Google's 2025 AI Gambit: Gemini 3, the Traffic Apocalypse, and the Rush to Keep Up

Google shipped Gemini 3 to 2 billion users on day one. Publishers watching their traffic charts saw a 27% drop year-over-year. Andrej Karpathy—one of the world's top AI researchers—watched Google's latest model refuse to believe it was 2025. Then it apologized for gaslighting him.

That's Google's AI strategy in 2025: ship fast, ship big, deal with the consequences later.

On November 18, 2025, Google launched Gemini 3. Not a quiet beta rollout. Not a limited preview. Day-one integration into Google Search, reaching 2 billion people using AI Overviews every month. The Gemini app itself? 650 million monthly active users.

This is speed. This is scale. This is also—according to former Googlers and outside observers—rushed, reactive, and following a "me-too" playbook as OpenAI dominates the conversation.

So what's actually happening inside Google's AI push? Let's look at the data.

Gemini 3: "Most Intelligent Model" or Rushed Rollout?

Google claims Gemini 3 is the most intelligent AI model ever created. Independent benchmarks agree—sort of.

Artificial Analysis, an independent AI benchmarking organization, crowned Gemini 3 Pro "the new leader in AI" globally. On the LMArena leaderboard, it hit 1501 Elo—the first model to crack 1500 points. On GPQA Diamond (PhD-level scientific reasoning), it scored 91.9%, beating Claude Sonnet 4.5 and ChatGPT 5.1.

On paper, Google finally has the crown. But there's a problem.

When Your AI Doesn't Know What Year It Is

Andrej Karpathy—former Tesla AI director, OpenAI co-founder, one of the most respected AI researchers alive—got early access to Gemini 3 on November 17. One day before public launch.

He told the model it was 2025. Gemini 3 didn't believe him.

Karpathy called this "model smell"—a riff on "code smell" in software engineering. When the AI goes off-script, you see its personality. And its flaws.

This wasn't a fatal bug. But it's telling. Google shipped Gemini 3 to 2 billion people in Search on day one. The model shipped with outdated training data and required manual tool activation to know what year it was.

The Publisher Traffic Apocalypse

While Google celebrated Gemini 3's launch, publishers were watching their analytics dashboards in horror.

Google's Defense: "Traffic Is Stable"

In August 2025, Liz Reid—Google's VP and Head of Search—published a blog post claiming "total organic click volume from its search engine to websites has been 'relatively stable' year-over-year."

She called third-party reports showing dramatic declines "flawed methodologies."

Publishers didn't buy it. Digital Content Next (representing 40 premium publishers including The New York Times, Condé Nast, and Vox) released detailed data from 19 member companies. Median year-over-year referral traffic from Google Search declined 10%. News brands: -7%. Non-news brands: -14%.

Stuart Forrest, global director of SEO at Bauer Media, said it plainly: "We're definitely moving into the era of lower clicks and lower referral traffic for publishers."

What Reddit's SEO Community Is Saying

The r/SEO subreddit has become an unofficial support group for publishers watching their traffic vanish. Analysis of the community shows negative sentiment jumped by 25% since AI Overviews expanded.

The irony isn't lost on publishers: Reddit itself has been one of the biggest winners from AI Overviews, with its content being cited more frequently than traditional news sources. Between August 2024 and June 2025, Reddit was the most-cited domain by both Google AI Overviews and Perplexity AI.

Source: Medium analysis of Reddit SEO community sentiment, Columbia Journalism Review: Reddit Is Winning the AI Game

The "Glue on Pizza" Problem: When AI Overviews Go Wrong

Gemini 3 wasn't Google's first AI embarrassment in 2025. Earlier in the year, AI Overviews went viral for absurd—and dangerous—suggestions.

The root cause? Google's AI was trained on Reddit data (Google pays Reddit $60 million a year for access). It couldn't distinguish jokes from facts. It couldn't identify satire. It confidently repeated nonsense.

Liz Reid acknowledged the issue: "Some odd, inaccurate or unhelpful AI Overviews certainly did show up. While these were generally for queries that people don't commonly do, it highlighted some specific areas that we needed to improve."

Google's fix: limit reliance on user-generated content and better detect satire. But the damage was done. Trust eroded.

Gemini 1's "Woke Output" Controversy

Before the glue-on-pizza fiasco, there was Gemini 1's image generation crisis.

In February 2024, Google paused Gemini's image generation after it produced historically inaccurate images: Black Vikings, racially diverse Nazi soldiers, a female pope. The internet exploded. Google apologized and pulled the feature.

The issue? Overcorrection for diversity in training data led to absurd outputs. Google tried to avoid bias and ended up creating different bias.

It took months to fix. Gemini's reputation never fully recovered.

The Research Nobody Talks About: AI Assistants Are Wrong 45% of the Time

A study by BBC and EBU (European Broadcasting Union) found that 45% of AI assistant answers contain "major issues." Not minor errors. Major problems.

