Whenever I start writing something new, I always start with a fundamental question: Who is the audience? It sounds simple, but the answer shapes everything. It influences the language we use, the messages we emphasize, and the information we include. These choices then determine whether we educate, persuade, inform, or inspire action. For B2B marketers, this question applies to virtually everything we produce. This is especially the case when AI search optimization is so top-of-mind. This concept applies to website content, sales collateral, press releases, thought leadership articles, and case studies.
But today, another question deserves our attention: Should we be writing for humans or for AI?
Increasingly, our content must serve both audiences. People still need compelling stories, relevant insights, and clear reasons to trust us. Meanwhile, AI systems are changing how buyers discover information, evaluate vendors, and develop purchasing shortlists.
AI is summarizing our content, extracting key facts, and citing our expertise in generated answers. AI agents may also navigate websites to gather information on behalf of prospective buyers.
This creates a new challenge for B2B marketing teams. How do we optimize content for AI search without compromising the human experience?
This topic is part of the New B2B Marketing Strategy based on AI, TRUST, and Influence. Read the full article here.
The good news is that we don’t need two completely different sets of content! A single strategy, executed correctly, can achieve both goals. Here are five practical ways to do it.
1. Start With the Audience, Then Make Your Message Explicit
Understanding your audience remains the foundation of effective communication. Before writing, identify who needs the information, what they care about, and what you want them to understand or do. For B2B marketers, that might mean addressing a CIO’s technology concerns, a CFO’s financial priorities, or a sales leader’s pipeline challenges. The more clearly we understand these needs, the more relevant our content becomes.
Now consider how AI systems interpret that same content. They need to identify what a company does, whom it serves, and what problems its products solve. Vague messaging makes that task harder.
Consider the difference between saying, “We help businesses unlock their potential,” and explaining, “We help enterprise software companies automate complex workflows using AI.” The second statement gives people a clearer understanding of the offering. It also provides AI systems with specific information they can interpret and potentially reference.
The takeaway: Define your human audience first, but express your message with enough clarity and specificity for machines to understand it, too. This is a foundational principle of AI search optimization.
2. Write Clearly, Structure Content Logically
Good writing has always depended on clarity. Yet marketing content often becomes unnecessarily complicated. This is especially the case for those of us marketing technical products. It is so easy to fall into the trap of using industry jargon, lengthy introductions, and clever phrases that obscure the message. After all, we need to portray ourselves as Subject Matter Experts (SMEs), right?
Here is the offset: Not all of your readers will be SMEs. And, with all the acronyms and abbreviations, it is always a good strategy to dumb it down a bit, at least to start. Humans may struggle to understand this content (and not want to ask for help). AI systems may also have difficulty identifying its central points, particularly when important information is buried in long passages.
The solution isn’t to eliminate personality or reduce every message to a collection of bullet points. Instead, organize information so readers can quickly find what matters. Use descriptive headlines, informative subheadings, and paragraphs focused on a single idea. Introduce the main point early, then provide supporting details and examples. Use lists when they genuinely improve readability.
This approach works across websites, product brochures, and press releases. Every reader should be able to scan a page and understand its main message without reading every word. Clear structure also helps AI systems identify relationships between concepts and retrieve relevant information. Descriptive headings provide context, while direct explanations make key points easier to interpret.
The takeaway: Write for people who scan, read, and evaluate. Structure content so AI systems can identify its meaning. Clarity benefits both audiences.
3. Answer Real Questions with Specific, Useful Information
Buyers rarely begin their research with a company’s preferred marketing message. They start with questions. Which solution addresses my problem? How does this technology work? What differentiates one vendor from another? What results can I expect? What risks should I consider? These questions should influence the content we create. Rather than simply describing product features, explain the problems they solve and the outcomes they support.
For example, a product page shouldn’t stop at announcing an AI-powered analytics capability. Explain what information it analyzes, how customers use the insights, and which business decisions it helps improve.
The same principle applies to press releases. An announcement should explain what has changed, why it matters, and who benefits. A customer case study should describe the challenge, the solution, and the measurable results whenever reliable figures are available.
This article provides further insight on the importance of writing with purpose: The Powerful Case for B2B Blogging in the AI Era.
