“AI-driven transformation is changing work, work artifacts, and workflow across every role, function, and business process,” said Satya Nadella, chairman and chief executive officer of Microsoft. “We are expanding our opportunity and winning new customers as we help them apply our AI platforms and tools to drive new growth and operating leverage.”
“Our AI business is on track to surpass an annual revenue run rate of USD 10 billion next quarter, which will make it the fastest business in our history to reach this milestone,” Nadella told analysts during the company’s fiscal first-quarter earnings call on October 30.
“Azure OpenAI Service usage more than doubled over the past six months, as both digital natives like Grammarly and Harvey, as well as established enterprises like Bajaj Finance, Hitachi, KT, and LG, move apps from test to production. GE Aerospace, for example, used Azure OpenAI to build a new digital assistant for all 52,000 of its employees. In just three months, it has been used to conduct over 500,000 internal queries, and process more than 200,000 documents,” Nadella said.
“We are also bringing industry-specific models to Azure AI, including a collection of best-in-class multimodal models for medical imaging,” he noted, highlighting that usage of Azure Cosmos DB and Azure SQL DB Hyperscale has accelerated as customers like Air India, Novo Nordisk, Telefonica, Toyota Motor North America, and Uniper leverage capabilities designed for AI applications.
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AI-Powered Analytics and Data Platform
Microsoft’s AI-powered analytics and data platform, Microsoft Fabric, is being utilized by customers like Chanel, EY, KPMG, Swiss Air, and Syndigo to unify their data across clouds, Nadella added, noting that the company now has over 16,000 paid Fabric customers, including over 70 percent of the Fortune 500.
Major enterprises are quickly adopting Microsoft’s AI tools, with nearly 70 percent of Fortune 500 companies using Microsoft 365 Copilot, the company’s AI-powered workplace assistant. “Vodafone, for example, will roll out Microsoft 365 Copilot to 68,000 employees after a trial showed that on average they saved three hours per person per week. And UBS will deploy 50,000 seats, in our largest FinServ deal to date,” Nadella said.
Microsoft is also seeing strong traction in specialised AI applications. Nadella noted that DAX Copilot is now documenting over 1.3 million physician-patient encounters each month at more than 500 healthcare organisations, including Baptist Medical Group, Baylor Scott and White, Greater Baltimore Medical Center, Novant Health, and Overlake Medical Center.
CFO Amy Hood told investors during the earnings call that demand for artificial intelligence “continues to exceed our available capacity.”
Also Read: Microsoft Announces New AI Models and Solutions for Healthcare
AI Investments
The company announced new cloud and AI investments in Brazil, Italy, Mexico, and Sweden to expand capacity in line with long-term demand. Microsoft is also diversifying its AI computing capabilities, offering “a broader selection of AI accelerators, including our proprietary accelerator, Maya 100, as well as the latest GPUs from AMD and Nvidia,” Nadella said.
“Our partnership with OpenAI also continues to deliver results. We have an economic interest in a company that has grown significantly in value, and we have built differentiated IP and are driving revenue momentum, Nadella noted.
“Our strategic partnership and investment in OpenAI has been pivotal in building and scaling our AI business, and positioning us as the leader in the AI platform wave” Amy Hood said.
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CapEx for OpenAI Scaling
In response to a question from UBS about the CapEx requirements of supporting OpenAI’s scaling ambitions, Nadella highlighted the mutual benefits of the partnership saying, “The partnership has been super beneficial”.
“We effectively sponsored what is one of the most, highest valued private companies today when we invested in them, and really took a bet on them and their innovation four or five years ago. And that has led to great success for Microsoft. That’s led to great success for OpenAI. And we continue to build on it,” Nadella added.
“We feel very, very good about our investment stake in OpenAI. And so, our focus and we’re always in constant dialogue with them. In a partnership like this, when both sides have achieved mutual success at the pace at which we’ve achieved it, that means we need to push each other to do more to capture the moment. And that’s what we plan to do, and we intend to keep building on it,” Nadella added. According to Hood, the company has invested USD 13 billion in OpenAI to date.
“The expansion of capabilities, the speed of innovation, the magnitude of the opportunities ahead for generative AI makes this the most exciting period for software I’ve seen in my 25 years of covering this space,” said Morgan Stanley’s Keith Weiss, congratulating Nadella on a strong quarter.
Also Read: Microsoft Targets Ecosystem Partnerships to Make India as AI-First Nation: Report
Constrained Encountered by Microsoft
Addressing a question related to constraints Microsoft has encountered, Nadella noted that “demand all showed up pretty fast.”
“Pick the top 4 or 5 products of this generation, they’re all in and around our ecosystem,” he said.
“We ran into a set of constraints which are everything because DCs (data centers) don’t get built overnight. There is DC, there is power and so, that’s been the short-term constraint,” he explained.
“In the long run, we do need effectively power, and we need DCs. And some of these things are more long lead, but I feel pretty good that going into the second half of even this fiscal year, that some of that supply demand will match up,” he added.
“Roughly half of our cloud and AI-related spend continues to be for long-lived assets that will support monetisation over the next 15 years and beyond. The remaining cloud and AI spend is primarily for servers, both CPUs and GPUs, to serve customers based on demand signals,” Amy Hood said, adding that the company expects capital expenditures to increase sequentially based on demand signals from cloud and AI.
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