It is quite evident that B2B professionals are leveraging AI-powered search tools, such as Perplexity and Google’s AI Mode, to make purchase decisions.
Whether it is learning about a new product or evaluating two different service providers, large language model (LLM) based chatbots streamline the overall process.
Consequently, brands are steadily losing organic traffic in varying degrees. When users find the answers to their questions right in AI’s summaries, they are less likely to click on the link.
On the other hand, traffic from LLM-driven search engines, such as Perplexity, ChatGPT, and Google’s AI Mode, is on the rise. Ahrefs has studied 82,000 sites to conclude that AI traffic has grown almost 10x over the last year.
Of course, the increased AI traffic and brand awareness come from targeted efforts. These efforts, collectively known as AI SEO, use artificial intelligence to improve search rankings and LLM visibility.
In this article, let’s understand AI SEO and identify what B2B marketers can do to leapfrog their competition during this market shift.
What is AI SEO?
Artificial Intelligence Search Engine Optimization (AI SEO) is the practice of using LLMs to enhance content to increase its visibility and relevance across search platforms. The search platforms include traditional search engines like Google and Bing, and AI-enabled search tools, such as Perplexity and ChatGPT.
AI SEO achieves two key goals for B2B brands:
Streamlines their existing content production (and SEO) process
Boost visibility in LLM-powered search engines
Apart from accelerating tasks in traditional SEO workflows, such as topic ideation and proofreading, AI SEO helps businesses earn credible citations in LLM-generated summaries in search results.
The practices make it easy for AI models to go through your website’s content, extract relevant information, and serve it effectively to your audience. This is non-negotiable, as traditional SEO and content marketing efforts were primarily designed for traditional search engines.
AI SEO, in a practical sense, will future-proof your brand’s digital presence by surfacing your messages in concise LLM-generated answers. These mentions, even if they direct little traffic to your website, leave a lasting impression on your audience, which improves brand recall down the line.
Core Components of a B2B AI SEO Strategy
These are the ingredients you need to gain visibility and reach through AI search engines.
1. Conversational and Structured Content
LLMs are trained to hold human-like conversations with users. If you write articles that flow like a natural dialogue, AI models can “understand” the content easily. Consequently, your message will be more likely to be referenced and cited in tools like Perplexity and ChatGPT.
It also means logical reasoning should follow a coherent pattern. Modern LLMs can easily detect flaws in logic and reasoning. When things don’t make sense, they may refrain from using your content to answer a user’s question.
Structure translates to the text formatting of your content. Proper structure means using headings, subheadings, paragraphs, and bullet points whenever needed. This practice makes the content scannable for AI search bots.
2. Technical Foundations for Machine Readability
B2B websites should be fast and safe. This is done when you follow technical SEO best practices, such as compressing images, removing internal redirects, fixing 404 errors, and keeping robots.txt updated.
These efforts help both search bots and LLMs go through your blog posts and landing pages efficiently when generating answers for your audiences.
Additionally, B2B marketers should focus on semantic HTML tags that clearly define their meaning, such as <article> and <footer>, and consistent internal linking to reinforce authority and content hierarchy.
3. Shift From Keywords to Intent
When drafting content for your B2B brand, prioritize the intention of the article, such as educating the audience or differentiating your product, over keywords.
This doesn’t mean that you ignore the keywords entirely. Keywords are still essential as they are relevant to your audience’s pain points and your offerings. They are useful for conducting research and shaping your message.
The body of your message, however, should emphasize the concern of your audience, which should be specific to a particular phase in the B2B buyer journey. To put it simply, each content piece should solve one problem or answer one question of your potential customer.
4. AI Tools in Content Production
B2B marketing teams are now operating on a much shorter timescale. If there is a new trend or emerging topic, delivering a piece quickly will help you capitalize on the buzz. The longer you wait, the more likely your competitors will beat you to it.
An effective way to accelerate your content production process is to leverage AI tools for various tasks in your writing process. For instance, SurferSEO can help you produce comprehensive outlines.
Similarly, Perplexity can speed up research, and ChatGPT can proofread your draft in under a minute to suggest edits that improve the piece.
How to Execute an AI SEO Strategy
The usual B2B content creation process remains unchanged. You start with ideation and go through outlining, drafting, and reviewing before hitting publish.
However, the approach to some tasks within the process has evolved.
1. Customer-Driven Topic Discovery
Traditional SEO started the ideation process with keywords, as that was the most reliable data available. This was caused by the very nature of search engines, where you can only enter a few terms related to your problem.
However, LLM-based search tools allow users to explain their problems in detail, and sticking with a keyword-first approach can backfire.
Therefore, it’s more effective to start your content production process by putting your customers at the center. Use real-world data to discover their problems, questions, and expectations. Then, you can use the relevant keywords when drafting to enhance the content further.
2. Contextual and Semantic Research
LLMs allow users to explain their problems in natural language. These models analyze the query to uncover the intent and objective of the user, which could be educational or commercial.
Based on the context and semantics of the message, AI search tools scrape the web for relevant information. Finally, the information is stitched together in a conversational format for the user to ensure engagement.
B2B brands must adapt by shifting their focus from absolute keywords to the purpose of their content pieces. Each blog post or landing page should deliver value to a potential customer rather than simply targeting a few keywords.
3. AI-First Content Creation
AI models are more likely to prefer content that is clear and easy to understand. LLMs can easily identify the central idea and context around it to serve users with the relevant extracts.
Poorly formatted articles or whitepapers that are filled with industry-specific jargon will have the opposite effect. Keep in mind that most search engines use lightweight LLMs over reasoning models for speed. These lightweight models will struggle to understand complex and indirect content.
