592000 The Brand Visibility Mandate: Why SEO Must Evolve for the AI Discovery Era

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The Brand Visibility Mandate: Why SEO Must Evolve for the AI Discovery Era

January 27, 2026
The Brand Visibility Mandate: Why SEO Must Evolve for the AI Discovery Era
The rules of digital visibility are changing fast. As generative AI engines increasingly shape how people discover, evaluate, and choose brands, traditional SEO metrics alone no longer tell the full story. Rankings still matter, but they are no longer the only gateway to visibility.
We believe that’s the core message of a recent IDC Market Note, The Brand Visibility Mandate: Semrush’s AI GEO Vision and IDC’s Enterprise Perspective (doc # US53968225, December 2025), which examines how Semrush is repositioning SEO for an era where large language models (LLMs) act as a new layer of discovery and decision-making.

From SEO to Brand Visibility Strategy

According to the IDC Market Note, “Traditional SEO continues to influence a large proportion of AI-generated answers, where web citations feed LLM outputs. AI engines now act as a second algorithmic gatekeeper, shaping brand perception before customers arrive on owned channels.”
In this environment, SEO and marketing teams are evolving into brand visibility strategists. The team now extends beyond rankings and clicks to include how brands are cited, mentioned, and interpreted across AI-generated answers. As highlighted at Semrush Spotlight 2025, this shift requires new measurement models that capture visibility across both SERPs and LLM interfaces.

The Attribution Gap: When AI Uses Your Content but Ignores Your Brand

One of the most striking insights in the Market Note comes from Semrush data presented by Marcus Tober, SVP of Enterprise Solutions. In many industries, more than 90% of pages cited by generative engines fail to deliver meaningful brand attribution or traffic back to the source.
Generative engines frequently rely on content for answers while omitting brand mentions altogether, making visibility harder to earn and even harder to measure.
The report noted, “In his ‘Cracking the Code of LLMs’ session, Marcus Tober, Semrush’s SVP of Enterprise Solutions, presented Semrush data showing a widening gap between the content used to source answers and brands actually mentioned or credited in generative engine results. In many verticals, the data showed that more than 90% of pages cited by ChatGPT and Perplexity fail to drive brand attribution or traffic.”
“To address this, Tober encourages brands to:
  • Rebuild topical authority on their own domains, using LLM-friendly content that is neutral, comparative, and structured.
  • Strengthen signals on external high-trust domains (e.g., Reddit, review platforms, and certification sources) that AI engines disproportionately rely on.
  • Refresh content frequently, to reflect LLM recency bias and improve citation likelihood.”
These tactics reflect a shift from optimizing for clicks to optimizing for citations and trust.

GEO Goes Far Beyond Marketing

According to the IDC report, “Semrush’s view of generative answer-engine optimization provides an important tactical foundation for practitioners, complementing IDC’s perspective of GEO as an enterprise capability, where SEO is a core capability. Achieving durable visibility in AI ecosystems requires:
  • Unified content operations that bridge marketing, product, and CX teams
  • Modernized content and data architecture across CMS, DAM, PIM, and DXP systems
  • Consistent metadata, provenance, and trust signals that can be interpreted by search crawlers and generative engines
  • Executive sponsorship, given the cross-functional dependencies and brand-risk implications”
In other words, GEO is not just an SEO problem, it’s an organizational problem that requires attention from customer-facing and infrastructure teams, plus leadership. Without cross-functional alignment, even strong SEO performance can fail to translate into visibility in AI-generated answers, leaving brands present in search but absent in the systems shaping modern discovery. 

Why LLM Friendly Content Still Needs to Be Human

Generative engines are shifting their focus: they will increasingly reward 'trust-rich' content rather than content that is simply easy to parse. This pivot is critical given IDC’s report warning that “rising AI-generated content homogeneity — where outputs are high quality but increasingly undifferentiated — will significantly erode brand differentiation by 2027.”
To combat this erosion, brands must demonstrate real, human expertise. Because AI engines now scan for signals of credibility, rather than anonymous or generic inputs, content must clearly attribute authorship and sourcing. This signals to both users and algorithms that the information is trustworthy and citable. Ultimately, even when AI aids in creation, humans must retain control over review and governance to ensure the accuracy and originality required to protect the brand.

Visibility Doesn’t Stop at Discovery

Finally, the report notes, “Semrush defines digital brand visibility primarily around search and LLM presence, which aligns well with IDC’s broader perspective that brand visibility spans three major phases of customer engagement:
  • Discovery visibility: Brand presence across SERPs, AI answers, social surfaces, marketplaces, and third-party ecosystems
  • Engagement visibility: The consistency and quality of digitally engaging customers across owned channels and devices
  • Visibility for value consumption: The extent to which customers transact with, use, and derive value from a brand’s digital products and services — particularly as AI agents increasingly mediate purchases, service interactions, and post-sale engagement”
The IDC report noted, “IDC research predicts that by 2029, over a third of digital transactions will be AI-mediated, making visibility within all three of these phases critical to long-term competitiveness.” From Semrush’s perspective, this model highlights an important shift: visibility is no longer a single moment or channel, but a fluid experience that compounds over time. Brands that focus only on discovery risk losing control of how they are understood, experienced, and ultimately selected as AI systems take on more decision making responsibility. Leaders must think about visibility as an end-to-end capability.

How Semrush is Leading in the AI Visibility Era

According to the report, “IDC believes Semrush can increase its strategic relevance to enterprise buyers by continuing to extend Semrush’s AIO tool beyond practitioner tooling into a platform that informs broader visibility, content, and search decisions across the organization.” Semrush combines mature products, proven expertise in search, and a scalable data foundation that unifies search, clickstream, backlink, and prompt-level data to deliver a holistic view of digital visibility.
At the center of this shift for enterprise organizations is Semrush AIO. Built for large, complex environments, it helps organizations understand and manage visibility across both traditional search and AI-driven discovery side by side and at scale.  Rather than treating AI visibility as a parallel or experimental channel, Semrush AIO brings AI SEO and SEO together within a single analytical framework. Teams can directly compare how brands, content, and competitors perform in classic SERPs versus AI-generated answers, revealing where visibility compounds, where it diverges, and where action is needed.
Moving beyond rankings and traffic, Semrush AIO makes AI visibility quantifiable and actionable for enterprise teams through AI visibility scoring, citation mapping, and source benchmarking, paired with powerful forecasting capabilities. This framework then guides teams from insight to action through recommendations on content improvement that aligns with how both search engines and AI systems surface, evaluate, and reward information. Together, these signals help organizations understand how AI-driven visibility evolves over time and model how AI-driven visibility is likely to evolve over time, connecting it to measurable business impact.
And for SMB and mid-market teams, there’s a complementary offering: Semrush One. It offers the same benefit of SEO and AI search visibility in a unified place.
Semrush’s tools provide a strong foundation for this future by helping organizations understand how AI engines interpret their digital footprint today and where they need to act to remain visible tomorrow.
Learn more about Semrush AI Optimization for enterprise and Semrush One built for the SMB. 

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