Three-quarters of new code written at Google is now generated by AI. That number — disclosed by CEO Sundar Pichai at Google Cloud Next 2026 — is significant not just for its size, but for how fast it got there.

In late 2024: 25%. Last fall: 50%. Today: 75%.

That’s a tripling in roughly 18 months. At one of the world’s largest software engineering organizations.

What Google Is Actually Doing

The AI-generated code at Google isn’t replacing engineers — it’s going through them. Every line is reviewed and approved by a human engineer before it ships. The shift is in where the initial work happens: increasingly, the first draft comes from AI tools, and engineers spend their time reviewing, correcting, and directing rather than typing from scratch.

Google’s engineers are primarily using Gemini models for code generation, embedded through Gemini Code Assist. The company has also been factoring AI adoption metrics into performance reviews, which means there’s structural incentive driving the numbers up, not just voluntary adoption.

“Recently, a particularly complex code migration done by agents and engineers working together was completed six times faster than was possible a year ago with engineers alone,” Pichai said in his keynote remarks.

That’s not a minor productivity bump. A 6x speedup on complex migrations is the kind of efficiency gain that changes how teams plan work.

The Agentic Shift

Pichai was specific about the direction: the company is moving toward “truly agentic workflows” where engineers run more autonomous tasks. This isn’t just Copilot-style autocomplete. It’s agents completing end-to-end tasks — full code migrations, refactors, feature implementations — with engineers in a supervisory role.

There’s a subplot worth noting: some Google DeepMind employees have been permitted to use Anthropic’s Claude Code for their work, which has reportedly created internal tensions. The implication is that Google’s own Gemini tooling isn’t meeting all engineering needs at the frontier, and individual engineers are reaching for alternatives. The 75% figure is the aggregate headline — the reality inside teams is messier.

Industry Context: This Is the New Normal

Google isn’t alone. Microsoft said 20-30% of code in some projects was AI-written in April 2025, and its CTO Kevin Scott predicted 95% of all code would eventually be AI-generated. Uber disclosed this week that roughly 70% of its committed code is now AI-generated, with 5,000 engineers using Claude Code monthly.

The pattern is consistent across companies at scale: when AI coding tools become genuinely useful, adoption accelerates faster than anyone plans for. Google’s 25% → 50% → 75% trajectory over 18 months is probably a template for what other large tech companies will experience over the next two years.

What It Means for the Profession

The engineering profession isn’t disappearing — but the job is changing structurally. At 75% AI generation with human review, the primary skill is no longer writing code. It’s reading code, evaluating code quality, directing AI agents toward the right problem, and catching the subtle errors that automated generation introduces.

This is already the reality at Google. It will become the reality everywhere else on roughly the same timeline as AI coding tools improve.

The tipping point has been crossed. The question isn’t whether AI-generated code becomes dominant — it’s how fast organizations update their hiring, training, and tooling strategies to reflect a world where it already is.

Sources

  1. Business Insider — Google says 75% of new company code is AI-generated
  2. Google Cloud Blog — Welcome to Google Cloud Next ‘26
  3. Reuters — Google Cloud Next 2026 coverage
  4. The Next Web — Google AI code generation report

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