The Internal Capabilities Needed to Win in AI-Influenced Search

For the last decade, SEO lived in a predictable silo. The SEO team handled rankings. Content, brand, and demand gen handled messaging and campaigns. Everyone stayed in their lane.

That doesn’t work anymore.

AI-influenced search has changed what gets cited and where that information lives. Help centers can get more citations than marketing pages. Product documentation answers technical queries. Third-party review sites shape competitive perception. The content that drives visibility is scattered across departments that don’t typically collaborate.

AI search isn’t won with more tools or more content. It’s won with independent, cross-functional teams that know exactly what to execute and can operate wherever customers discover your brand, not just in marketing. 

Specifically: the ability to coordinate knowledge across teams that have historically operated independently.

What Large Enterprises Need to Win in AI Search

Most large enterprises have everything they need to win in AI search. They have help centers with thousands of articles. Product documentation. Established brands. Customer success teams. PR teams getting thousands of media mentions. And strong marketing and SEO teams optimizing all the campaigns and content. 

What they don’t have is coordination between those functions.

Marketing tells one story. Product docs tell another. Support articles use different words. PR pitches a different narrative. Legal signs off on language that never gets used. It’s not a messaging problem,  it’s a communication, ownership, and system-sprawl problem.

When AI models synthesize information about your company, they’re pulling from all of these sources. If those sources are inconsistent, the model either picks one at random or creates something generic that doesn’t match any of your positioning.

And here’s the key point: the companies earning the most frequent and useful citations won’t be those publishing the most content, but those maintaining consistency across every public surface because their teams are truly aligned.

 Our research into citation patterns shows that five organizational capabilities consistently separate companies that appear in AI responses from those that don’t.

Cross-Functional Coordination Between SEO, Brand, Product, CS, and PR

This is the foundational capability everything else depends on.

• SEO knows what matters and how to structure content for extraction.
• Brand knows how the company should be positioned. 
• Product knows what the product actually does. 
• CS knows what questions customers ask most often. 
• PR knows what third parties are saying.

None of these teams can win in AI search alone. SEO can optimize the marketing site perfectly and still lose visibility if the help center is a mess. Brands can have perfect positioning and still get described incorrectly if product docs use different terminology. Products can have comprehensive documentation and still not show up if structured data is missing 

Cross-functional coordination means these teams have regular touchpoints, shared priorities, and aligned incentives. Not quarterly check-ins. Ongoing collaboration on content planning, publishing, and measurement.

In practice, this looks like:

• SEO and brand aligning on approved terminology before content gets created. 
• Product and CS coordinating on which features need public documentation and which questions need help articles. 
• PR and SEO share intelligence on how the company is being described in third-party sources and where gaps exist. 
• Legal and everyone else establishing pre-approved language for common factual claims so content can move quickly.

The capability here isn’t “have an SEO team” or “have a brand team.” It’s “these teams can make decisions together and execute in coordination.”

It’s not a talent gap, most organizations are missing the connective bonds and common targets that make scale possible.. Teams operate independently, optimize for different metrics, and only coordinate when there’s a conflict.

Strong Brand Direction That Gets Enforced Across All Content

Brand teams typically own positioning and messaging. What they often don’t own is enforcement.

Marketing uses brand-approved language. Product docs don’t. The help center doesn’t. Sales enablement materials don’t. Everyone interprets the brand guidelines differently or ignores them entirely because there’s no mechanism to ensure consistency.

In AI search, this fragmentation is visible. When someone asks “What does [your company] do?”, the model pulls from multiple sources. 

If your marketing site says “workflow automation platform”, your help center says “productivity software”, and your product docs say “business process management tool”, the model synthesizes something that probably doesn’t match what brand wanted.

The capability needed here is brand authority that extends beyond marketing. 

Brand defines how the product should be described, what terminology to use, which features to emphasize, and what category you compete in. Then that direction gets enforced across every team that publishes content.

This requires executive support. A senior, adequately resourced leader of brand language who can establish standards and drive compliance across product, customer success, and marketing teams.

