The $75 billion gamble: Is Google risking its empire for Gemini?

Google under pressure: How the AI ​​revolution threatens and transforms the search empire

This is a pivotal year for the Mountain View giant. Caught between a historic antitrust lawsuit demanding the sale of the Chrome browser and the aggressive expansion of AI challengers like ChatGPT and Perplexity, Google faces the biggest test in its corporate history.

For a long time, Google's search monopoly, with market shares of around 90 percent, was considered an unassailable license to print money. But the rules of the game changed fundamentally in 2025. While Google is pumping 75 billion dollars into a gigantic AI infrastructure and forcefully integrating the Gemini language model into every one of its products, the foundations of the classic web business are crumbling: The era of "zero-click search" has begun.

In this new reality, Google delivers answers directly instead of redirecting users to websites – a paradigm shift that not only threatens its own advertising business but also puts publishers and SEO experts worldwide in dire straits. At the same time, the company is fighting on the legal front against billions in fines from the EU and threats of a breakup by the US Department of Justice.

This analysis goes behind the scenes of the “Gemini Offensive,” illuminating the true power dynamics in the AI ​​war against OpenAI and explaining why Google’s strategy of absorbing rather than blocking change could succeed despite all the risks. Learn how the world’s most powerful advertising company is reinventing itself to avoid becoming the next Kodak.

Between technological dominance and regulatory attack – Google's risky strategy in the age of generative intelligence

Google's position as the undisputed ruler of global information search is crumbling. What was long considered invincible—an economic empire with an 89 to 90 percent market share in web search, processing over 14 billion queries daily and generating over 70 billion dollars in advertising revenue annually—is increasingly coming under massive pressure. The threat comes not only from traditional search engine alternatives, but from an entirely new breed of competitor: artificially intelligent assistants that are fundamentally challenging the search engine's business model.

This analysis examines how Google is operating during this transformative phase, what strategic decisions the company is making, and what economic consequences arise from this realignment. The reality is more complex and less existential than some tech pundits claim, but also more far-reaching in its implications than a superficial examination suggests.

The technological counter-offensive: Gemini as the central answer

Google's answer to the AI ​​revolution is called Gemini. This language model has not become a byproduct or a research showcase, but has evolved into the strategic centerpiece of the entire company. In January 2025, CEO Sundar Pichai announced that Gemini would become the company's absolute focus product by 2025 – with priority and resources it would not have to share with any other initiative.

The numbers behind this strategy are impressive. Google's Gemini application reached over 400 million monthly active users, while its integration with Search Generative Experience (SGE), which provides AI-generated summary answers in search results, boasts over 1.5 billion monthly users. The infrastructure is growing exponentially: Google processed 480 trillion tokens in a single month—roughly a fifty-fold increase compared to the previous year. Seven million developers are already using the Gemini API.

Gemini 3, the latest language model, positions itself as a technical leader in complex tasks. It processes up to one million tokens of context—roughly ten times more than leading competitor models—and demonstrates superior capabilities in agent-like activities that require longer thought processes and planning. This is strategically significant because it enables Google not only to answer historical questions but also to independently solve multi-step tasks—from summarizing complex research to managing appointments and communications.
This Gemini push is explicitly designed as an attempt to close the existing market gap with OpenAI's ChatGPT. ChatGPT dominates the generative AI chatbot market with approximately 60 percent market share. But Gemini has closed the gap: While Gemini held 5.4 percent of the AI ​​market about a year ago, its current share is 18.2 percent—a tripling in less than twelve months. This is the result of aggressive integration across the entire Google ecosystem. Gemini is not a separate product that users have to actively seek out, but is already embedded in Gmail, Google Docs, Google Slides, Google Search and even Chrome.

The core problem: The search engine business model is up for debate

To understand the existential dimension of this transformation, one must understand how Google's business model works. Google is not a search engine that makes money with search technology. Google is an advertising company that operates a search engine to lure users to a platform where the company sells personalized advertising.