This specificity serves human buyers who need evidence to make informed decisions. It also gives AI systems concrete information to draw upon when answering related questions. In AI search optimization, useful answers can be more valuable than generic claims about innovation, leadership, or transformation. Those claims rarely communicate what makes a company distinctive.
The takeaway: Anticipate your audience’s questions and answer them directly. Specific, useful content is more informative for people and easier for AI systems to interpret.
4. Support Claims with Evidence and Consistent Messaging
Trust has always been essential to B2B marketing. Buyers need confidence that a vendor understands their challenges and can deliver what it promises.
AI-driven discovery makes credibility even more important. When systems assemble answers from multiple sources, unsupported claims offer little meaningful context. Clear facts, credible evidence, and consistent explanations give your content a stronger foundation. Where possible, support your claims with customer outcomes, original research, expert commentary, product documentation, and relevant industry evidence. Explain the source and context of statistics rather than presenting impressive numbers without explanation.
Consistency matters, too. Your website, sales presentations, press releases, and executive commentary should tell a coherent story about your company. Differences in terminology or positioning can create confusion for buyers and complicate the interpretation of your content. And, with AI now reading everything we publish, any inconsistencies will be noticed – trust me on this one!
This doesn’t mean every asset must repeat the same wording. A sales deck should speak to a buyer’s business priorities, while a press release should communicate news and its significance. Both should reflect the same underlying positioning and facts. For marketers, this is an opportunity to connect content development with product marketing, analyst relations, public relations, and sales enablement. A consistent narrative reinforces what makes your company relevant and credible.
The takeaway: Make your claims specific, substantiate them with evidence, and maintain consistent positioning across channels. Credibility strengthens both human confidence and the usefulness of your content to AI systems.
5. Make Your Content Accessible to Machines Without Sacrificing the Human Experience
The conversation about AI search optimization extends beyond the words on a page. It also involves how information is organized, labeled, and made accessible to technology. Websites provide a useful example. Human visitors benefit from intuitive navigation, readable pages, and clear product information. AI systems and agents also benefit when content is accessible, logically organized, and supported by appropriate technical signals.
Structured data, such as relevant Schema.org markup, can help identify information about products, organizations, articles, and other entities. Descriptive page titles, meaningful links, and accessible text provide additional context. Technical implementation matters, but it isn’t a substitute for useful content. Nor does adding structured data guarantee that an AI system will select or cite a page. These measures simply make information easier to interpret when systems support and use them.
The same principle applies beyond websites. Product briefs should identify the product and its capabilities clearly. Press releases should distinguish announcements from background information. Sales collateral should explain the value proposition without relying entirely on graphics that obscure essential details.
Marketers should work with their web and technical teams to ensure important content can be accessed by the search and AI systems they want to reach. Access permissions, rendering, and crawler controls can affect discoverability.
The takeaway: Combine well-written content with sound technical foundations. Make information accessible and machine-interpretable while preserving a useful, engaging experience for human readers.
One Content Strategy, Two Parallel Audiences
So, are we writing for humans or AI?
The answer is both.
AI search optimization is changing how we think about content, but it doesn’t eliminate the fundamentals of effective communication. We still need to understand our audiences, articulate our value, answer important questions, and build credibility. What changes is the need to make our content work harder. It must communicate clearly to people while providing enough structure, context, and evidence for AI systems to interpret it accurately.
This isn’t an argument for creating separate websites or duplicating every marketing asset. In most cases, the better starting point is a single, well-designed content strategy that serves both audiences.
There will be technical considerations, particularly as AI agents become more capable of navigating websites and gathering information on behalf of buyers. We should pay attention to those developments without losing sight of the people making purchasing decisions. Ultimately, the goal isn’t to write content that pleases an algorithm. It’s to communicate our expertise, differentiate our companies, and help the right buyers understand why we matter.
When we get that right, we improve the experience for humans and give AI systems better information to work with.
Before you write your next website page, sales presentation, press release, or thought leadership article, ask yourself one question: Who is the audience?
Then ask a second: Have I made this content clear and useful for both the person reading it and the AI system interpreting it?
That’s how we can optimize for both without losing sight of what good marketing communication has always required.