This isn't unique to Google. ChatGPT, Perplexity, and others have similar issues. But when you're shipping AI to 2 billion users in Search—where people expect factual answers—45% error rates matter.

Inside Google's Rush: "Follow-a-Competitor Strategy"

Ex-Googlers describe the company's AI strategy as "rushed" and driven by OpenAI's success. Internal memos show debates between safety teams and product teams. Safety wanted slower, more rigorous testing. Product wanted to ship fast.

Sundar Pichai, Google's CEO, called 2025 "a critical year" in leaked audio from an internal meeting. He told employees: "I think it's really important we internalize the urgency of this moment, and need to move faster as a company. The stakes are high."

Employees asked about ChatGPT "becoming synonymous with AI the same way Google is to search." The fear is real. Google has the technology. But OpenAI has the brand.

What's Actually Working for Google

So is this all a disaster? Not quite. Google has real advantages.

Scale Nobody Else Has

• 2 billion users of AI Overviews: OpenAI's ChatGPT has hundreds of millions of users. Google has billions.
• 650 million Gemini app users: This is the fastest-growing consumer product in Google's history.
• 13 million developers: Building with Google's generative AI models.
• 70% of Google Cloud customers: Using Google's AI tools.

Ironwood: The Hardware Advantage

Google unveiled its seventh-generation Tensor Processing Unit (TPU) in November 2025. Ironwood is custom-built for training and running massive AI models at scale. It's cheaper and more efficient than Nvidia GPUs for Google's workloads.

OpenAI rents compute. Google owns it. That's a long-term cost advantage.

Benchmark Wins

Gemini 3 isn't fake. It really did top the leaderboards. On Humanity's Last Exam, it scored 37.5%—better than GPT-5 Pro's 31.64%. On math, science, multimodal reasoning, and agentic AI benchmarks, Google is genuinely competitive.

Whether benchmarks translate to real-world superiority is a different question. But Google's catching up.

Stock Market Believes the Story

Google's stock surged 70% in 2025. It jumped 12% after Gemini 3's launch. The company is approaching a $4 trillion market cap.

Investors believe Google can win the AI race. Whether they're right is TBD.

The Real Problem: Google's Conflict of Interest

Here's the tension nobody's solved: Google makes money when people click ads. AI Overviews reduce clicks. Zero-click searches kill publisher traffic—and publisher revenue. Google's ad business depends on a healthy web ecosystem. AI Overviews are destroying that ecosystem.

Chegg's lawsuit against Google makes this explicit: AI Overviews are "materially impacting our acquisitions, revenue, and employees."

If Google succeeds with AI Overviews, it might kill the business model that made Google rich.

What This Means for Developers

If you're building on Google's AI tools, here's what you should know:

• Speed is the priority: Google is shipping fast—sometimes too fast. Expect bugs, retractions, and rapid iteration.
• Scale is real: 2 billion users of AI Overviews means massive distribution. If your product integrates with Google's AI, you have instant reach.
• Quality is inconsistent: Gemini 3 tops benchmarks. It also forgot what year it was. Hallucinations, errors, and weird outputs are part of the deal.
• The ecosystem is unstable: Publishers are losing traffic. Business models are breaking. If you depend on Google Search traffic, you're vulnerable.
• Google's catching up, not leading: OpenAI still sets the pace. Google reacts. That might change, but it hasn't yet.

The Bottom Line

Google shipped Gemini 3 to 2 billion people on day one. That's aggressive. That's scale nobody else has. It's also rushed.

Publishers are watching their traffic collapse. Chegg cut 45% of its workforce and sued Google. CNN lost up to 38% of its traffic. Zero-click searches jumped from 56% to 69% in a year.

Gemini 3 tops benchmarks—and also didn't know what year it was until a researcher turned on Google Search manually. It told people to put glue on pizza and eat rocks. It generated historically inaccurate images.

Sundar Pichai calls 2025 "critical." He's right. Google is moving fast because it has to. OpenAI owns the conversation. Google has the scale, the infrastructure, and the technical chops. But it doesn't have the brand dominance it once did.

Google isn't losing. But it's not winning the way it used to. And 2025 is the year we find out if speed, scale, and infrastructure beat brand, trust, and first-mover advantage.

Related Articles

Google's ADK and the Great Go Framework Wars

Google launched an AI development kit that might reshape how we build AI agents. Or it might get ignored. Framework wars are weird.

Analysis • 12 min read

Chinese AI Dominance: What the West Isn't Seeing

DeepSeek, Qwen, and others are releasing models that rival GPT-4. At a fraction of the cost. Here's what's happening.

Research • 14 min read

Anthropic's Path to Profitability (Or Not)

Claude is technically impressive. The business model is unclear. What we know about Anthropic's finances.

Business Analysis • 10 min read