Large Language Models (LLMs) are fundamentally reshaping the landscape of search engine optimization.
As AI-powered tools and platforms become increasingly sophisticated, SEO and marketing professionals are faced with the challenge of adapting their strategies to this new reality.
In this post, we explore the practicalities of integrating LLM optimization into existing SEO frameworks.
We’ve gathered insights from leading SEO and marketing professionals, asking them to share their approaches to this integration and to identify the one key factor they prioritize when balancing the finer details of LLMs with traditional SEO principles.
Their responses offer a roadmap for navigating this evolving breakthrough and maximizing the potential of both traditional and AI-driven optimization techniques.
Read on!
Think Beyond Keywords
I’m trying to think beyond keywords and more in a conversational manner.
What would be the FAQs from the target audience when they run an AI search?
What would be their next question once they get an answer?
I think the way the article is structured around these FAQs is one of the key factors to optimize for LLM, while EEAT remains my key focus as I believe optimizing for EEAT guarantees quality content, no matter the research tool used.
Valerie Leroux
SEO Health Blog Writer & Editor, Bioty Healthcare
Align Content with User Intent
Integrating LLM optimization into an SEO framework involves aligning high-quality content creation with user intent and search engine guidelines.
A key factor is ensuring the content remains authentic and value-driven while utilizing AI-generated insights to enhance relevance and scalability.
Balancing creativity and data, I focus on crafting unique, engaging narratives optimized with precise keywords and semantic structures.
This approach ensures LLM-enhanced content resonates with users and ranks effectively, maintaining a synergy between automation and a user-centric SEO strategy.
Brenton Thomas
Founder, Twibi
Use AI for Enhanced Keyword Analysis
As an expert in SEO and marketing, it’s possible to build on an existing SEO strategy by incorporating the optimization of LLMs, or large language models. This is achieved by using AI tools for enhanced keyword analysis, content generation, and user intent detection.
Predictive LLMs such as ChatGPT or Google’s PaLM can help identify potential topics of interest and help create marketing articles, descriptions, or tags with better accuracy.
The first step is to integrate the results with the language of the brand and the expectations of the target audience because the attention-grabbing engaging material must not sacrifice search-engine friendliness. It ensures that AI acts as a modifier, but never a substitution for human-made imagination.
So, one aspect I focus on in finding this middle ground is the genuineness and contextual appropriateness of the material.
It is true that while LLMs work better with text generation now, their outputs have to be modified to prevent the creation of cutout copies and dull information. This means that more AI insights are implemented with the manual hand so that the audience can engage with the content.
For instance, instead of making AI the source of content production, I make it the source for revealing new patterns and optimizing better internal links, or content formats that lead to improved SEO as well as a better user experience.
Ultimately, I am focused on the ethical and tactical application of LLM tools in a manner that avoids the over-optimization I intend to steer clear of. In this field, quality matters more than quantity, which is why I tend to devise strategies that offer actual value to users while using acceptable SEO strategies like E-E-A-T (Experience, Expertise, Authority, Trustworthiness).
I maintain defined parameters on how and when I will be using LLMs so that AI tools are beneficial to my SEO strategy, instead of taking over it. This approach has proven to be effective in helping my clients foster organic traffic and engagement sustainably.
Pual Kelly
Founder, SEO Agency For Startups
Focus on Semantic Depth
Integrating large language model (LLM) optimization into an SEO framework is like navigating uncharted territory. It’s a balancing act between creating content that engages users and ensuring it aligns with how AI understands and prioritizes information.
I learned this the hard way while helping a tech client boost their underperforming blog content.
One key factor I focus on is semantic depth: moving beyond surface-level keywords to explore the context and relationships between ideas.
For instance, my client had a blog post titled “How Cloud Storage Works,” but when I analyzed it using an NLP tool and LLMs like ChatGPT, it became clear the content was too shallow. It covered the basics but failed to answer deeper, more intent-driven questions like “How does cloud storage handle hybrid models?” or “What happens in a data recovery scenario?”
We took an AI-assisted approach to rewrite it. By analyzing related queries and using LLMs to simulate user intent, we identified key areas to expand on: edge computing, hybrid storage solutions, and disaster recovery.
We also structured the content in a way that AI models love well-organized headings, concise answers, and layered depth. The result was a post that not only covered the basics but also anticipated long-tail questions, making it invaluable for readers.
The impact was immediate. Organic traffic increased by 40%, time-on-page metrics doubled, and the client saw a noticeable uptick in leads originating from that post. It wasn’t just optimized for SEO: it was designed to connect with users and AI models simultaneously.
The takeaway? Don’t create content for AI; create content with AI as your guide.
LLMs can help you spot gaps, anticipate user needs, and add depth where it’s lacking. But always remember: humans come first. When you create content that’s both user-centric and AI-friendly, you’ll strike the perfect balance for modern SEO success.
Martynas Siuraitis
SEO Consultant, The SEO Consultant Agency
Emphasize Non-SEO Human Content
For our business, at this point in time, the marketing relationship with LLMs is restricted to content generation. Even then, it’s got some important nuance to it – namely our growing emphasis on non-SEO-optimized, human-generated expert content.
