The Browser Is the New Battleground, And It's Reshaping GSO Strategy
For the past two years, the conversation around generative search optimisation has focused almost entirely on model quality. Which LLM is most accurate? Which one hallucinates less? Which one cites the best sources?
Those are the wrong questions.
The real battle isn't being fought at the model level. It's being fought at the distribution layer. And the browser is where it's all going to be decided.
The Market Share Numbers Aren't What They Look Like
Gemini's Growth
Jan 2025 to early 2026 [1]
5.7% → 21%
ChatGPT's Decline
Over the same period [1]
87% → 64%
But look closer. Those numbers are misleading.
The Distribution Effect
Gemini's surge is primarily due to Google embedding AI Mode directly into Search, a product used by billions. Interactions with AI overviews in Search are counted as Gemini sessions, often without users consciously choosing it over alternatives.
Where Deliberate Preference Sits
True adoption is better reflected in deliberate, intentional usage and enterprise deployments. Despite only 2% consumer traffic, Claude is reportedly winning in enterprise deployments, indicating where informed buyers are consciously making choices [2].
Why the Retrieval Layer Matters More Than the Model
Beyond the distribution story, there's a meaningful technical difference between how different LLMs retrieve and ground their responses. And it has direct implications for GSO strategy.
Gemini's Google Search Grounding
Gemini grounds its responses using Google Search. That sounds like an advantage — Google has the largest, most current web index in the world. And for time-sensitive queries, it helps.
But traditional ranking signals remain heavily weighted toward authority and optimisation patterns rather than direct semantic accuracy. Domain authority. Backlinks. On-page SEO. Freshness.
That means Gemini's grounding inherits all of Google's ranking biases. Well-optimised but shallow content can surface over deeper, more authoritative material. High-authority but outdated pages can outrank more accurate newer sources. For niche technical topics — exactly the content enterprise technology brands need to win on — the most SEO-savvy page isn't always the most accurate one.
Semantic Search Retrieval
Contrast this with retrieval systems built on semantic search. Exa (formerly Metaphor) surfaces content based on meaning and relevance rather than PageRank signals [3]. Models or tools that use semantic retrieval find the genuinely best answer to a query, not the best-ranked page for related keywords. It's one reason Perplexity's citations often feel more directly on-point than Gemini's.
The implication for GSO is significant. Optimising for Gemini and optimising for Google Search are largely the same task. But optimising for Perplexity, Claude, or ChatGPT requires a different emphasis — semantic clarity, citation-worthiness, and genuine authority over keyword density and link profile.
Google Search Is Hollowing Out From the Inside
While the browser wars play out at the distribution layer, something equally significant is happening within Google Search itself.
Total search volume is holding roughly steady. But the behaviour underneath that headline number has changed dramatically.
~20%
Drop in US Desktop Searches
Year over year in the US (Datos/SparkToro) [4]
38%
Decline in US Organic Referrals
From Google Search year on year [5]
Google search traffic to publisher websites globally was down by a third in the year to November 2025, according to Chartbeat data [5]. Users aren't abandoning Google — they're just searching less often. Because AI Overviews are resolving their questions before a second or third search becomes necessary.
This is Google cannibalising its own referral model to defend against external AI competition. By answering queries within the SERP, AI Overviews keep users inside Google's ecosystem. It's a rational defensive move. But it fundamentally breaks the implicit contract that has underpinned content marketing and SEO for two decades.
A brand can rank in position one, earn an AI Overview citation, and still see clicks collapse — because the answer was delivered without requiring a visit to the site. Visibility no longer reliably translates to traffic.
This is precisely why GSO has moved from a nice-to-have to a strategic necessity. The traffic model that most enterprise content strategies were built on is structurally broken. The question is no longer whether to adapt. It's how fast.