Is Amazon’s once-dominant cloud business losing its edge in the AI race?

It’s no exaggeration to say Amazon.com Inc. invented the cloud business. Amazon Web Services took the corporate data center apart and split it into pieces, building pay-as-you go services delivered with remarkable speed and consistency. The effort brushed aside incumbents, transformed an internal startup into Amazon’s profit engine and gave executives in Seattle the power to dictate terms to much of the industry.

Now, suddenly, AWS is struggling. Last week, Amazon’s cloud unit suffered one of the worst outages in its history, taking down its most important cluster of data centers and disrupting the operations of hundreds of companies and consumer apps. Trading platforms, digital curriculums for students, online utility payments for Seattle, Amazon’s hometown, were all disrupted. The event dragged on for about 15 hours before AWS managed to get all of its services back online.

Then on Thursday, confirming a Bloomberg report, Alphabet Inc.’s Google said it will supply up to 1 million of its specialized AI chips to Anthropic PBC. The deal deepens Google’s partnership with the fast-growing artificial intelligence startup and represents a blow to Amazon, which has invested billions in Anthropic.

Three years into an AI boom spawned by OpenAI’s revolutionary ChatGPT, AWS is widely perceived as trailing its tech peers in AI. While AWS remains the cloud market leader, Microsoft Corp. is now growing its backlog of corporate sales faster than Amazon, a trend that recently favored AWS. Last year, according to a Gartner Inc. estimate, Amazon’s cloud division captured 38% of corporate spending on cloud infrastructure services. That sounds hefty until you consider that Amazon’s cloud division held almost half of that market as recently as 2018, according to the firm.

To understand what ails AWS, Bloomberg interviewed cloud computing and financial analysts, businesses that use or resell Amazon’s cloud, and 23 current and former AWS employees spread across engineering, product management, marketing, sales and support. They describe internal bureaucracy that has slowed AWS down at a time when it needs to be nimble, a lackluster start to the company’s AI efforts and an operation that has become less attractive to startups.

Despite all the challenges, these people said, AWS remains committed to its longtime playbook amid a rapidly changing marketplace. These people acknowledge that AWS retains considerable strengths and customer loyalty but they worry it’s losing its cutting edge and chasing rivals it once blindsided. Financial results due next week are expected to show a cloud business that grew 18% to $32 billion, slowing modestly from the 19% growth AWS posted a year earlier.

It doesn’t help that the cloud market has become more fiercely contested in the last couple of years. Oracle Corp., once dismissed as a cloud industry also-ran, has been booking multibillion-dollar deals to host cutting-edge AI development work. Google has become a much more serious threat. And a swarm of newcomers with little track record running massive data centers have ambitious plans to rent their infrastructure to AI companies.

Dave McCarthy, who advises corporate technology buyers at IDC, said clients once mostly wanted to understand the difference between Amazon’s and Microsoft’s cloud offerings. These days, they’re just as likely to ask about Google, Oracle and an upstart such as CoreWeave Inc. “There’s more choice out there,” McCarthy said. “It doesn’t bode well for Amazon. It’s creating some new competitive pressure that they didn’t have before.”

As it seeks to retake the initiative, AWS has reorganized engineering and sales teams, swapped chief executives and marketing chiefs, and thrown some of its own product development rules out the window in the name of speeding products to market. At the same time, employees said, the company has tried to streamline the bureaucracy that took hold after AWS went on a pandemic-era hiring spree.

Earlier this month, AWS released Quick Suite, which is designed to succeed its prior main workplace AI tool. In December, the company is expected to launch a flurry of new and restyled AI services.

“AWS remains the leader in cloud by a wide margin and we’re excited by the tremendous customer response we’re seeing to our AI services like Amazon Bedrock, SageMaker and Kiro, as well as the unique price and performance benefits they’re enjoying from our Trainium2 chips,” Amazon spokesperson Selena Shen said in an emailed statement.

