As AI-powered search experiences become more common across search engines and conversational platforms, brands are rethinking how they approach visibility. Traditional rankings still matter, but generative search results increasingly rely on authority, relevance, context, and structured information when selecting sources. Businesses investing in AI SEO services are focusing on strategies that help content surface within AI-generated answers while maintaining strong organic performance. To understand what is working in 2026, we asked search and AI marketing leaders to share the approaches they recommend.
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Matt Bowman, Founder, Thrive Internet Marketing Agency
“Generative search rewards content that answers questions completely. The goal is no longer ranking for a keyword alone—it is becoming the source AI systems trust when building responses.”
According to Matt Bowman of ThriveAgency.com, businesses should focus on creating comprehensive resources that address user intent from multiple angles. AI systems often prioritize content that provides complete, contextual answers rather than isolated information.
Organizations can implement this strategy by developing detailed topic hubs, FAQs, and supporting resources. For example, a software company may create content covering implementation, pricing, integrations, troubleshooting, and industry use cases within a connected content ecosystem. This increases the likelihood of appearing in AI-generated summaries and recommendations.
Michael King, Founder & CEO, iPullRank
“Search is becoming entity-driven. Brands that clearly establish expertise and topical relevance are more likely to appear in AI-generated experiences.”
Generative search systems rely heavily on understanding relationships between entities, topics, and sources. Brands that demonstrate authority consistently across related subjects often gain stronger visibility.
Businesses can strengthen entity recognition by publishing expert-driven content, maintaining consistent branding, and building topical depth. A cybersecurity company, for instance, can improve visibility by covering interconnected topics such as compliance, threat prevention, risk management, and incident response.
Lily Ray, VP of SEO Strategy & Research, Amsive
“Trust signals are becoming increasingly important because AI systems often prioritize sources that demonstrate expertise, experience, authority, and credibility.”
As AI-generated results become more influential, demonstrating expertise matters more than ever. Content supported by real experts, verifiable credentials, and trustworthy information often performs better.
Organizations should highlight author expertise, include expert commentary, and showcase credentials throughout their websites. A healthcare provider publishing content reviewed by licensed professionals may strengthen both user trust and AI search visibility.
Kevin Indig, Growth Advisor, Hypergrowth Partners
“Brands need to understand that AI visibility is often earned through topic ownership rather than individual rankings.”
Traditional SEO service frequently emphasizes keyword performance. AI search experiences, however, often evaluate broader authority signals across entire subjects.
Companies can improve visibility by creating content clusters that address related themes comprehensively. An eCommerce brand specializing in outdoor equipment, for example, may develop extensive resources covering camping, hiking, gear maintenance, safety, and trip planning. Comprehensive topic coverage strengthens relevance and authority.
Tom Capper, Senior Search Scientist, Moz
“Question-based content is becoming more valuable because AI systems frequently surface answers that align directly with user queries.”
Many AI-driven search experiences are designed around answering questions rather than presenting lists of links. Businesses that structure content around common customer questions often gain advantages.
Organizations should identify recurring questions from sales conversations, support interactions, and keyword research. A financial services company creating detailed responses to retirement planning questions may increase opportunities to appear in AI-generated answers.
Areej AbuAli, Founder, Women in Tech SEO
“Technical SEO remains essential because AI systems still rely on websites being accessible, understandable, and properly structured.”
Content quality alone is not enough. Technical foundations help search systems interpret information accurately and efficiently.
Businesses should prioritize schema markup, crawlability, page speed, and site architecture. For example, a professional services firm implementing structured data across service pages may improve content discoverability within both traditional and AI-driven search environments.
Dixon Jones, CEO, InLinks
“Internal linking is becoming increasingly important because it helps search systems understand relationships between topics and content assets.”
Many organizations overlook internal linking even though it plays a significant role in establishing topical authority. Strong internal connections help search engines interpret website structures more effectively.
Companies can build logical content pathways connecting resources, service pages, and educational content. A manufacturing company linking related guides and technical resources together may strengthen authority signals while improving user experiences.
Jes Scholz, International Digital Growth Consultant
“AI search visibility often comes from creating information that is genuinely useful rather than simply optimized.”
Many businesses still approach SEO from a ranking-first perspective. However, AI systems increasingly evaluate usefulness and context alongside traditional relevance signals.
Organizations should focus on creating original insights, practical examples, and expert-driven perspectives. A logistics company sharing unique operational data and industry observations may differentiate itself from competitors relying on generic content.
Ryan Jones, VP of SEO, Razorfish
“Measurement needs to evolve. Visibility within AI-generated experiences may become just as important as traditional rankings.”
As AI search adoption grows, marketers must develop new methods for evaluating performance. Traditional ranking reports provide valuable information but may not capture the full picture.
Businesses should monitor branded search growth, referral traffic patterns, engagement metrics, and visibility across AI-driven platforms. Understanding these trends helps guide future optimization efforts.
Sam Torres, SEO Director, Gray Dot Company
“The brands winning in AI search are often the ones creating the most useful customer journeys, not just the most optimized pages.”
Generative search experiences frequently connect users to resources throughout the buying process. Businesses that support customer needs at every stage often gain stronger visibility.
Organizations can develop content supporting awareness, evaluation, implementation, and retention. A SaaS company offering educational resources, onboarding guidance, and advanced tutorials may improve both customer experiences and AI search performance.
Frequently Asked Questions
What are AI SEO services?
AI SEO services focus on improving visibility within AI-powered search experiences while maintaining strong traditional search performance.
How is AI search different from traditional search?
AI search often generates direct answers using information from multiple sources rather than relying solely on ranked search results.
Does traditional SEO still matter in 2026?
Yes. Technical SEO, content quality, authority, and user experience remain important foundations for visibility.
Why is topical authority important for AI search?
AI systems often prioritize sources that demonstrate comprehensive expertise across an entire subject area.
How can businesses improve visibility in generative search results?
Creating authoritative content, strengthening trust signals, improving technical SEO, and building comprehensive topic coverage can help improve visibility.
