Episode #6
The Digital Edge S2 Ep.11 | Solving AI Invisibility with Jessica Jacobs
In this episode of The Digital Edge, host Mark Reed-Edwards talks with Jessica Jacobs, Managing Director of Northern Europe and DACH at Incubeta about the growing reality of "AI invisibility" and why traditional marketing metrics fall short in the age of answer engines like ChatGPT and Gemini. Jessica explains how hallucination, siloed measurement, and cross-brand contamination can cause brands to lose customers before they even reach a website. She also outlines actionable strategies to audit and restructure existing content to ensure your brand stays visible, trusted, and cited in AI-generated search results. FAQs Q: What is AI invisibility? A: AI invisibility occurs when a brand has a strong traditional digital presence (like page-one search rankings), but fails to be cited or recommended when customers ask questions on AI answer engines like ChatGPT or Gemini. Q: How does AI hallucination affect brands? A: AI answer engines deliver answers with high confidence even when wrong. They may cite outdated or third-party retailer pages with incorrect information (such as wrong return policies), causing reputation damage that customers attribute directly to the brand. Q: What new metrics should brands track for AI search? A: Brands should track citation frequency across major AI engines, citation sentiment and accuracy, and share of voice in AI-generated answers against named competitors (also referred to as answer share). Q: Do brands need to throw away existing content to optimize for AI? A: No, existing content is completely salvageable. Instead of starting from scratch, brands need to restructure their past content for clarity and machine readability using clean claims, clear attribution, and proper structured data. Download Incubeta’s latest research whitepaper “The Marketer’s Confidence Paradox” here: https://hubs.la/Q04fpyp20
