Editorial
The Gist
- SEO enters the generative era. As AI tools like ChatGPT and Gemini redefine search, visibility now depends on content that language models recognize as credible and structured.
- Questions replace keywords. Content strategies built around real customer questions perform better in AI-driven discovery than those relying on traditional keyword tactics.
- Authority and authenticity win. AI prioritizes content from identifiable experts, supported by real data, multimedia context, and human insight—signals that reinforce trust.
I’ve spent years watching SEO evolve. What began as a process of keyword stuffing has matured into a more strategic discipline focused on user intent, content quality and technical structure. Now, the introduction of generative AI is initiating another major shift that demands a deeper look at how digital content earns visibility.
AI-driven tools like ChatGPT, Google Gemini and Claude are changing how people find and engage with information. Users are arriving directly on deep-linked pages, such as individual product details, instead of starting from the home or navigation pages. While this disrupts the typical website flow, it also creates opportunity. As James McCormick of IDC observes, traffic today is increasingly intent-driven, with visitors arriving later in the decision process and often much closer to making a purchase or completing a conversion.
This shift is significant. Marketers are now challenged to meet the expectations of both traditional search engines and language models. It is no longer enough to appear in search results. Content must now be recognized by AI systems as a high-quality source worthy of citation.
In this piece, I’ll share best practices for generative engine optimization, including using plain HTML, featuring original expertise, structuring for readability and incorporating multimodal content.
Table of Contents
- The New Foundation: Questions Over Keywords
- Building Content AI Can Trust
- Creating Content That Performs in a Machine-Readable World
- Prioritize Question-Based Content
- Improve Structure and Clarity
- Feature Original Expertise and Supporting Data
- Measure New Awareness Signals
- Elevate Human Voices
- Incorporate Multimodal Content
- A Strategy Based on Value
- Video on AI Visibility Optimization: The Next Evolution of SEO
The New Foundation: Questions Over Keywords
Content strategy used to begin with keyword mapping. That approach is evolving. Today, a more effective method involves mapping the real questions customers are asking. AI tools rely on natural language inputs. They surface content that addresses those queries with clarity, relevance and completeness.
Keyword Mapping vs. Question Mapping
This table contrasts traditional SEO keyword strategies with the emerging question-based approach used in generative engine optimization.
| Aspect | Traditional Keyword Mapping | Question-Based Content Strategy |
|---|---|---|
| Focus | Targeting specific high-volume search terms to boost rankings. | Answering real customer questions to demonstrate relevance and expertise. |
| Search Intent | Often transactional or navigational, based on word matches. | Contextual and conversational, aligned with natural language queries. |
| Optimization Method | Relies on density, backlinks, and metadata alignment. | Uses clarity, completeness and semantic structure to satisfy AI interpretation. |
| Measurement of Success | Page ranking and traffic volume. | Visibility in AI summaries, user engagement and brand authority signals. |
| Primary Tools | Keyword research platforms like SEMrush, Ahrefs, Moz. | Conversational insight tools like ChatGPT, Perplexity and AnswerThePublic. |
| Content Tone | Optimized for search algorithms. | Optimized for human understanding and AI reasoning. |
Developing content around well-researched questions offers a more meaningful way to connect with prospective audiences. It shifts the focus from optimization techniques to a genuine understanding of the challenges, concerns and decisions users are facing.
Related Article: Survive the AI Takeover of Search — 5 Moves Every Brand Must Make
Building Content AI Can Trust
A growing misconception is that AI platforms can be gamed with auto-generated content. However, language models are already being trained to evaluate content more critically. Indicators such as tone, authority and specificity may carry increasing influence over time. These factors reflect the same principles that have long defined effective content marketing.
Thoughtful, in-depth content created by experienced professionals is more likely to stand out. For instance, a video of a product leader discussing implementation challenges or lessons learned is likely to carry more weight than anonymous copy repeating general information. Content that demonstrates real-world experience often performs better, not because of polish, but because of substance.
Creating Content That Performs in a Machine-Readable World
As AI systems continue to evolve, marketers can take practical steps to strengthen their visibility and authority. The following approaches provide a roadmap for building content that resonates with both human readers and language models:
Prioritize Question-Based Content
Audiences rarely type isolated keywords into AI tools. They ask questions such as “What is the best way to reduce compliance risk in financial services?” or “How do manufacturers streamline employee training?” Creating content that directly addresses these kinds of queries increases the likelihood of being surfaced in AI summaries. A bank could publish a detailed FAQ that answers client concerns about digital security. A healthcare provider might produce a blog series around common patient questions, supported with case studies. Framing content in this way makes it more conversational and more aligned with how people search today.
Related Article: Why AI-Optimized Websites Win Higher Conversion Rates
Improve Structure and Clarity
Clean, structured text gives AI systems the best chance to interpret your content. Many crawlers handle JavaScript poorly, so logical organization in plain HTML or markdown is ideal. Clear headings and consistent formatting make key information easy to extract. Metadata and semantics also play a critical role. Titles, descriptions, dates and schema.org markup signal context before the full text is analyzed.
Bulleted lists improve both readability and machine understanding. Generative engines rely on structure to identify key points, and lists provide clear visual and semantic cues. They break complex ideas into simple, scannable elements, helping AI summarize information more accurately while guiding human readers through the main takeaways.
