When ChatGPT launched in late 2022, it caught the public and the tech industry off guard, including Google. In a recent interview at Google’s Manhattan offices, CEO Sundar Pichai spoke about the moment he realised how fast the AI race had picked up pace. Despite having positioned Google as an “AI-first” company back in 2015, Pichai admitted that the speed at which things moved still took him by surprise.
Speaking to Fast Company, he recalled his first reaction to seeing OpenAI’s chatbot: “Wow, this technology is going to diffuse earlier and faster than we were expecting.”
How ChatGPT Triggered A ‘Code Red’ At Google
Pichai described the moment as “uncomfortably exciting.” What made it more striking was the fact that Google’s own research labs already had the technology needed to build something similar. It was OpenAI, however, that was first to turn it into a product that grabbed global attention.
Reports from that period said Google had internally declared a ‘Code Red’, with employees rushing to respond. Pichai confirmed that this scramble eventually led to the development of Gemini 3, Google’s latest AI model series.
Released in late 2025, Gemini 3 Pro has since outperformed rivals from OpenAI and Anthropic across several industry benchmarks.
The tables then turned, with OpenAI CEO Sam Altman reportedly issuing his own internal warning, telling staff that “the vibes out there” would be “rough for a bit” as Google found its footing again.
What Pichai Said About Google’s Long-Term AI Strategy
This is not the first time Pichai has addressed the ChatGPT launch. At Salesforce’s Dreamforce conference last year, he acknowledged that OpenAI deserved credit for moving first, even though Google had been working on similar technology.
“We knew in a different world, we would’ve probably launched our chatbot maybe a few months down the line,” he said, adding that the product had not yet met Google’s internal quality standards at the time.
Pichai also spoke about Google’s broader approach, describing it as a “full-stack” strategy that focused on building from infrastructure to model training. “If you were on the outside, it would look like we were quiet, or we were behind, but we were putting all the building blocks in place, and then executing on top of it,” he said.
