OpenAI and the broader AI industry have moved decisively from speculation to demonstrated productivity gains, with companies now spending billions on AI tools that deliver measurable results. Six months ago, experts worried the AI sector was a bubble similar to the dot-com crash. Today, that narrative has flipped entirely. Software developers are adopting AI tools at scale and reporting genuine productivity improvements, while companies are scrambling to secure computing resources to meet skyrocketing demand.

What Changed to Make AI Suddenly Profitable?

The turning point came in November when Anthropic released Claude Code, an update that let teams of autonomous AI agents take over computers and complete programming tasks in minutes or hours that previously required humans days or weeks. OpenAI followed with similar updates to its own coding tools, and other companies released competing products considered nearly as impressive. This wasn't just incremental progress; it represented a fundamental shift in what AI could do.

The evidence is striking. Researchers at a think tank called Model Evaluation and Threat Research ran an experiment where software developers were randomly assigned to complete coding tasks with or without AI. In an earlier test, developers actually worked 20 percent slower with AI because they spent so much time correcting errors. But when the same researchers re-ran the experiment using the latest AI coding tools, developers completed tasks almost 20 percent faster with AI than without it.

"This really was a step change. For years now, we've been in an era of chatbots that mostly just say things. Now we've officially crossed into the era of agents that can actually do things," said Ethan Mollick, co-director of the Generative AI Lab at the University of Pennsylvania.

Ethan Mollick, Co-director of the Generative AI Lab at the University of Pennsylvania

Real-world adoption tells the same story. By one estimate, the percentage of American businesses with a paid subscription to at least one AI tool or service jumped from about 25 percent at the beginning of 2025 to over 50 percent today. Researchers at Goldman Sachs interviewed 40 software companies about their AI spending in mid-April and found many were "overrunning their initial budgets" by orders of magnitude, with some already spending as much as 10 percent of their total engineering labor costs on AI tools.

How Is This Productivity Boom Affecting Sam Altman's Bottom Line?

The financial impact has been extraordinary. In just two months, Anthropic's annual run rate, which measures how much revenue the company would generate if current monthly earnings continued for a full year, jumped from $14 billion to $30 billion. To put that in perspective, Anthropic grew four times as much during the first quarter of this year as Google did over three years during its peak expansion.

OpenAI's own revenue growth is nearly as impressive. The company's annualized revenue increased by nearly 20 percent from December to February. Beyond the flagship AI companies, the entire ecosystem is booming. Google, Microsoft, and Amazon reported in February that their cloud revenue had grown by 48 percent, 39 percent, and 24 percent respectively compared with the year prior, largely driven by AI firms using their services.

This demand surge has created a supply crunch. Anthropic has been forced to limit customers' use of its coding tools during peak hours, and OpenAI scrapped its video-generation app to free up computing power for more profitable services. Semiconductors are in such high demand that even Nvidia's fourth-best AI chip, released back in 2022, costs more today than it did three years ago.

Ways AI Adoption Is Reshaping Business Operations

• Workforce Productivity: A member of the technical staff at semiconductor-research firm SemiAnalysis reported his small team now produces four times as much software as it did last year despite having the same number of employees.
• Project Scaling: Meta announced it will lay off 10 percent of its workforce, with CEO Mark Zuckerberg telling investors that projects requiring big teams can now be accomplished by a single talented person thanks to AI.
• Budget Reallocation: Companies are spending unprecedented amounts on AI infrastructure, with some allocating 10 percent of their total engineering labor costs to AI tools and services.

The implications extend beyond revenue numbers. The AI models powering this growth continue to improve at an accelerating pace. In early April, Anthropic announced Mythos, a new model so powerful the company did not release it to the public. Mythos has exceeded just about every benchmark of AI progress, including completing complex coding tasks and solving graduate-level problems across multiple subjects. It has also discovered cybersecurity vulnerabilities that had gone undetected by humans for decades.

"On basically every indicator we have, we were already seeing a big acceleration in the pace of AI progress, and that was before Mythos," said Jean-Stanislas Denain, a senior researcher at Epoch AI, a think tank that measures AI capabilities.

Jean-Stanislas Denain, Senior Researcher at Epoch AI

OpenAI's newly released GPT-5.5 is not far behind Mythos in capability. The convergence of proven productivity gains, explosive revenue growth, and continued model improvements has fundamentally altered the conversation about AI's viability. Where experts were comparing the AI buildout to historical bubbles like the railroad boom of the 1800s and the dot-com crash of the 1990s, the narrative has shifted to questions about whether companies are building enough data centers to meet demand.

Even Sam Altman himself acknowledged the bubble concerns last year. "Are we in a phase where investors as a whole are overexcited about AI?" he asked publicly. "My opinion is yes." That skepticism now appears premature. The productivity data, adoption rates, and revenue trajectories suggest the AI sector has moved from speculation into a new phase where the technology delivers tangible business value.

"It's very important to emphasize that this pace of revenue growth is absolutely not normal. Even the biggest AI boosters, myself included, have been caught by surprise by just how fast these companies are taking off," said Azeem Azhar, a widely cited AI-industry analyst.

Azeem Azhar, AI-Industry Analyst

Some skeptics still argue the AI sector only appears solid on the surface, with flagship companies like OpenAI and Anthropic bringing in substantial revenue but not yet achieving profitability. They continue spending all incoming revenue and more to develop next-generation models. However, the sheer speed of adoption, the measurable productivity gains, and the willingness of enterprises to dramatically increase spending suggest the market has moved decisively beyond the speculative phase that characterized the sector just six months ago.