It also requires documentation. Not a 50-page brand book nobody reads. A single source of truth that answers: What do we call our product? How do we describe what it does in one sentence? What features do we lead with? What category are we in? Which competitors do we acknowledge?

Every team that creates public-facing content should be working from the same answers.

Clear Product Specs That Everyone Can Access

Product teams know what the product does. Which features exist, what integrations are supported, what the technical requirements are, what’s launching next quarter.

That knowledge usually stays in product. Marketing writes benefit-forward content without detailed specs. CS answers support questions based on what they’ve learned, not documented truth. Sales makes claims that may or may not be accurate.

When AI models look for factual information like “Does [product] integrate with Salesforce?” or “What are the system requirements?”, they need specific, accurate answers. If that information doesn’t exist publicly or exists in multiple conflicting versions, you lose visibility.

The capability needed is a single source of truth for product information that everyone can access. Not internal wikis or Slack threads. Accessable, easy to process,documentation that’s maintained, current, and structured for extraction.

This means the product needs to document features, integrations, requirements, and limitations in a format that’s accessible to AI models and useful to other teams. And the data behind it is easy to consume and use at the scale of your enterprise. 

Marketing should be pulling from this when they write product pages. CS should be referencing it when they create help articles. SEO should be auditing it for structure and completeness.

Most enterprises have product documentation. What they don’t have is product documentation that’s treated as the authoritative source for all other content about the product.

Alignment with PR on Third-Party Perception

For competitive queries, third-party sources dominate. Organic discovery can’t directly control what G2 says about your product or how an analyst positions you in a market landscape. But PR can influence it.

The capability here is regular coordination between SEO and PR on third-party perception. SEO tracks how the company is being described in AI responses and where competitive positioning doesn’t match internal positioning. PR identifies campaigns that matter most and works towards ensuring an accurate and well positioned set of third party placements..

This requires both teams to see third-party sources as shared responsibility. PR isn’t just focused on press coverage. SEO isn’t just focused on owned content. Both are monitoring and influencing how the brand appears in external sources that AI models cite.

Practically, this means PR prioritizes analyst briefings and review platform management with the same rigor as press outreach. SEO provides PR with intelligence on which sources are being cited most often and where information gaps exist.

Most enterprises have PR teams and SEO teams. What they don’t have is regular collaboration between them on competitive positioning in third-party sources.

Faster Decision-Making and Publishing Processes

AI models prioritize current information. If your competitor can publish accurate specs for a new feature in three days and your legal review process takes three weeks, the model cites your competitor.

Speed matters more in AI search than traditional SEO. In traditional search, you could update a page whenever and gradually improve rankings. In AI search, whoever has the most current answer when the model looks wins that moment.

The capability needed is faster publishing cycles for factual updates. Not for new marketing claims or promotional content. For straightforward factual information like feature updates, integration additions, pricing changes, policy updates.

This requires pre-approved language for common scenarios so content doesn’t need full legal review every time. It requires authority for certain teams to publish factual updates without waiting for multiple approval layers. It requires processes that distinguish between “new marketing claim that needs review” and “factual update that can move quickly.”

Most organizations are their own worst enemy of progress and have thorough review processes. What they don’t have is differentiated processes that allow factual content to move faster than promotional content.

What Success Looks Like

Companies that have built these capabilities look different operationally.

When they launch a new feature, product, marketing, CS, and SEO coordinate on where that information needs to appear and publish it simultaneously across product docs, help articles, marketing pages, and integration directories. All using consistent terminology defined by brand.

When SEO identifies that third-party sources are describing the product incorrectly, PR has established relationships and processes to update that information.

When a pricing change happens, pre-approved language exists and content gets updated across all surfaces within days, not weeks.

When someone asks an AI assistant about the company, the response is consistent because every source the model pulls from is aligned.

These capabilities don’t require new tools. They require different ways of working. Shared priorities. Regular coordination. Authority that crosses departmental lines. Processes that allow speed where speed matters.

The companies that move fast, and adopt these capabilities, will win in AI search.