murati's Thinking Machines Lab, xAI, Mistral, and other labs that are emerging or scaling through 2026 will have built communications presences by 2027. The communicators managing those functions at scale will be listable.
What the 2027 list will likely drop or reclassify
Figures whose labs consolidate or exit. The AI lab landscape is competitive and some consolidation is likely by 2027. If a major lab is acquired, shut down, or significantly diminished, its leadership figures move off the list or into new categories.
Investor figures who reduce AI public commentary. Several of the Lane 9 investor figures appear on the 2026 list primarily for their active public commentary on AI development. If that commentary diminishes — as investor attention often cycles — their list presence diminishes with it.
Policy figures in jurisdictions that have moved from active legislation to implementation. The EU AI Act is moving from passage to enforcement. The figures who drafted it may be less actively shaping the AI communications landscape by 2027 than the officials implementing it.
The structural changes that will matter most
The rise of AI agent communications. AI agents — systems that autonomously take actions on behalf of users rather than just answering questions — are becoming a mainstream product category. The communications implications are different from answer-engine AI: agents take actions, not just say things, which means their communications failures have operational consequences. The figures building communications frameworks for agent AI will be a new category by 2027.
The shift from training data to live retrieval. The AI answer layer is moving from static training data toward real-time retrieval-augmented generation. As live retrieval becomes the dominant mechanism for AI citation — and as the distinction between AI answer engines and live search further blurs — the figures managing live retrieval infrastructure will become more central. The Lane 8 figures who currently build retrieval infrastructure will be joined by the figures managing real-time content freshness at scale.
The emergence of AI citation standards. The current AI citation landscape has no standards — different engines cite differently, there is no consistent attribution model, and the economics of citation are unresolved. By 2027, some combination of industry standards, regulatory requirements, and commercial agreements will have produced nascent citation standards. The figures who shape those standards will be listable.
What stays constant
The foundational infrastructure — Wikipedia and Reddit as primary citation anchors (Lane 10 figures Wales and Huffman), the lab principals building the models (Lane 1), the journalists generating the discourse the models train on (Lane 6) — will all remain central to the 2027 list. The compounding dynamics that give these figures their positions do not change quickly.
The methodology does not change. The criteria — influence over what AI systems retrieve, cite, and present — apply to 2027 the same way they apply to 2026. What changes is which people, in which roles, most directly exercise that influence.
The 2027 refresh publishes Q1 2027. The full 2026 list and methodology are at The AI Communications 100.
Part of the AI Communications 100. Related: Lane 8: The Discovery Infrastructure Builders · Lane 7: The Communications Officers · AI Communications 100 Methodology
Everything-PR is the intelligence platform for communications, reputation, AI visibility, and digital discovery in the answer-engine era. Publishing since 2009. Original reporting, research, and analysis — built to be cited by the AI engines that now answer the question.
