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AI’s SEO Revolution: 9 Experts on the Future of Search

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▼ Summary

AI is pushing SEO professionals to expand their roles, rethink strategies, and prepare for uncertainty in the industry.
– SEOs risk falling behind as enterprise organizations invest in AI transformation, yet the community underestimates its impact.
– AI demands a broader, cross-functional approach, requiring SEOs to become AI visibility leaders and avoid working in silos.
– SEOs lack visibility into AI search usage, with no equivalent of an “AI search console,” making attribution and measurement challenging.
– The industry must not lose sight of real consumer behavior and demographics amid AI hype, reinforcing the need for traditional marketing insights.

The search engine optimization landscape is undergoing a seismic shift, driven by the rapid integration of artificial intelligence into how users find information online. At a recent roundtable in Miami, nine leading SEO professionals gathered to discuss what this transformation means for the future of their field. Their conversation revealed a clear consensus: AI is pushing SEOs to expand their roles, rethink strategies, and brace for uncertainty.

A significant concern raised was that many in the SEO community risk falling behind the pace of real-world change. Mike King of iPullRank emphasized that enterprise organizations are already investing heavily in AI-driven strategies, while some SEO professionals continue to underestimate the scale of disruption. He noted that while his firm is pioneering approaches like “Relevance Engineering,” challenges around attribution and projection modeling remain unresolved, leaving executives hungry for clearer answers.

Several experts stressed that AI demands a broader, more integrated approach to search visibility. Leigh McKenzie from Backlinko argued that this is the moment for SEOs to reposition themselves as AI visibility leaders, working across departments rather than in isolation. Jennifer Cornwell of Tinuiti echoed this, emphasizing that siloed SEO teams can no longer thrive, cross-functional collaboration is essential for building comprehensive brand strategies that support SEO efforts on emerging platforms. Matthew Kay put it bluntly: professionals must evolve into complete marketers or risk becoming irrelevant.

A major point of frustration highlighted during the discussion is the current lack of visibility into how people interact with AI search tools. Devesh Khanal of Grow and Convert pointed out that without an “AI search console” equivalent, professionals are largely in the dark about the detailed, conversational queries users are making. This gap makes it difficult to optimize effectively. Ryan Jones of SERPrecon advised flexibility over panic, noting that the entire industry is adapting together and that no one has all the answers yet.

Attribution and influence are tougher than ever in this new environment, according to Nick Eubanks of Semrush. He explained that off-site channels like brand, product, and PR have always been critical but were never fully within an SEO’s control, now, with AI in the mix, measuring impact has become even more complex. Matthew Melinger of SEO Gets added that part of the SEO’s evolving role is to act as a “marketing therapist,” helping executives navigate uncertainty and anxiety.

Amid the excitement around AI, Gaetano DiNardi of Marketing Advice reminded the group not to lose sight of real consumer behavior. He highlighted that user demographics are broadening, with women now using AI tools like ChatGPT just as frequently as men for shopping and spending, a reminder that traditional product marketing principles remain vitally important.

Ultimately, the roundtable concluded that AI is accelerating SEO’s transformation, pushing the discipline beyond technical optimization and into a more strategic, integrated, and consumer-focused future.

(Source: Search Engine Land)

Topics

ai seo 95% role expansion 90% industry adaptation 88% strategy rethinking 88% industry transformation 87% visibility leadership 85% professional evolution 85% cross-functional approach 83% data visibility 82% attribution challenges 80%

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