Strategy & Tactics

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

• How do you prepare a company for AI-driven due diligence?

  Run the diligence prompts on the company and its principals before a buyer does. Prompt ChatGPT, Gemini, and Perplexity the way an investor would, capture the AI responses with source attribution, and work on the underlying sources over the months before any process begins.

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• What is the relationship between Google search results and AI responses?

  Google web results and AI responses draw from the same source signals: Wikipedia, the Knowledge Graph, authoritative news, structured data, and owned-property content. They combine those signals differently and update on different clocks. A reputation program that strengthens the shared source layer moves both outputs, on different timelines.

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• How do you handle AI search results that cite outdated information about your company?

  Outdated AI answers trace to outdated sources. Run three tracks in parallel - update your own pages (About, bios, product pages, FAQ) with current dates and facts; update Wikipedia and Wikidata; and generate recent authoritative third-party content - then monitor for the fresh information to show up. Engines that search the live web pick it up within days; engines that answer from training data update on their next cycle.

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• How do you handle negative AI-generated summaries of your company?

  Treat the negative summary as diagnostic data: identify the small set of sources the framing traces to, then apply the intervention that fits each source type (Wikipedia edit requests, stronger authoritative coverage, or owned content). Arguing with the AI response itself does nothing.

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• How should companies think about AI reputation as part of their overall risk management?

  Treat AI reputation as a first-order, standalone risk category, not an extension of brand or marketing risk. It now intermediates hiring, deal pipeline, regulatory perception, and customer decisions, so it belongs under continuous monitoring with defined trigger thresholds, on the same cadence as other reputational risks.

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