As an independent ad tech advisor, Ivan Guzenko provides professional advice to the CEO and C-level management of the company SmartyAds Inc.
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SEO is no longer only about dropping a well-placed keyword or evenly sprinkling key phrases throughout a text. Quality trumps quantity, with search engines like Google favoring content that showcases deep expertise, experience, authoritativeness and trustworthiness (EEAT).
But here’s the twist: Recent shifts in search dynamics, driven by large language models (LLMs), are rewriting the rules. Unlike traditional search, LLMs cut straight to the chase, skipping links and delivering direct answers—a perfect fit for the growing demand for instant information.
Mastering this shift isn’t just an upgrade—it’s the key to staying ahead and outpacing the competition in the race for relevance.
From Keywords To Conversations: Is ChatGPT A New Google Search?
For billions of people worldwide, Google has long been the main gateway to the internet, accounting for about 90% of the search market share. But the winds are shifting for the first time in two decades: LLMs are poised to disrupt the status quo in a way browsers never saw coming.
Instead of skimming through a sea of blue links, users are increasingly turning to apps like ChatGPT, Perplexity, Google’s Search Generative Experience (now AI Overviews) or Bing’s Copilot. These tools don’t just answer questions; they guide users to products and brands in a way that feels less like a search engine and more like chatting with an advisor.
For marketers, this creates a whole new stream of information to monitor, ensuring their brands not only show up in relevant queries but are also represented accurately in AI apps.
Technologies Change Habits: How SEO Is Evolving
Users already know the platform they want to use for answers—for example, YouTube accounts for three billion searches monthly.
Voice assistants, too, are carving out a space of their own—as of 2023, 62% of Americans use voice assistants when seeking information. This shift in how and where questions are asked is a siren call for marketers to rethink their current SEO strategies.
For example, in an age when a large part of the web’s content is AI-generated, keywords are losing their relevance.
The role of keywords and their placement in the text was once grounded in algorithms like TF*IDF and BM25. Today’s search engines have evolved—they genuinely grasp the substance of the text, discerning the questions it answers and those it doesn’t. As a result, traditional methods of keyword-stuffing have become, at best, obsolete.
The era of blindly chasing keywords is over. Success now hinges on crafting content that resonates with user intent, offering meaningful answers instead of drowning readers in keyword-laden fluff.
Evolving, Not Dying: How AI’s Takeover Transforms Search
ChatGPT is the undisputed heavyweight champion of the generative AI arena.
Following ChatGPT’s meteoric success, Google’s engineers faced an existential question: Could their dominance in search be slipping away? As more users turned to ChatGPT for quick queries instead of Google, the company responded with Gemini, an LLM designed to reclaim its edge in the evolving search landscape.
To strengthen Gemini’s capabilities, Google struck a $60 million deal with Reddit, gaining access to a treasure trove of user-generated responses to train its model. Later, at Google I/O, the company also unveiled a suite of AI-powered innovations aimed at redefining user experience in search, including:
• Complex Query Breakdowns: AI now tackles intricate questions almost as long as those people paste into ChatGPT or Gemini.
• Video-Powered Search: Users can search for information directly through video content, adding a new dimension to visual discovery.
Search is also transforming into an experience that’s intended to be faster, smarter and more contextually aware.
Befriending Generative AI: Can Marketers Really Do It?
As generative AI reshapes the search landscape, a pressing question arises: Can marketers steer its outputs?
These systems, fueled by vast and often opaque data sources, operate in an environment marketers can’t directly impact. From a data science perspective, influencing an AI’s “viewpoint” isn’t child’s play—it takes over 50% of the training data to hold an opinion to cause the model to reflect a desired viewpoint.
In theory, however, there’s a chance that LLM’s output can be influenced through a strategic alignment of measures like:
• Establishing your own content that corresponds to expertise, authoritativeness and trustworthiness (EAT) principles. This increases the likelihood that such content could be used as a source of LLM training data.
• Getting mentioned in qualified media. Generative AI relies on high-ranking and reputable sources to make content recommendations. Being featured by authoritative sources increases the probability that LLM will associate your brand with relevant attributes.
• Getting your brand into the knowledge graph. These graphs are AI’s go-to for fact-checking and refining answers, boosting your brand’s credibility in the AI-driven ecosystem.
• Optimizing your content for voice search. Focus on natural speech patterns, like questions and conversational language, and ensure your site addresses the common topics your audience might voice-search.
What’s Next
In the age of LLMs, keeping your business visible means plugging it into their ecosystems. Organic traffic isn’t dead yet—people are still finding businesses through search—but today’s AI-powered engines are getting smarter by the second. Will generative AI completely overtake keyword-based search?
Maybe not just yet. However, mastering generative AI optimization (GAIO)—which I’ll dive into more in a future article—is a must for everyone who wants to future-proof their brand.Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?