Simply put, you need to break things down and explain them in plain English to your audience because that’s how your audience looks for solutions to their problems.
4. Technical Optimization for AI Search Bots
AI bots take longer to go through an article compared to search engine bots because they “read” the body of the content to “understand” the context. Hence, it’s crucial to help them move fast through your website when trying to find a personalized answer to a user’s specific query.
B2B companies must maintain a logical and clean site architecture optimized for mobile devices. Such websites have shorter load times and rank higher, maximizing your chances of making it into AI-generated summaries.
5. Targeted Distribution and Monitoring
AI search tools enable your audiences to enjoy hyper-personalized content experiences when finding new information or evaluating products and services.
Likewise, to maximize the impact of your pieces and increase credibility for these LLM-based search engines, you should distribute your message in relevant corners of the internet. This is pivotal for building a strong and consistent digital presence across the web.
LinkedIn, YouTube, guest posting, and media outreach are some of the content distribution methods that can be customized based on your current B2B marketing needs. You can set UTM parameters and pipelines to track the efficacy of each effort.
6. Audit and Optimize Existing Content
If you have been publishing branded content to promote your B2B products or services, chances are you’ve already relayed your core message. Rather than reinventing the wheel and producing new creatives from scratch, you can just tweak them for relevance and engagement.
Audit your past articles, blog posts, landing pages, case studies, etc., to discover areas of improvement. You can easily update them by adding new and updated statistics, facts, and insights.
Even evergreen content pieces can be refreshed by updating the metadata and rewriting some sections, such as converting a couple of paragraphs into a set of bullet points.
Apart from improving your AI search visibility, this will also give you new content ideas for your upcoming B2B marketing campaigns.
AI SEO Challenges
Like every B2B content marketing strategy, AI SEO can pose roadblocks. Let’s look at some difficulties you might encounter and how to overcome them.
1. Overreliance on AI for Content Creation
B2B marketing teams are increasingly relying on generative AI solutions, such as ChatGPT and Claude, to accelerate their creative process. While this is helpful for creating content quickly, it can affect the overall efficacy of a campaign.
For instance, your blog posts may lack empathy or emotionality, which is critical for engaging readers. Similarly, LinkedIn posts written in a wooden tone will fail to encourage your audience to share their perspective.
It is essential to publish human-crafted content with AI’s assistance rather than the other way around. This will allow you to create a message that speaks to your audience.
2. Tracking Wrong Metrics
Organic traffic to your blog can take a hit due to AI search tools. Hence, you must focus on other metrics across platforms to ensure your content marketing efforts are targeted and delivering the desired results.
Impressions, citations in AI summaries, social media engagement, newsletter subscribers, and demo requests are a few key performance indicators (KPIs) to measure your B2B content’s performance.
3. Maintaining Alignment with Stakeholders
B2B marketing is not a one-person show. Writers, marketers, sales professionals, and business leaders need to get on the same page before any content is drafted. Similarly, multiple team members are involved in editing, reviewing, and publishing the piece.
As the principles and practices around AI SEO are still in their infancy, it’s natural to have disagreements on certain aspects. For instance, you may want to create thought leadership content, while others may suggest LinkedIn posts for improving overall brand presence.
To tackle this, start by designing campaigns based on tangible organizational goals. Let’s say you currently want to increase your social media following by 50% in the next three months. The B2B content marketing strategy should be shaped around that.
4. Keeping Up with Rapid Changes
LLM vendors like Anthropic and OpenAI are constantly releasing new models that can “reason” and “think” better. This evolves how AI search tools, such as Perplexity and ChatGPT, generate answers for users.
Additionally, the AI-powered marketing tools used to aid B2B content creation change too. Consequently, marketing teams have to tweak their workflows to make the most out of them.
You need to run experiments and quarterly audits to evaluate your tech stack, philosophies, workflow, and strategies. This proactiveness will help you stay ahead of the curve and leapfrog the competition.
Boost AI SEO Visibility with Growfusely
B2B brands need to invest in AI SEO today to leapfrog their competition and capture domain authority in LLM-based search results. Visibility in AI summaries is pivotal for earning high-intent traffic and leads.
However, enhancing your existing content, establishing strong technical foundations, creating AI-first content, and distributing them across platforms at scale can be challenging when done in-house.
Growfusely can do that for you, allowing you to focus on core marketing and sales activities.
Our team will create and distribute expert-led, LLM-friendly branded content that puts your audience at the center.
Ready to reach your potential customers via Perplexity, Google’s AI Mode, and ChatGPT?
How can AI SEO improve lead generation for B2B companies?
AI SEO helps you rank in generative search results, increases topical authority, and improves content discoverability. By answering buyer-intent queries clearly, you attract more qualified leads early in their decision-making process.
What’s the difference between traditional SEO and AI-powered SEO strategies?
Traditional SEO focuses on keywords and rankings. AI SEO emphasizes user intent, semantic relevance, and structured content optimized for large language models and answer engines like Google SGE and ChatGPT.
How do I measure ROI from AI SEO in a B2B marketing context?
Track impressions in AI-powered results, homepage traffic, and dwell time. Combine this with CRM data to tie content influence to sales pipeline growth and closed deals.
Which AI SEO tools are best suited for enterprise-level B2B marketers?
Tools like Clearscope, MarketMuse, SurferSEO, and Jasper support semantic optimization and scalable content creation. Platforms like Ahrefs and Google Search Console still help track traditional performance and technical health.
How do I ensure AI-generated content aligns with EEAT and brand voice?
Use AI for efficiency, but involve subject matter experts to verify facts and tone. Apply brand style guides, include author bios, and cite credible sources to maintain trust and meet EEAT standards.
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