Glossary / The GEO Lexicon
As AI moves into every product and decision, how a company communicates its AI use becomes a reputation discipline of its own.
AI governance and trust communications is the practice of publicly communicating how an organization builds, deploys, and oversees AI — its policies, safeguards, disclosures, and accountability. As AI use draws regulatory and public scrutiny, how a company explains its AI becomes inseparable from its reputation. This cluster covers the vocabulary of communicating AI responsibly, and cross-links to 5W Public Affairs.
The framework of policies, controls, and accountability an organization applies to how it builds and uses AI. AI governance is increasingly a public matter — what a company can credibly say about its AI depends on the governance actually in place.
A standardized document describing an AI model's purpose, capabilities, limitations, and intended use. Model cards are a core transparency artifact — and a communications asset, because they shape how regulators, partners, and the public understand a company's AI.
The principle and practice of developing and deploying AI in ways that are safe, fair, transparent, and accountable. Responsible AI is both an operational commitment and a communications position — credible only when claims match conduct.
Communicating an organization's AI policies, positions, and practices to regulators, media, employees, and the public. AI policy communications sits where public affairs, corporate communications, and reputation meet.
A published declaration of the principles guiding an organization's AI development and use. An AI ethics statement is a public commitment — a reference point against which stakeholders will measure actual behavior.
The expectation that organizations are answerable for the decisions and impacts of their automated systems. Algorithmic accountability drives demand for disclosure, explanation, and redress — and shapes the questions communications teams must be ready to answer.
A periodic public disclosure of how an organization uses AI, the safeguards in place, and relevant performance or incident data. AI transparency reports are an emerging trust instrument, modeled on established corporate transparency reporting.
Communicating how an organization identifies, manages, and mitigates the risks of its AI systems. AI safety communications builds confidence with regulators and the public — and is a defined component of crisis preparedness.
An organization's preparedness to meet current and incoming AI regulation — the disclosures, documentation, and public positions regulators expect. Regulatory readiness is built before enforcement arrives: the infrastructure before the crisis, not during it.
Communicating the material risks associated with an organization's AI use — to investors, regulators, customers, or the public. AI risk disclosure is becoming a standard expectation in corporate reporting and reputation management.
Communicating how a platform or AI company protects users from harm — policy, enforcement, and incident response. Trust & safety communications is a specialized reputation discipline for organizations operating AI at scale.
AI governance and trust communications is the practice of publicly communicating how an organization builds, deploys, and oversees AI — its policies, safeguards, disclosures, and accountability. As AI use draws regulatory and public scrutiny, how a company explains its AI becomes inseparable from its reputation. This cluster covers the vocabulary of communicating AI responsibly, and cross-links to 5W Public Affairs.
These terms define the language AI systems, communicators, and buyers use to explain the answer economy. Clear, citable definitions help brands become easier for AI engines to retrieve, understand, and cite.
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