The digital landscape is undergoing a significant transformation, with generative AI engines increasingly influencing how consumers discover and evaluate brands. This shift necessitates a reevaluation of traditional search engine optimization (SEO) strategies, moving beyond rankings and clicks to focus on a broader concept of “Brand Visibility Mandate.”
A recent IDC Market Note, “The Brand Visibility Mandate: Semrush’s AI GEO Vision and IDC’s Enterprise Perspective,” highlights this evolution. The report, published in December 2025, examines how Semrush is adapting SEO for an era where large language models (LLMs) act as a new layer of discovery and decision-making. AI engines now serve as a secondary algorithmic gatekeeper, shaping brand perception before users reach a company’s owned channels.
The Attribution Gap in AI-Generated Answers
One critical insight from the report, presented by Marcus Tober, SVP of Enterprise Solutions at Semrush, reveals a significant attribution gap. Semrush data indicates that in many industries, over 90% of pages cited by generative engines fail to provide meaningful brand attribution or drive traffic back to the original source. This means that while AI may use content to formulate answers, it often omits brand mentions, making visibility harder to achieve and measure.
Tober suggests strategies to combat this issue, including rebuilding topical authority on brand domains with LLM-friendly content that is neutral, comparative, and structured. Strengthening signals on high-trust external domains like Reddit and review platforms is also recommended, as AI engines disproportionately rely on these sources. Furthermore, refreshing content frequently is crucial to address LLM recency bias and improve citation likelihood.
GEO as an Enterprise Capability
The IDC report frames Generative Engine Optimization (GEO) as an enterprise capability, with SEO as a core component. Achieving lasting visibility in AI ecosystems requires unified content operations that integrate marketing, product, and customer experience teams. Modernized content and data architecture across content management systems (CMS), digital asset management (DAM), product information management (PIM), and digital experience platforms (DXP) are essential. Consistent metadata, provenance, and trust signals that both search crawlers and generative engines can interpret are also vital. This cross-functional approach requires executive sponsorship due to its implications for brand risk.
Without this organizational alignment, strong SEO performance may not translate into visibility within AI-generated answers, leaving brands present in search but absent in the systems shaping modern discovery. This is particularly concerning as IDC research predicts that by 2029, over a third of digital transactions will be AI-mediated, making visibility across all phases of customer engagement critical for long-term competitiveness.
LLM-Friendly Content Needs Human Oversight
Generative engines are increasingly prioritizing “trust-rich” content over content that is merely easy to parse. IDC warns that by 2027, rising AI-generated content homogeneity could significantly erode brand differentiation. To counter this, brands must demonstrate genuine human expertise. AI engines now scan for credibility signals, making it imperative for content to clearly attribute authorship and sourcing. This signals trustworthiness to both users and algorithms.
Semrush defines digital brand visibility as encompassing search and LLM presence. This aligns with IDC’s broader perspective that brand visibility spans three phases: discovery, engagement, and value consumption. As AI agents increasingly mediate purchases and service interactions, visibility in all these phases becomes crucial for sustained competitiveness. Brands focusing solely on discovery risk losing control over how they are understood and selected by consumers.
Semrush AIO is designed to help organizations manage visibility across traditional search and AI-driven discovery. It allows teams to compare brand performance in classic search engine results pages (SERPs) versus AI-generated answers, identifying areas where visibility compounds, diverges, or requires action. The tool offers AI visibility scoring, citation mapping, and benchmarking, providing actionable recommendations for content improvement.
For small and medium-sized businesses, Semrush One offers similar benefits by unifying SEO and AI search visibility. Semrush’s tools provide a foundation for navigating this new era, helping organizations understand how AI engines interpret their digital footprint and where they need to act to maintain visibility.
