On this week’s episode of the Niche Pursuits podcast, Travis Talent and I discuss what enterprise-grade SEO really looks like in today’s AI-driven landscape. Travis is the Managing Director of SEO and CRO at Brainlabs, where he leads a team of 90 people working with some of the world’s biggest brands.
While much of our conversation covers big-picture SEO strategy at scale, we explore specific examples of what it takes to get meaningful results in this ever-changing search environment, especially in the second half of the interview. Let’s share the highlights from our conversation, from organizing SEO on millions of pages to AI search and optimizing for LLMs like ChatGPT and Perplexity.
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SEO at Scale: Beyond random acts of optimization
Travis highlighted one of the biggest problems with SEO at any level: Relying on “random acts of SEO.” In his view, many brands, even enterprise brands, favor isolated events like technical audits or one-off content briefings that fall short of a broader, organized strategy. His solution is to move from optimization to orchestration.
Highlights from Travis:
- 50% of his role is focused on defining high-level SEO strategies for new clients.
- SEO works best when closely aligned with product developers, developers, content creators, and CRO teams.
- Brands should avoid focusing solely on audits or one-off tasks; they need a long-term, integrated plan.
He likens traditional SEO to a house, with tech SEO as the foundation, on-page SEO as the framework, and CRO as the staging. In contrast, today’s SEO is more like a city with multiple platforms (Google, TikTok, Reddit, YouTube, LinkedIn) feeding search and AI systems.
How to prioritize when you have 61 million pages
Travis provided an example of a prime client with 61 million pages and over 20 million keyword rankings. Obviously, it is not possible to optimize every page. This is where prioritization frameworks come from.
He introduced a framework called RISE:
- Radius to reach: Measure the reward by identifying where the off-brand keyword opportunities are.
- Intention: Match content creation to what your audience is looking for and where they meet.
- Scale: Decide how to efficiently create or update content using evaluation systems like the RICE model.
- Execution: Align all stakeholders with established communication tempos and quarterly planning.
Highlights from this strategy:
- Focused on AI-related content with high growth and low competition.
- It detected large blocks of low-performing content due to internal connectivity issues.
- Scripting and automation are used to make these at scale.
Winning with Content in an AI-First World
One of the most interesting parts of the interview was Travis’ insight into content strategy in the age of AI search. While some SEOs shy away from content that drives clicks because of AI reviews, Travis has a different take.
He believes that upper funnel content is no longer just about traffic: it’s about visibility:
- Visibility in AI Views and large language models (LLM).
- Creating brand awareness early in the search journey.
- Building topical authority through expert-led, multi-platform content.
The approach to content creation at Brainlabs:
- Interviews with subject matter experts to inform long-form articles.
- Using pull quotes, expert lines and multimedia formats.
- Focus on strategic discovery content that drives long-term brand visibility.
According to Travis, 50% of all content online is now generated by artificial intelligence, allowing the real experience to shine through well-crafted human-generated content.
Measuring Success: Not Just Rankings Anymore
When it comes to delivering results, Travis takes a sophisticated, multi-layered approach. It’s not just about rankings or raw traffic. For mature brands, success depends on wider visibility and revenue impact.
Important dimensions:
- Visibility on search engines and platforms (Google, YouTube, LinkedIn, Reddit, etc.).
- Increase in brand search volume, especially from AI-driven queries.
- As a proxy for AI search performance, referral traffic increases.
- Lifetime value and income attribution whenever possible.
In his 12-month experience review, he shared:
- The brand saw a 400% increase in SEO-optimized traffic.
- They earned 2,000 net-new page one keyword rankings.
- They became the most cited brand in AI search results for their industry.
Optimization for AI Search and LLM
Artificial intelligence is reshaping the way search results are delivered, and Travis is already ahead of the curve. It differentiates LLMs like ChatGPT or Perplexity with Google’s views on AI and adjusts optimization efforts accordingly.
Main differences:
- AI Views: 98% of citations come from first page rankings. Traditional SEO still rules.
- LLMs: Less advanced scanners; It also cannot handle JavaScript or dynamic rendering. They rely heavily on how content is structured and analyzed.
Tactical tips:
- Do not rely on client-side rendering for important data.
- Make your content easily digestible by using short paragraphs, structured information, and clear headings.
- Opt for static, accessible content that LLMs can definitely scan and understand.
AI Conversations in the C-Suite
Travis shared that conversations on the board are now centered around the broader implications of AI. Leaders think well beyond SEO.
Topics that come to their mind:
- Focus ad budgets on content and multimedia that feed AI models.
- Adapting products and services to stay relevant in an AI-powered world.
- Using SEO data (especially from social platforms) to guide paid media strategy.
Interestingly, Travis is more involved in the conversation about paid strategy than ever, simply because SEO teams now have the data they need to help brands compete effectively in AI-powered environments.
What to do if you’re not yet Enterprise level
For SEOs working with small and medium-sized sites, Travis recommends not trying to be everywhere at once. Instead, start with a deep understanding:
- Know where your audience stands and double down on this platform.
- Build visibility where competitors are weak.
- Move to new platforms only after building a foothold.
The “be everywhere” strategy works, but it needs to be approached in stages to be sustainable.
Final Thoughts
This episode provided a rare look at how SEO works at the highest scale and strategy. Travis Tallent didn’t just talk about AI in the abstract; he told us how this is changing content priorities, platform strategies and even how enterprise brands define success.
Keynote speeches:
- Enterprise SEO is about orchestration, not isolated tactics.
- Frameworks like RISE and RICE help prioritize and scale SEO effectively.
- AI search is already changing how content is found, and visibility is the new traffic.
- Brands need to play the long game by being present on multiple search platforms and formats.
Whether you’re running a 100-page site or a 61-million-page behemoth, the principles remain the same: understand your audience, scale your efforts intelligently, and prepare for an AI-dominated future. Stay tuned for more episodes that break down SEO in practice, not just in theory.
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