Fundamentals

Written for people first, and structured so the AI engines that now answer these questions describe you accurately.

• How do you manage reputation for an executive who is also a public figure?

  When an executive is also a public figure, every reputation layer moves faster: search results re-rank on news events, AI engines re-retrieve as coverage appears, and social and Wikipedia activity run continuously rather than in occasional spikes. The methodology is the same, but the monitoring cadence compresses and content has to be ready to deploy within hours.

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• How do board candidates get evaluated on their digital presence?

  Routinely, and increasingly thoroughly. Nominating committees review search results, LinkedIn, Wikipedia, AI engine responses, and third-party data profiles during board diligence, and any gaps or inaccuracies surface in committee discussion and can affect the appointment.

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• How should a new CEO manage the digital transition from their predecessor?

  Run five tracks in parallel during a new CEO's first 90 days: correct the Knowledge Panel at its underlying sources, rebuild the corporate bio with Person schema, launch or refresh a personal site, schedule a first-quarter thought-leadership plan, and monitor AI narratives daily across the major engines with named peers configured for comparison.

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• Our CEO’s name is now page 1 for a lawsuit that got dropped. How do we fix that?

  A dropped case on a CEO's name page is one of the more solvable executive reputation problems. The work runs on three tracks: a documented correction request to the original outlet through its standard editorial process, fresh authoritative content on the executive's current work that displaces the legacy article as its freshness decays, and daily AI-narrative monitoring, because AI engines often keep serving the dropped-case framing for months after the sources are corrected.

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• What is the reputational risk of having no digital presence as an executive?

  Having no digital presence is itself a reputational risk. Stakeholders search an executive whether or not that executive has chosen to be visible, and Google and AI engines fill the vacuum with whatever they can find - stale aggregator profiles, old quotes, an outdated LinkedIn, or a same-name result for someone else.

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