In the fourth quarter of 2024, Google generated $72.46 billion in advertising revenue – roughly 10.6 percent growth year-over-year. Of this, $54.03 billion came from Google Search & Ads alone. YouTube Advertising contributed another $10.47 billion. For its parent company, Alphabet, this means that approximately 75 percent of all group revenue comes from Google's traditional advertising business.
This model operates on a simple yet powerful principle: A user submits a search query, Google displays search results with ads, the user clicks on a search result or an ad, and Google earns fees through cost-per-click or cost-per-impression. The value of the space directly next to a search result is astronomical – one of the most valuable spots in the digital economy – because the user has explicitly expressed a purchase intent or need for information. This contextualization enables advertisers to place highly relevant ads.

AI-based answer engines like Perplexity AI or ChatGPT fundamentally threaten this model. If a user asks ChatGPT, "How do I fix a dripping faucet?", they receive a detailed, well-structured answer from the AI ​​– directly and without the detour of website links. For Google, this is a catastrophic scenario because: First, the user is distracted from Google's search page. Second, there are no traditional ad placements in an AI-generated answer (yet). Third, the website traffic doesn't reach the publishers who create content for Google.

The threat from new competitors: Real, but not existential

The competitive landscape needs to be analyzed precisely to distinguish between hype and reality. Perplexity AI, the company most often described in the tech media as a “Google killer,” currently holds a market share of less than 1 percent in web search. The company has been valued at $14 billion—a substantial sum, but also many times less than Google’s own market capitalization of approximately $2 trillion. DuckDuckGo CEO Gabriel Weinberg recently stated that Chrome alone would be worth at least $50 billion should Google be forced to sell the browser. This highlights the enormous barriers to entry.
Indeed, despite its 800 million weekly users (as of July 2025), ChatGPT’s impact on search substitution is limited. Google processed approximately 5 trillion search queries in 2024—roughly 14 billion daily. ChatGPT handles an estimated 37.5 million search-like queries daily, giving Google a lead of approximately 373 times. However, this too needs to be viewed in a nuanced way: While Google grew by 21.64 percent, ChatGPT showed a doubling of its user base within a few months – this is a different growth dynamic and signals structural changes in search behavior, not immediate market share substitution.

In these market scenarios, Google is being challenged by several new competitors. OpenAI is developing SearchGPT as a search engine alternative. Apple plans to integrate its own AI-based web search into its ecosystems. You.com and other specialized AI search engines are attempting to penetrate niche markets. However, Google's absolute dominance remains: forecasts indicate that by 2028, Google will retain approximately 86 percent of the search market, while all AI tools combined will grow to around 14 percent.

The regulatory offensive: Antitrust law as an economic weapon

While Google responds with technological innovation, the company faces regulatory pressure from two sides. In September 2025, the European Commission fined Google €2.95 billion for abusing its market position in online advertising technology. The ruling focuses on Google's control over three components of the digital advertising market: Google is simultaneously the largest operator of advertising platforms for publishers (AdSense), the largest operator of ad exchanges for advertisers and clients (Google Ad Manager), and a major user of these systems for its own services.

This creates fundamental conflicts of interest. Google can favor its own ads, access information from competitors, and set prices in ways that disadvantage others. The Commission interprets this as an abuse of market power. Furthermore, the US government, under the direction of the Department of Justice, is conducting a parallel antitrust investigation. In August 2024, a federal court found Google guilty of securing a monopoly through exclusive agreements with device manufacturers and browsers and of hindering competition by controlling the advertising market.

The remedies from these legal proceedings could be substantial. Some scenarios discuss the forced spin-off or sale of Chrome—Google's web browser, which holds approximately 65 percent of the market share and is essential for Google Search's default settings. Such a divestment would deprive Google of one of its most valuable distribution assets. If Apple integrates Perplexity AI into its ecosystems and leverages this integration preference, it could quickly propel Perplexity to significant market share.