In the last few months, she said, Amazon has signed significant deals with a wide array of customers, including Delta Air Lines, Volkswagen, the U.S. General Services Administration and State Farm. “If you look at any list of the world’s most innovative or fastest growing startups, you’ll find the vast majority are running significant workloads on AWS,” Shen added, citing lists from Forbes and CNBC, among others.

On Nov. 30, 2022 — the day ChatGPT debuted — AWS brass were in Las Vegas for their annual re:Invent conference. Adam Selipsky, then the cloud division’s CEO, gave a two-hour talk that amounted to an infomercial for AWS and an exhortation to get with the times and start using the cloud. “With AWS, you don’t have to worry about having too much or too little capacity,” he said.

AI barely merited a mention. That afternoon, OpenAI’s Sam Altman announced the release of ChatGPT — instantly turning the industry upside down.

Amazon, which has used algorithms to automate much of its operations, was hardly unaware that a new AI revolution was brewing. A few years earlier, AWS engineers had strung together about 6,000 Nvidia Corp. graphics processing units, creating an AI supercomputer before anyone would have called it that. At first, it went mostly unused. Even corporate giants didn’t need that kind of horsepower, and executives began worrying that the initiative was a wasteful research experiment, according to a person familiar with the matter.

Then a tiny startup called Anthropic, founded by former OpenAI personnel, began using the cluster of chips. The startup, already taking the first steps toward creating what would become known as generative artificial intelligence, chewed through whatever computing power AWS could throw at it. Even then, it was clear Anthropic was working on a potentially game-changing technology.

The obvious move was to invest in the startup, and Amazon considered doing just that, according to the person, who requested anonymity to discuss confidential information. Anthropic was spending most of its cash on Amazon servers. If the startup ever took off, so would its spending on AWS.

But Amazon executives weren’t convinced that Anthropic would find a way to monetize the emerging technology, the person said, and didn’t pursue the idea. The resistance was partly cultural: AWS has historically been reluctant to pay for access to technology that it believed could be readily developed in-house, two people familiar with the strategy said.

Anthropic, in the search for ever more computing power, subsequently started using Google’s cloud, in addition to Amazon servers. When the startup raised money from investors in early 2023, Google was among them.

Amazon invested in Anthropic that September, making the first of two planned $4-billion infusions. The deals committed Anthropic to using AWS computing power and in-house chips and offering its Claude models to Amazon customers. The size of the check shocked Amazon veterans who knew the company loathed paying tech industry prices. To some, it looked like desperation.

Amazon has long prided itself for operating like a startup, structured as a loose collection of independent teams that compete in a kind of Darwinian bakeoff. That worked well when the goal was creating streamlined databases or durable file storage systems. Not so much for deep research into models capable of displaying humanlike reasoning or generating video. When OpenAI debuted ChatGPT, science and engineering units nestled within AWS, Amazon’s retail organization and the Alexa and devices group were all pursuing similar, sometimes duplicative work training their own AI models, current and former employees said.

Executives eventually tried to impose order. A few months before the Anthropic investment, they centralized most cutting-edge model development work under Rohit Prasad, who led the engineering organization that built the brains behind Alexa. Swami Sivasubramanian, the cloud unit’s longtime AI chief, was ordered to focus on ways to help businesses actually use AI tools.

The new sense of urgency was palpable at AWS’ re:Invent conference in November 2023. Suddenly artificial intelligence was very much on the agenda, with Selipsky and other executives mentioning AI almost 100 times in two hours. They also debuted software called Amazon Q that included a chatbot and a software coding assistant. The offering gave Amazon salespeople a counter to ChatGPT, but didn’t introduce anything revolutionary to a market already awash with chatbots, according to analysts.

Seven months later, Selipsky was gone in what Amazon said was a planned transition. His replacement was Matt Garman, who had spent his career at AWS leading increasingly large engineering teams and, eventually, sales and marketing. Colleagues describe Garman as a whip-smart, occasionally brusque sports fan with a dry sense of humor and Amazonian distrust of conventional wisdom. For some of the company’s engineers, Garman also brought a credibility that Selipsky never established, and struck outside analysts as a better fit for the wartime conditions AWS found itself in.

Day writes for Bloomberg.