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

OpenAI and Anthropic have released a pair of new reports on how the use of their AI products helps to grow enterprise productivity. The reports serve as the AI industry's latest response to a wave of recent academic studies amid a sea of public discontent pushing back on the AI data center boom, as the big AI firms seek to stow doubts in the value of enterprise AI spending.

OpenAI's report released today, "The State of Enterprise AI", hinges on two major points: companies are using AI more, and workers are saving time as a result. OpenAI claims that in a survey of 9,000 workers across 100 companies, workers reported having saved 40 to 60 minutes of work per day on professional tasks with the use of ChatGPT. Of these 9,000 workers, 75% of respondents reported that AI has improved either the speed or quality of their work.

Because OpenAI's report appears to be more focused on marketing to enterprise than performing scientific resaerch, there is no way of knowing beyond the most favorable published numbers how this 75% metric breaks down. Much of the data isn't very specific.

The OpenAI report also makes a case that companies are using AI more, stating that "frontier firms" and "leaders" are sending 6x more prompts to ChatGPT than "laggards", or the median AI-using firms. However, all this "6x" number proves is that some companies use ChatGPT more than others, saying nothing about the quality of the work done or how this usage affects business numbers.

OpenAI may be looking to contradict studies from educational institutions published earlier this year. 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. The study shows that the "vast majority" of AI pilot programs stall, delivering little to no measurable impact on profit. Shortly after, a research initiative from Harvard Business Review found that most professional AI use constituted little more than "workslop", or work content that "masquerades as good work, but lacks the substance to meaningfully advance a given task.”

In late November, Anthropic published its own research to respond to these allegations. The internal survey, submitted without peer review, found that using Claude, Anthropic's AI assistant, cuts down the time it takes people to complete work tasks by 80%, from an average of 90 minutes down to 18 minutes, based on a look at 100,000 private Claude conversations. But as the company admits, buried deep in the website copy, these numbers have no promise of actually reflecting real-world efficiency. "This doesn’t account for the time that humans might spend on these tasks beyond their conversation on Claude.ai, however, so we think these estimates might overstate current productivity effects to at least some degree," says Anthropic's own study.

Regardless of these self-admissions of weak methodology and the cherry-picking of numbers, the AI industry is still publicly bullish on its own claims of enterprise profit increase.

In a statement to Bloomberg, OpenAI COO Brad Lightcap directly addressed the MIT and Harvard Business studies. "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."

The AI industry doesn't just have academia to reckon with in the new year, however. The physical realities of the needs of the AI industry to keep up with data center expansion are catching up, with a copper shortage expected to hit data center buildouts in the next decade, matching the current RAM shortage crisis currently caused by AI data centers. Add this to rising public fear and outrage over data center expansion's health risks and rising electricity prices, and the AI juggernaut will have more pictures to paint than one of productivity.

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