B2B support and SaaS for SEO and GEO (AI search) combined: The all-in-one solution for B2B companies - Image: Xpert.Digital

AI search changes everything: How this SaaS solution is revolutionizing your B2B rankings forever.

The digital landscape for B2B companies is undergoing rapid change. Driven by artificial intelligence, the rules of online visibility are being rewritten. It has always been a challenge for companies to not only be visible in the digital masses, but also to be relevant to the right decision-makers. Traditional SEO strategies and local presence management (geomarketing) are complex, time-consuming, and often a battle against constantly changing algorithms and intense competition.

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SEO and content quality: The new battlefield

The integration of AI into Google Search is not only changing the user experience, but also fundamental business logic for publishers, agencies, and content creators. The so-called “AI Overviews”—AI-generated answer blocks at the top of the search results—have already led to a phenomenon that marketers call “zero-click searches”: For approximately 25 to 60 percent of queries, users receive their answer directly from Google without clicking on an external website.

This has massive implications for traditional search engine optimization. For a long time, SEO strategies operated on the principle that visibility in search results directly led to traffic. Today, visibility in an AI-generated overview might mean that your website is cited without generating relevant traffic. Previous ranking factors such as keyword density, systematic backlink building, and technical on-page optimization are becoming less important. Instead, other factors are becoming central:

Topical Authority replaces individual keywords. While SEO historically rebelled against optimizing for specific keywords, AI systems now evaluate a publisher's comprehensive expertise on an entire topic. A blog that publishes 50 superficial articles on various travel topics will achieve less visibility than a specialized publisher who writes 10 in-depth, interconnected articles on a travel destination that reference each other and provide coherent, structured knowledge.

EEAT (Experience, Expertise, Authority, Trustworthiness) is becoming the central evaluation metric. AI systems analyze whether an author is truly an expert in their field, whether the sources used are trustworthy, whether the information is current and accurate, and whether the author demonstrably possesses the authority of a voice. This privileges established media outlets, academic and scientific publishers, and industry leaders over pure content farms.

Content structure is becoming a strategic weapon. AI systems understand structured HTML hierarchy better than unstructured text. A page with clear headings (H1, H2, H3), concise answers in the first 100 words, and verifiable data sources is preferred, as this structure allows the AI ​​algorithm to parse content more quickly and extract relevant passages for AI answers.

Semantic relevance instead of keyword matching. Modern search algorithms use natural language processing to understand that "automobile," "car," and "vehicle" are not simply synonyms, but have different semantic contexts. A page that covers a topic holistically—including relevant subtopics, definitions, examples, and links—is rated as semantically denser.

The advertising transformation: AI as a monetization vehicle

While publishers suffer from zero-click searches, Google has developed a new monetization strategy: advertising directly within AI-generated answers. Google has experimented with “AI Mode” and “AI Max”—tools that allow advertisements to be embedded contextually within AI-generated search results.

For example, a user initiates a conversation-based query like, “I have a problem with my faucet – it’s dripping.” The AI ​​responds with a detailed explanation of the likely causes and possible solutions. Alongside this response, or directly integrated, a highly relevant ad for local plumbing services appears. This is incredibly valuable for advertisers: they place their message precisely where the user has explicitly expressed a need.

This fundamentally changes Google's role. The company is no longer just a gatekeeper of information, displaying links to content, but a content producer itself. Google generates content (via AI), controls this content, and monetizes it through advertising. This creates a new competitive dynamic: While publishers could previously expect high-quality content to lead to visibility and thus traffic, they now have to ask themselves whether their content will even be included in an AI-generated response or whether Google would prefer to generate its own content.

This strategy also works for Google's cloud business. Google Cloud recorded revenues of $11.96 billion in Q4 2024 – with year-over-year growth of approximately 30 percent. A large portion of this growth is driven by AI infrastructure, Vertex AI, and generative AI services. While OpenAI and other AI companies purchase external cloud infrastructure (often from Azure, AWS, or others), Google operates its own AI infrastructure internally – resulting in enormous cost savings and technology control.

