As I delve into the world of AI-driven search, it’s clear that advice around AI is becoming way too simple. What really sets you apart are knowledge graphs, expert entities, and how you influence trusted datasets.
Recently, I came across a Harvard Business Review article that resonates with the shifts we’re noticing in SEO. AI Overviews and Google’s AI-enhanced search features are not only creating what’s known as a zero-click environment but they’re also redefining user journeys and behaviors.
User journeys that were once multi-touch are now compressed into a single, synthesized answer. The metaphor of the “Search” monolith crumbling visually captures this transformation.
In this dramatic shift, brands like mine lose many traditional touchpoints, requiring a change in marketing strategy. HBR brilliantly highlights how algorithms are reshaping first impressions. However, while pointing in the right direction, the article’s tactical advice feels too generic and superficial.
Much of the advice sounds strategic yet lacks deep operational insight. This gap is crucial for sustainable visibility and long-term success.
The challenge is deeper than what appears as simple advice to navigate at an executive level. Real structural change is essential to adapt to the evolving search landscape.
The Problem with Flock Tactics
The HBR article brings forward schema, authorship signals, and branded concepts but these suggestions risk becoming “flock tactics.” They spread because they’re easy to grasp, yet they lose their edge once widely adopted.
Schema
Schema is highly debated in LLM and AI optimization. Although Microsoft Bing uses schema for its LLMs, Google’s models have a more complex relationship with third-party LLMs.
Incorporating schema in AI and SEO activities is useful, but presenting it as a fundamental tactic neglects its diminishing returns when everyone implements it.
Another oversight is the importance of external knowledge systems such as Wikidata. LLMs often rely on these authorities more than on any single website.
There’s a significant gap in understanding how models process structured versus unstructured data signals.
E-E-A-T — Shallow Authorship Signals
Using real experts’ credentials aligns with E-E-A-T but often becomes superficial, focusing on bios and headshots without actually strengthening expertise.
There’s a profound difference between mere display of bios and nurturing an expert entity recognized in academia or industry.
Only genuine expertise creates the signals that AI models trust.
Vanity Concepts
Creating branded concepts like “The Acme Index” sounds appealing but is difficult to successfully execute. External adoption is key for them to gain traction.
These concepts must be embraced by reputable sources, which is a hurdle many brands fail to overcome.
The Structural Blind Spots
Beyond tactics, there are deeper structural issues in perceiving AI solely as an external shift rather than an opportunity to innovate internally.
Internalizing AI Infrastructure
The potential to integrate AI deeply into operations, through AI assistants or domain-specific agents, is often overlooked.
In controlled environments, fundamentals like site architecture and data structures remain crucial for success, even if they need to be reimagined for AI.
It’s Not Just SEO
SEO as a ranking problem is an incomplete perspective. It’s moving towards entity-level knowledge management.
Visibility now hinges on solid entity definitions and connections to external data sources.
Effective SEO requires understanding these complex relationships.
LLM Model Heterogeneity
Different AI systems use unique datasets and processes, implying a single strategy may not work for all AI platforms.
Essential is an awareness of these risks to prevent reputational damage due to missteps in optimization strategies.
Surface-Level Tactics Won’t Build AI Visibility
HBR article usefully outlines how marketing is changing with AI, emphasizing that traditional SEO is no longer sufficient.
Practical advice is thinner, filled with tactics quickly replicated by others.
The challenge lies in doing the harder, unglamorous work that leads to real, long-term visibility.
Inspired by this post on Search Engine Land.
