From understanding AI visibility to influencing it

When Sitecore acquired Scrunch, the vision was never just to help brands understand what AI was saying about them. The vision was to help them influence it, improve it, and ultimately turn those insights into action.

For decades, digital marketing was built around a relatively simple model. Buyers searched for information, clicked a link, landed on a website, and formed opinions based on what they found there. Brands invested heavily in search, content, digital experiences, and analytics because the website sat at the center of the customer journey.

That journey now starts somewhere else. Buyers are asking AI instead of relying only on search engines. In Forrester's 2026 survey of 18,000 business buyers, 94% used AI during their most recent purchase, and generative AI was the most meaningful information source at every stage of buying. They are researching products, comparing vendors, and exploring solutions through AI-powered assistants often before they ever reach your website.

Visibility was the first problem to solve. Before organizations could influence AI search, they needed to understand it. They needed to know what AI systems could find, what they couldn’t find, and how their brand appeared when buyers asked the questions that mattered.

It helps to distinguish what we’re trying to improve. AI discovery is how people find brands and information through AI-powered search, assistants, and agents. Discoverability describes how readily those systems can find and use your content. Visibility is the presence you can observe and measure, including how often your brand is mentioned and your content is cited in relevant answers.

Answer engine optimization (AEO) and generative engine optimization (GEO) are overlapping practices for improving how content appears in these experiences. For marketing teams, that work starts with understanding where your brand shows up today and which content needs attention.

Visibility should now be considered the foundation for improvement. Once teams understand how their brands are represented in AI, the next step is to act on those insights more quickly and consistently.

Customers want to understand where opportunities exist and have a practical way to turn that intelligence into better outcomes.

Ask a team how many of last quarter's AEO recommendations actually shipped and most can't say, and the ones who can rarely like the number.

SitecoreAI and Scrunch connect AI visibility insights with the work of improving and publishing content. Scrunch identifies changes in how your brand appears in AI answers and surfaces content optimization opportunities directly in SitecoreAI. Your team can review recommended updates in the CMS, apply supported changes, and move the revised content through its existing approval and publishing workflows.

That connection helps teams act while the opportunity is still relevant. The people responsible for the content can assess a recommendation where they already work, decide whether it is right for the page, and get the approved update published. Scrunch then continues monitoring mentions and citations so teams can assess how visibility changes over time.

Most brands sit somewhere on a four-stage path.

1. Anecdotal: Someone screenshots a bad AI answer and forwards it.
2. Monitored: A dashboard tracks presence and citations.
3. Diagnosed: Findings are prioritized and explained.
4. Operational: Findings become published changes on a cadence the team can sustain, and each change is measured.

Every tool in the category will take you as far as Diagnosed. Taking the step to Operational means owning the system where the change is made. SitecoreAI customers can now move beyond understanding how AI represents their brand and take action on those insights through the same workflows they already use to create, review, and publish digital experiences.

For enterprise teams evaluating platforms, the practical question is how easily an insight becomes an approved, published change and how they track what happens next. These capabilities are a useful starting point:

By rapidly converting recommendations into measurable improvements and making optimization part of your everyday workflow, your team is equipped to adapt to the constantly evolving ways customers discover, evaluate, and engage with your brand through AI.