AI-Generated Answers Are Reshaping Brand Discovery
AI-generated answers in search are machine-written summaries from large language models that respond directly to user questions, often combining multiple sources into a single response and influencing which brands, products, and citations appear before users ever click a traditional search result. As AI summaries from tools like ChatGPT, Gemini, and Perplexity move to the center of buyer research, marketers face a new visibility problem: brand visibility in AI answers can now matter more than classic blue links. Gartner forecasts a 25% drop in traditional search volume as AI chatbots gain ground, while Pew Research Centre found Google users clicked a standard result in only 8% of visits when an AI summary appeared, compared with 15% without one. For many buyers, the AI layer now makes the first impression.
Inside Sitecore’s Scrunch Deal and the New AI Search Stack
Sitecore’s acquisition of Scrunch pulls AI search visibility directly into a mainstream digital experience platform. Scrunch was built as an AI customer experience system that tracks how brands appear, are omitted, or are misrepresented in AI-generated search results and conversational answers. Its Agent Experience Platform (AXP) reformats existing content so AI agents can read, interpret, and cite it without breaking the human experience on the page. Sitecore plans to plug these brand monitoring tools into its content management, marketing, and digital asset management workflows, turning “answer engine optimisation” from a standalone niche into a core part of day-to-day operations. The combined platform promises to surface where brand messages are missing or off-target, show which competitors AI answers prefer, and offer practical content changes to improve AI search optimization. For marketers, AI search becomes a measurable channel, not a black box.
From Monitoring to Action: Connecting Insights to Content Workflows
Scrunch’s role inside Sitecore’s ecosystem is to turn AI answer monitoring into a continuous optimization loop. The platform tracks buyer queries, brand representation, competitive positioning, source citations, and content gaps across large language models, then feeds those findings into Sitecore’s existing workflows. That connection means marketing teams can diagnose where AI-generated search results underrepresent them and then update landing pages, knowledge bases, and assets from the same environment. According to Sitecore, Akamai saw a 364% increase in brand presence for non-branded prompts and a 218% increase in citations after rolling out AXP-enabled pages, while Runpod reported a 400% increase in paying customers tied to AI search optimization efforts. Instead of treating AI search visibility as a one-off initiative, marketers can now fold it into regular content planning, testing, and performance measurement.
Shaping Brand Representation Across AI-Powered Search Engines
For marketers, the promise of AI search optimization is the ability to actively shape how AI systems describe their brands. Scrunch highlights where AI answers include or exclude a brand, what language they use, and which content the models cite, across AI tools such as ChatGPT, Google Gemini, and Perplexity. Sitecore’s integration then helps teams create or refine content so AI systems can interpret it more reliably, without sacrificing human readability. This covers everything from structured product data and FAQs to expert articles and customer proof. Sitecore CEO Eric Stine argues that “the internet must be written for machines to understand if we want humans to experience it,” framing brand visibility in AI answers as a prerequisite for customer trust. The outcome is not only more mentions, but clearer, more accurate explanations that guide buying decisions in AI-first journeys.
AI Search Optimization Becomes a Core Marketing Function
The Sitecore–Scrunch deal signals a broader shift in martech: AI search optimization is moving from experimentation to a standard discipline alongside SEO and paid media. A Semrush study reported that only 22% of US marketers surveyed have a fully integrated AI search and SEO strategy, and 37% say competitors are mentioned more often in AI results. This gap creates both threat and opportunity. Brands that treat AI search visibility as a core function can influence how answer engines evaluate options, which sources they trust, and whose content they surface when buyers ask non-branded questions. Tools that connect brand monitoring insights to content workflows give marketers a way to keep up as AI-generated answers evolve. Instead of waiting to see how AI describes them, organizations can now treat AI discovery as a managed channel that they test, tune, and measure over time.
