OpenAI is in a far less commanding position than it was following the public release of ChatGPT a few short years ago.<\/p>\n
Back in 2022, the sudden popularity of ChatGPT sent Google into a panic<\/a>. The company was so worried about the possibility of the upstart chatbot disrupting its Search business, executives sounded a “code red” alert<\/a> inside of the company and called Sergey Brin and Larry Page out of retirement<\/a> to help it formulate a response to OpenAI. It then rushed out Bard, announcing its first commercial chatbot on February 6, 2023<\/a>. Google’s stock tanked days later when the AI incorrectly answered<\/a> a question about NASA’s James Webb Space Telescope during a public demo.<\/p>\n But it wasn’t just Google that wanted a piece of OpenAI, while the search giant sought to compete with it, others \u2014 including Microsoft and Apple \u2014 made deals with the company to bring its technology to their products and services, all the promise that AI would eventually revolutionize every facet of the economy.<\/p>\n Since then, OpenAI has seen its lead against Google and much of the AI industry evaporate, culminating in a series of successive blows throughout 2025. On January 20, the same day Altman was busy rubbing shoulders with other tech oligarchs at Donald Trump\u2019s inauguration, China\u2019s DeepSeek quietly released its R1 chain-of-thought model. A week later, the startup’s chatbot surpassed ChatGPT as the most-downloaded free app on the US App Store<\/a>. The overnight success of DeepSeek eliminated $1 trillion worth of stock market value, and almost certainly left OpenAI blindsided.<\/p>\n In response, the company showed a newfound urgency. In one week, for instance, OpenAI released both o3-mini<\/a> and Deep Research<\/a>. It even went so far as to announce the latter on a Sunday evening. But for all its new urgency, OpenAI’s biggest, most important release of the year was a miss.<\/p>\n It’s safe to say GPT-5 <\/a>hasn’t lived up to anyone’s expectations, including OpenAI’s own. The company touted the system as smarter, faster and better than all of its previous models, but after users got their hands on it, they complained of a chatbot that made surprisingly dumb mistakes<\/a> and didn’t have much of a personality. For many, GPT-5 felt like a downgrade compared<\/a> to the older, simpler GPT-4o. That’s a position no AI company wants to be in, let alone one that has taken on as much investment as OpenAI.<\/p>\n Anthropic was quick to take advantage of the weakness, signing a deal with Microsoft to bring its Claude models to Copilot 365<\/a>. Previously, Microsoft depended exclusively on OpenAI for partner models in Copilot. Before the company announced the integration, reporting from The Information<\/a> said Microsoft made the decision based on the strength of Anthropic’s Sonnet 4.0 model<\/a>, judging it “perform[ed] better in subtle but important ways” relative to OpenAI’s offerings.<\/p>\n However, what will likely go down as the defining moment occurred a few short weeks after OpenAI announced the conclusion of its restructuring. On November 18, Google released Gemini 3 Pro<\/a>, and immediately the new model leap-frogged the competition, including GPT-5. As of the writing of this article, Google’s new model is at the top of LMArena<\/a>, the site where humans compare outputs from different AI systems and vote on the best one. GPT-5, by contrast, is currently ranked sixth overall, behind models from Anthropic and Elon Musk’s xAI.<\/p>\n According to a December 2 report from The Wall Street Journal<\/a>, Sam Altman sent a companywide memo following the release of Gemini 3 Pro. Echoing the words Google used to describe the situation it found itself against OpenAI in 2023, he called for a “code red” effort to improve ChatGPT. Altman reportedly told employees there would be temporary reassignments and that the company would delay some products, all in an effort to catch up to Google and Anthropic.<\/p>\n The few numbers these companies are willing to share don’t paint a promising picture for OpenAI. Each month, about 800 million people use ChatGPT. On paper, that’s impressive, but Google is catching up there too. In October, the company said the Gemini app had 650 million users, up from 450 million just a few months earlier in July, thanks to the popularity of its Nano Banana Pro image generator<\/a>.<\/p>\n More importantly, OpenAI has an inherent disadvantage against Google. For the search giant, AI may touch everything the company does now, but Gemini is just one product in an extensive portfolio that includes many other popular services. Google can fund its AI advancements with money it makes elsewhere. OpenAI cannot say the same. The company is constantly raising money to stay afloat, and according to a financial roadmap obtained by The Journal, it will need its revenue to grow to about $200 billion annually to become profitable by 2030. In November, Altman said on X the company was on track to hit above $20 billion<\/a> in annualized revenue this year.<\/p>\n In an effort to grow revenue, Altman and company have adopted an incredibly risky strategy. In recent months, OpenAI has signed more than $1.4 trillion<\/a> worth of infrastructure deals in a bid to outscale the competition that is already beating it. Many of those agreements can only be described as circular<\/a>, and I think the fears about a financial bubble are real. In the first half of 2025, investment in data centers accounted for nearly all of US GDP growth<\/a>. Even if there’s not a repeat of the 2008 housing market crisis or the dot-com crash, the AI boom is at the very least poised to make everyday electronics (and utilities<\/a>) more expensive for regular people in the short term.<\/p>\n Since late October, demand for server-grade computer components, including memory and storage, has sent the price of consumer PC parts skyrocketing as manufacturers devote more of their production capacity and wafers to high-margin customers like OpenAI and Google. Since late October, the cost of most RAM kits has doubled and tripled<\/a>. In November, the price of some SSDs went up by as much as 60 percent<\/a>. Next year, the cost of LPDDR5X memory, which is used in both smartphones and NVIDIA servers, is expected to climb as well.<\/p>\n “Be it carmakers, smartphones or consumer electronics, everyone that uses memory is facing pressure from price hikes and supply constraints in the coming year,” Zhao Haijun, the co-CEO of memory manufacturer SMIC told analysts, per Bloomberg<\/a>.<\/p>\n