How Sitecore AI and Scrunch Are Transforming Content Strategy
The way buyers discover brands has fundamentally changed. Before a user ever lands on your website, an AI system has already shaped their perception. Brands to include in the response, who the competitors will be, and what sources will be used have all been determined. When someone reaches out to you directly, chances are they've already formed an opinion about you.
This is the new reality of content creation, and it calls for a new approach to doing business. To survive, businesses need to keep generating, collecting, and connecting content in such a way that AI understands it.
Answer Engine Optimization (AEO) is rising and Sitecore's acquisition of Scrunch on June 3, 2026, is one of the clearest signals yet that the industry is moving decisively in this direction.
For developers building on Sitecore's composable DXP, this acquisition isn't just a marketing headline, it reshapes the content pipeline, the data workflows, and the tools available to drive real business outcomes.
1. The AI Visibility Problem Sitecore Is Solving
Most enterprise content was never built for machines. It was built for humans navigating websites, reading blogs, and clicking CTAs. Bots have been generating more web traffic than people representing almost 60% of all HTTP requests to HTML content. That's a structural mismatch between how content is published and how it's being consumed.
When an AI system answers a query, it decides which brands appear, which competitors get mentioned, and which sources it cites. By the time a buyer reaches a brand directly, they have often already formed an opinion based on those answers.
Scrunch was built to address exactly this. The platform tracks buyer queries, brand representation, competitive positioning, source citations, and content gaps in AI systems across LLMs including ChatGPT, Gemini, and Perplexity. For Sitecore developers, this means the platform can now surface where content is working, where it's missing, and where it's being misrepresented before it costs conversions.
Why it matters for your content pipeline:
- Visibility into which content assets are influencing AI-generated answers
- Identification of brand misrepresentation across major LLMs
- A clear diagnostic layer before any content optimization begins
2. Scrunch's Agent Experience Platform (AXP): Content Built for Machines
The core of Scrunch's technical value is the Agent Experience Platform (AXP). Scrunch's AXP reformats existing content so AI agents can read and use it accurately, without altering the experience built for human visitors.
Scrunch launched a redesigned website that delivers dual experiences from a single URL serving one version tailored to human users and another optimized for AI agents using structured, lightweight HTML. This is the architectural direction enterprise content is heading: the same source, two output layers.
For developers, this is significant. You're not rebuilding your Sitecore implementation. AXP layers on top of existing content infrastructure, making it machine-readable without compromising the UX you've built for end users.
Developer benefits of the AXP model:
- No disruption to existing frontend architecture or rendering pipelines
- Structured, lightweight HTML served specifically for AI agent consumption
- Cleaner separation between human-facing and machine-facing content layers
3. From AEO to a Continuous Optimization Loop
Standalone AEO tools stop at diagnosis they show you where you win or lose in AI answers and where competitors show up. Sitecore described the combined offering as moving brands from standalone Answer Engine Optimization to a continuous content optimization loop that connects discovery data to the content, experience, and workflow infrastructure marketers already use.
Scrunch's recommendations will be integrated into SitecoreAI Content Management, Content Marketing, and Digital Asset Management products. This means insights from AI search visibility don't sit in a separate dashboard they feed directly into the tools content teams are already using.
Scrunch also expanded its Content Gaps capability, moving from diagnostics to execution by converting prompt, citation, sitemap, and search-volume insights into structured briefs for human or AI content creation.
What this loop enables:
- Insight from AI search automatically triggers content workflow actions
- Content gaps convert into structured creation briefs no manual translation required
- Unified platform for discovery data and content activation
4. Knowledge Studio and Enterprise Knowledge Management
Scrunch introduced Knowledge Studio, a beta product for enterprise customers that connects internal repositories Notion, SharePoint, uploaded files into its platform. AI agents transform this proprietary data into sourced knowledge documents that can be reviewed, edited, and approved to serve as an internal source of truth for AI-generated responses.
For enterprise Sitecore implementations, this is a meaningful unlock. It means brands can govern how their proprietary knowledge surfaces in AI answers with human review built into the process before that content influences outputs.
The Knowledge Studio workflow emphasizes governance and brand control by incorporating human review and conflict flagging before information is used to influence AI output.
Enterprise use cases for Knowledge Studio:
- Internal documentation surfaced accurately in AI-driven buyer research
- Governance layer ensuring brand-approved knowledge reaches AI systems
- Reduces risk of AI systems citing outdated or incorrect proprietary data
5. Proven Outcomes: The Business Case
The acquisition wasn't built on theory. Customer results validate the investment.
Akamai compared AXP-enabled webpages against comparable non-AXP webpages across tracked AI search prompts and models, finding a 364% increase in brand presence for non-branded prompts and a 218% increase in citations in AI-generated results.
Runpod used the Scrunch platform to expand prompt tracking and identify rendering and indexing issues that were limiting AI discoverability, reporting a 400% increase in paying customers associated with its AI search optimization efforts.
These aren't marginal improvements they're structural gains from making content machine-readable and continuously optimized within the platform.
Best Practices for Developers Working with SitecoreAI and Scrunch
- Audit your existing content for AI readability before configuring AXP identify pages with rendering or indexing issues that may be limiting AI discoverability.
- Prioritize high-authority pages first. Scrunch recommends optimizing existing high-authority pages for AI readability before pursuing new content creation.
- Use structured, information-dense content. Detailed, technical posts referencing specific companies and products secure more AI citations than generic high-engagement content.
- Integrate Content Gaps briefs into your CMS workflows treat AI-generated briefs as structured inputs for your content team, not optional suggestions.
- Connect Knowledge Studio to internal repositories early. The sooner your proprietary knowledge is structured and approved, the earlier it starts influencing AI-generated answers accurately.
- Track competitive positioning across LLMs not just branded queries. Non-branded prompts represent discovery moments where buyers are still forming opinions.
The Bigger Picture
AI systems influence brand perception: which offerings appear in answers, which competitors get mentioned, and which sources are cited. By the time buyers reach a brand if they reach it at all they have often already formed a point of view.
Sitecore CEO Eric Stine put it plainly: the internet must now be written for machines to understand if we want humans to experience it. The Scrunch acquisition makes that possible within the same DXP developers already work with no new platform, no disconnected tooling.
For teams building on SitecoreAI , this is the moment to treat AI visibility as a first-class requirement in content architecture not a marketing add-on. Content that isn't readable by machines is content that doesn't exist in AI-driven discovery.
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