LLMs allow users to generate extraordinary volumes of content. With well-formed prompts on ChatGPT alone, AI will deliver refined insights, articles, and advice on just about any topic.
Using specialist tools such as Scalenut and Surfer SEO allows you to go even further, automating the embedding of keyword clusters, ensuring disciplined article structure, suggesting authoritative links, etc.
However, that AI-generated content is somewhat of a race to zero i.e., if everyone and anyone can do it so easily, then the volume of noise becomes so loud that audiences stop caring. For example, LinkedIn now fires so much content at its users that many are obliged to turn it off in order to concentrate on their day job.
We’ve got plenty of expertise in-house. A key marketing goal is to use that authority to cut above the noise. We actively publish articles that have been hand-written. Moreover, it’s our policy that such articles are not SEO optimized and that the author is free to express themselves.
AI content generation for SEO is a rabbit hole that can rapidly become a comfort zone. While at present, there are some gains from leaning into LLM optimization of content, it’s clear from the growing influence of services such as Featured and Inspo, that demand for original thought leadership is on the rise.
The burden of proof for experts to prove they do indeed have authority in their domain is higher now than it was a couple of years ago when LLMs first burst into mass market consciousness.
For the moment, the SEO concept of Domain Authority is tied to specific quantitative metrics, measuring backlink volume, backlink sources, content structure, etc.
It wouldn’t be surprising to see the pendulum swing, at least a little, towards an approach that is more inclusive of qualitative factors and more assurances that an author is indeed who they claim to be.
Improve Content with LLMs
Integrating large language model (LLM) optimization into an SEO framework is a powerful way to improve content creation and boost search visibility. LLMs analyze huge datasets to identify trending keywords and phrases and audience preferences, making keyword research more targeted and effective.
They can also assist in generating high-quality, contextually relevant content that meets SEO best practices. When it comes to on-page SEO, LLMs help optimize keyword placement and ensure your content is clear and structured.
Still, human oversight is non-negotiable. While LLMs save time and increase efficiency, ensuring the content is high-quality, unique, and credible is up to you. When you pair AI tools with your expertise, you create a strategy that delivers real value to your audience while staying competitive in search rankings.
Shankar Subba
Head of SEO, WP Creative
Align Content with User Intent
Integrating LLM (Large Language Model) optimization into an existing SEO framework involves aligning content creation with how LLMs understand and prioritize information.
One approach I use is crafting highly structured, semantically rich content that answers user queries comprehensively. This includes using natural language and incorporating long-tail keywords that align with conversational search behavior.
A key factor I consider is user intent alignment. While optimizing for LLMs like ChatGPT or Google’s BERT, I ensure the content serves actual human needs first.
For example, instead of keyword stuffing, I focus on creating well-structured content with FAQs, schema markup, and concise answers that are LLM-friendly but also actionable for users.
This balance ensures the content performs well in both traditional SEO and AI-driven environments.
Nikita Sherbina
Co-Founder & CEO, AIScreen
Match Content to Search Intent
When integrating LLM optimization into SEO, the key is to adapt content to match search intent while staying focused on audience needs.
My approach is to create straightforward, concise content that answers user queries without stuffing keywords. The content needs to be natural with LLMs but still drive relevant traffic. I won’t overcomplicate things; if you create content that aligns with people’s desires, you won’t go wrong.
User engagement is a crucial factor to consider. If people spend time on a page and interact with it, that’s a strong signal to both LLMs and search engines that your content is valuable.
Instead of focusing purely on technical SEO, I emphasize how well content meets the audience’s needs and how they engage with it. Please keep it simple and focus on what users want to know.
Natalia Lavrenenko
UGC manager/Marketing manager, Rathly
Understand Limitations and Ensure Alignment
SEO professionals can harness Large Language Models (LLMs) by integrating AI into their content strategies while maintaining careful oversight. These models can assist in generating content drafts, but human review and editing are crucial to ensure quality and accuracy.
Beyond content creation, LLMs can support on-page SEO, user experience (UX) improvements, technical SEO tasks, and much more.
However, using AI tools strategically is essential, as well as understanding their limitations and ensuring alignment with SEO best practices.
By balancing AI capabilities with expert insights, SEO professionals can enhance efficiency and effectiveness across various optimization efforts.
Blake Baxendell
CEO, Digital Marketer, Wahha Design
Maintaining Contextual Relevance
Integrating LLM optimization into an existing SEO framework involves aligning AI-driven content strategies with human intent and search behavior.
At our SEO agency, we leverage LLMs to scale content creation while maintaining authenticity and alignment with user needs.
One key factor is contextual relevance—ensuring that AI-generated content answers real user queries while reflecting the brand’s tone and expertise.
For instance, we use LLMs to analyze search trends and generate topic clusters, but every output undergoes manual editing to meet E-A-T standards.
Striking the right balance also requires integrating LLM insights with traditional SEO pillars like link building and technical optimization.
By focusing on intent-driven content that complements user journeys, we ensure LLMs enhance—not replace—the human element critical to building trust and driving conversions.
Kay Velik
Communications and Partnership Director, Nine Peaks
On behalf of the BoostMyDomain community of readers, we thank these leaders and experts for taking the time to share valuable insights that stem from years of experience and in-depth expertise in their respective niches.
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