Machine-Readable Content Optimization Checklist
This table provides a structured guide for optimizing content so it can be accurately parsed and ranked by AI systems and search crawlers.
| Optimization Area | Action Steps | Why It Matters |
|---|---|---|
| HTML Structure | Use clean, semantic HTML tags (H2, H3, UL, LI, etc.) instead of script-heavy layouts. | Ensures crawlers and AI models can interpret the logical hierarchy of your content. |
| Metadata | Include accurate titles, meta descriptions, publication dates, and schema.org markup. | Provides contextual cues that improve search and AI citation relevance. |
| Formatting Consistency | Maintain uniform heading sizes and list structures across all articles. | Improves machine parsing accuracy and reader comprehension. |
| Readable Lists | Use bullet points to highlight main takeaways or sequential actions. | Facilitates faster understanding for humans and clearer extraction for AI systems. |
| Multimodal Elements | Pair written content with labeled images, transcripts, and short clips. | Expands AI’s contextual data points and boosts visibility in visual search results. |
| Accessibility | Use descriptive alt text and captioned media. | Strengthens SEO while supporting inclusive design and compliance standards. |
Together, clean structure and strong metadata improve machine readability while reinforcing authority and trust with human audiences.
Feature Original Expertise and Supporting Data
Content tied to identifiable professionals or events signals authenticity. For example, a podcast where an insurance executive discusses emerging risk models, or a webinar featuring a CIO sharing digital transformation lessons, offers credibility that anonymous text cannot. These formats showcase lived experience and provide a depth of insight that LLMs are trained to recognize as authoritative.
Pairing expert insight with reliable data strengthens visibility. Referencing reputable studies or survey results gives algorithms verifiable context and helps readers trust the information. Statistics add depth and demonstrate that the content is grounded in evidence, not opinion. When expertise and data appear together, AI systems are more likely to surface the material as a trustworthy source, rewarding brands that combine authentic voices with measurable proof.
Measure New Awareness Signals
Traditional SEO metrics are no longer the only indicators of success. Marketers should begin tracking how often prospects mention discovering a brand through ChatGPT, Google Gemini or other AI tools. These anecdotes can provide an early sense of how content is being represented in AI-driven environments.
Elevate Human Voices
Highlighting subject matter experts strengthens both brand trust and discoverability. A manufacturer might film engineers walking through product innovations on video. A government agency could feature staff explaining policy updates in plain language. These authentic voices give audiences confidence while reinforcing to AI systems that the content originates from real expertise.
Related Article: Click End Game: What AI Search Means for SEO, CX and Brand Visibility
Incorporate Multimodal Content
AI-driven search is no longer limited to text. Platforms like Google are enabling multimodal queries, where someone can upload a photo, combine it with a written question and receive an enriched response. To support this kind of interaction, brands should pair their textual content with high-quality images, diagrams and videos.
A home improvement retailer, for instance, might provide step-by-step written instructions for installing a light fixture alongside annotated photos of each stage. These elements make the content more useful for human readers while also giving AI systems additional data points to interpret, index and present in search results.
A Strategy Based on Value
The age of AI search rewards clarity, credibility, and structure. Marketers who focus on those fundamentals will see their content rise in both traditional and generative search results. The key is to think less about feeding algorithms and more about building genuine authority.
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To stay visible and trusted in this new environment:
- Build content around real questions, not isolated keywords.
- Use clean HTML, clear headings and complete metadata so AI systems can interpret your content accurately.
- Use bulleted lists to improve readability and make information easier to parse.
- Feature original expertise and subject matter experts that demonstrate lived experience and professional credibility.
- Pair text with multimodal assets, such as images, diagrams and videos, that enrich both human understanding and machine interpretation.
- Track new visibility signals, including mentions in AI-generated summaries or conversations.
- Incorporate data to add depth and increase credibility.
AI search is reshaping discovery, but the path to visibility still runs through relevance, trust and quality. Marketers who create well-structured, expert-driven content will earn recognition not only from algorithms, but from the audiences those algorithms serve.
Video on AI Visibility Optimization: The Next Evolution of SEO
Editor’s note: This section draws on insights from CMSWire’s Digital Experience Show featuring Editor-in-Chief Dom Nicastro and Luis Fernandez, executive director at VML Enterprise Solutions. The discussion explores how AI-driven discovery is transforming search, visibility and marketing strategy—and what brands must do to stay relevant in a multi-engine world.
Here's what we at CMSWire took from this conversation, piling on the central thesis from the author of this piece.
In their conversation, Nicastro and Fernandez unpacked how the rise of generative search marks a seismic shift in how audiences find and trust content online. Traditional SEO, once the lifeblood of digital visibility, is being overtaken by AI Visibility Optimization (AIVO)—a strategy focused not on search rankings, but on being selected and cited by AI bots such as ChatGPT, Gemini and Claude. Fernandez argues that marketers must rethink visibility altogether, because AI systems now determine which sources—and voices—enter the conversation.
- AI-driven discovery replaces static rankings. Search results are no longer lists of blue links; instead, AI tools synthesize and summarize insights from multiple sources. Brands must ensure their content is structured and authoritative enough to be included in these syntheses.
- Multiple AI “gatekeepers” shape exposure. Unlike the Google-dominated era, marketers now face diverse ecosystems—each with unique algorithms, preferences, and biases. Visibility depends on understanding and adapting to these varying rules of engagement.
- AIVO emphasizes context over clicks. Fernandez notes that AI relevance isn’t measured by traffic or page views, but by whether bots consistently reference your expertise when forming answers. This means content quality and credibility outweigh traditional keyword metrics.
- Authenticity remains the differentiator. Both Nicastro and Fernandez stress that AI systems are increasingly trained to value real-world expertise, verifiable data and contextual authority—aligning perfectly with the principles of generative engine optimization discussed in this article.
This conversation reinforces the central thesis of this piece: visibility in the AI era requires more than keyword optimization—it demands content designed to earn trust, inclusion and relevance in machine reasoning. The next evolution of SEO isn’t about gaming algorithms, but about creating structured, human-centered, expert-led content that both audiences and AI systems recognize as valuable.
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