The data crisis: Who trains the AI ​​models?

A critical bottleneck for all AI companies – including Google – is high-quality training material. Large language models are text-hungry; they need hundreds of billions or trillions of words from various sources to develop good generative capabilities.

This is creating a conflict between large content platforms and AI companies. Reddit, one of the largest collections of human conversations on the internet, sued Perplexity AI and three other data scraping companies in October 2025 for damages, claiming they were illegitimately scraping Reddit content and using it as training material. To substantiate its claims, Reddit staged a honeypot: The company created a test post that could only be crawled by Google's search engine and was otherwise inaccessible on the internet. Within a few hours, this exact content appeared in Perplexity search results—proof that Perplexity was indirectly stealing content via Google results.

This has deeper implications. Cloudflare documented similar practices by Perplexity – manipulating user agents, circumventing safeguards, and masking IP addresses. Ben Lee, Chief Legal Officer at Reddit, characterizes the situation as an “industrial-scale data laundering economy,” in which AI companies have built an illegal infrastructure in an arms race for high-quality human content.

For Google, this situation is ambivalent. Google has already entered into licensing agreements with Reddit, OpenAI, and other content platforms, paying for this data. This entails significant costs, but also legal certainty. Perplexity and other recently founded AI startups are trying to avoid these licensing costs by scraping content—a strategy that is ethically questionable and legally risky.

The investment arms race: $75 billion for AI infrastructure

The scale of Google's AI investments underscores the seriousness of its strategy. Pichai announced that Alphabet will invest approximately $75 billion in AI infrastructure, data centers, and AI research by 2025. This is an enormous sum—larger than the annual budget of many nation-states. Considered in the context of Google's overall capital expenditures (roughly 43 percent higher than the previous year), it becomes clear that this is not an incremental investment, but rather a strategic reallocation.

These investments aim to achieve several goals: First, to build the infrastructure to process 480 trillion tokens monthly and to expand this capacity. Second, to enable new research in areas such as agent-based AI (Gemini Agents) that can autonomously perform tasks. Third, to reduce the latency and cost of AI inference—that is, to run AI models faster and cheaper, thus opening up greater scaling opportunities.

The future strategy: Diversification vs. Dependence

Despite all of Google's efforts to diversify its business – cloud services, hardware (Pixel phones, Nest devices, Pixel tablets), software subscriptions – Google remains fundamentally dependent on its traditional advertising business. With $72.46 billion in advertising revenue per quarter and net profits in the tens or even hundreds of billions (Alphabet reported $23.6 billion in net profit in Q2 2024), Google has little incentive to embark on rapid experiments that could threaten this core business.

At the same time, old business models can become obsolete faster than established companies can react. The analogy to the photography industry is instructive: Kodak invented digital photography but didn't aggressively exploit this innovation because margins were higher in the film business. Today, Kodak's photography business practically no longer exists.

Google is walking a tightrope. The company is aggressively integrating AI into its own search – creating zero-click searches and potentially reduced user engagement on website links. It's monetizing AI responses through advertising – valuable for advertisers but detrimental to publishers. It's building massive infrastructure – requiring enormous cost flexibility.

One of the most important findings is that Google is not trying to block or ignore AI search. On the contrary, Google has accepted the market shift and is attempting to control it: through its own AI models, integrations into its platform, and monetization mechanisms that protect and expand its existing advertising business. This is a classic strategy of market power: not to ignore what is coming, but to absorb and control it.

Whether this strategy will be successful in the long term will become clear over the next three to five years. The technology industry has often demonstrated that market leaders can be displaced faster than their balance sheets and market shares would suggest. At the same time, Google has repeatedly proven its ability to absorb and neutralize massive threats—from the emergence of Facebook to the mobile app store market and OpenAI ChatGPT. The central thesis of this analysis is that Google remains dominant because it has the capacity to absorb disruption. But this dominance is no longer automatic—it is maintained through constant technological and strategic effort.

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