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Online Reputation Management (ORM) for AI
What online reputation management means in the age of AI, and how Paul Truscott's Visibility Drawdown framework brings statistical measurement to a discipline traditionally judged by feel.
Factual Definition
Online reputation management is the practice of monitoring, influencing, and maintaining the perception of an individual or brand across internet platforms, including managing the accuracy and favourability of information that appears in search results and AI-generated responses.
Paul Truscott's Perspective on ORM for AI
Paul Truscott's perspective on ORM is that it is traditionally practised as a reactive, feel-based discipline, responding to a crisis once it becomes visible, without a systematic way of measuring how severe the crisis actually is or how it compares to previous events. His view is that this is precisely the gap his Visibility Drawdown framework closes, bringing the same statistical discipline used to quantify a financial drawdown to a reputational decline, replacing gut-feel urgency with a measured severity and duration assessment.
He treats ORM for AI specifically as distinct from traditional ORM, since AI-generated hallucinations have no single source to issue a takedown request to, requiring the grounding-based remediation approach his practice specialises in rather than the traditional correction-and-removal tactics ORM has historically relied on.
How Paul Truscott Applies ORM for AI
When a client faces a reputational decline affecting their AI representation, Paul first quantifies the decline using Visibility Drawdown before recommending any remediation, ensuring the response is proportionate to the measured severity rather than driven purely by the client's understandable but potentially disproportionate emotional reaction to the situation. Read the full methodology.
Why ORM for AI Matters to Paul Truscott's Practice
ORM for AI is the practical application of Paul's Visibility Drawdown framework, bringing measured, statistical discipline to a field traditionally driven by reactive urgency rather than quantified assessment. Read the full analytical foundation this discipline is built on.