OpenAI Code Red: Google Gemini 3 Sparks AI Race

OpenAI Declares Code Red as Google Closes the Gap

OpenAI CEO Sam Altman has issued an internal code red memo to employees, signaling urgent action to improve ChatGPT as Google's Gemini 3 model gains momentum in the AI race. The directive, reported by The Information, delays several planned initiatives including advertising integration, AI agents for health and shopping, and a personal assistant feature called Pulse 1

. In the memo, Sam Altman wrote that "We are at a critical time for ChatGPT," establishing daily calls for employees responsible for enhancing the chatbot and encouraging temporary team transfers to accelerate development 4

Source: Geeky Gadgets

The urgency comes as Google's Gemini app has grown from 450 million monthly active users in July to 650 million in October, adding 200 million users in just three months. ChatGPT maintains a larger user base with more than 800 million weekly users, but the rapid user growth of Google's Gemini signals intensifying competition 1

. Google released Gemini 3 in mid-November, and the model quickly topped the LMArena leaderboard, outperforming ChatGPT on some industry benchmarks 1

Source: BreakingNews.ie

AI Race Comes Full Circle

The code red declaration creates a striking symmetry with events from December 2022, when Google management declared its own internal emergency after ChatGPT launched and rapidly gained popularity. At that time, Google CEO Sundar Pichai reassigned teams across the company to develop AI prototypes and products to compete with OpenAI's chatbot 1

. Now the tables have turned, with OpenAI responding defensively to Google's advances. Salesforce CEO Marc Benioff publicly announced he was switching to Gemini 3 after using ChatGPT daily for three years, writing on X that "The leap is insane" 1

Google's success with popular AI tools like the Nano Banana image model has helped drive user growth, while Gemini 3 has blown past competitors on many industry benchmarks and popular metrics 4

. This shift in momentum matters because it demonstrates that early market leadership in AI doesn't guarantee sustained dominance, particularly when competitors have substantial resources and distribution advantages.

Financial Pressures Mount for OpenAI

OpenAI faces a critical competitive disadvantage that amplifies the stakes of this AI race. Unlike Google, which subsidizes its AI ventures through search advertising revenue, OpenAI does not turn a profit and relies on funding to survive. The company has committed more than $1 trillion in financial obligations to cloud computing providers and chipmakers that supply the computing power needed to train and run its AI models 1

. Some reports indicate OpenAI has committed $1.4 trillion to infrastructure commitments over the next few years, making enterprise growth essential to its business model 2

Source: ET

Reuters columnist Robert Cyran suggested that OpenAI's announcement "added to the impression that OpenAI is trying to do too much at once with technology that still requires a great deal of development and funding." He noted that on the same day Altman's memo circulated, OpenAI announced an ownership stake in a Thrive Capital venture and a collaboration with Accenture, writing that "The only thing bigger than the company's attention deficit is its appetite for capital" 1

Enterprise AI Shows Mixed Results

Days after the code red memo, OpenAI released "The State of Enterprise AI" report highlighting enterprise usage gains. The data shows ChatGPT message volume growing 8x since November 2024, with close to 36% of U.S. businesses as ChatGPT Enterprise customers compared to 14.3% for Anthropic 2

. Organizations using OpenAI's API are consuming 320 times more reasoning tokens than a year ago, suggesting companies are using AI for more complex problem-solving, though this increased energy usage could prove expensive and unsustainable 2

However, productivity gains from AI tools in businesses remain modest. The report, based on anonymized data from more than 1 million business customers and a survey of 9,000 workers at nearly 100 organizations, found that ChatGPT Enterprise users save only 40 to 60 minutes per active workday on average 3

. While 75% of workers report that AI has improved either the speed or quality of their output, and 75% say they can complete new tasks they previously couldn't perform, the time savings fall short of the sweeping productivity overhaul many anticipated 3

Growing Divide in AI Adoption

OpenAI's data reveals a widening gap between "frontier" users in the 95th percentile of adoption intensity and average workers. Frontier employees send about six times more messages than average users and report bigger gains of over 10 hours per week 3

. Brad Lightcap, OpenAI's chief operating officer, explained that some companies "still very much see these systems as a piece of software," while others "are really starting to embrace it, almost more like an operating system" that enables re-platforming of company operations 2

The report found that use of custom GPTs jumped 19x this year, now accounting for 20% of enterprise messages, with digital bank BBVA regularly using over 4,000 custom GPTs 2

. The report also noted a 36% increase in coding-related messages outside of engineering, IT, and research teams, though this raises concerns about security vulnerabilities from non-technical workers generating code 2

Questions About Enterprise AI Spending

The timing of OpenAI's enterprise report appears designed to counter recent academic studies questioning the value of enterprise AI spending. An August study from MIT showed that 95% of organizations that invested in AI business products "found zero return" despite corporate investments of $30-40 billion 5

. A Harvard Business Review research initiative found that most professional AI use constituted "workslop," or work content that "masquerades as good work, but lacks the substance to meaningfully advance a given task" 5

Anthropic published its own research in late November claiming that using Claude cuts task completion time by 80%, from an average of 90 minutes down to 18 minutes. However, the company admitted these numbers "might overstate current productivity effects" because they don't account for time spent beyond conversations on Claude.ai 5

. Brad Lightcap directly addressed these academic studies, telling Bloomberg that "There's a lot of studies flying around saying this, that and the other thing. They never quite line up with what we see in practice" 5

What's Next in the AI Race

Altman's memo reportedly stated that OpenAI plans to release a new simulated reasoning model next week that may beat Gemini 3 in internal evaluations 1

. The back-and-forth cycle of one-upmanship is expected to continue as long as funding flows, though OpenAI's massive financial commitments and lack of profitability create pressure that Google doesn't face. The majority of OpenAI's revenue still comes from consumer subscriptions, a base threatened by Google's Gemini, while it must also compete against Anthropic for enterprise customers 2

. Whether the modest worker productivity gains will justify continued enterprise AI spending remains an open question, particularly as the AI industry faces infrastructure challenges including copper shortages, RAM shortages, and rising public concerns about data center expansion's health risks and electricity costs 5

OpenAI declares code red as Google's Gemini 3 gains 200 million users in three months

OpenAI Declares Code Red as Google Closes the Gap

AI Race Comes Full Circle

Financial Pressures Mount for OpenAI

Enterprise AI Shows Mixed Results

Growing Divide in AI Adoption

Questions About Enterprise AI Spending

What's Next in the AI Race

References

OpenAI CEO declares "code red" as Gemini gains 200 million users in 3 months

OpenAI boasts enterprise win days after internal 'code red' on Google threat | TechCrunch

AI Saves Workers Less Than an Hour Each Day, New OpenAI Report Shows

OpenAI declares 'code red' as Google catches up in AI race

Research commissioned by OpenAI and Anthropic claims that workers are more efficient when using AI -- Up to one hour saved on average, as companies make bid to maintain enterprise AI spending

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