Microsoft earnings: Five big takeaways

Microsoft’s latest earnings provide an handy insight into what the company thinks is important and where it’s going next. Here are five key takeaways.

1. If cloud is king, AI is the power behind the throne

Cloud continues to be an absolute powerhouse for Microsoft, passing $31.8 billion in quarterly revenue - up 24% in its first quarter fiscal year 2024 results. That’s significant figure considering the software giant’s total revenue stood at $56.5 billion; for context Microsoft is currently number two in the cloud market behind AWS and ahead of Google.

If cloud computing is where the revenue is for Microsoft, it’s the company’s big bets on generative AI over the last few years that are creating the new momentum right now.

In the company’s earnings call, Microsoft CEO Satya Nadella pointed to the arrival of new hardware like its next generation H100 virtual machines designed for high-end deep learning, and its range of AI models from OpenAI and open source models, including those from Meta and Hugging Face to allow customers to build their own apps.

Nadella said more than 18,000 organizations are using Azure OpenAI Service, including new customers – reflecting how AI tools are now a competitive differentiator. “And we’re expanding our reach with digital-first companies with OpenAI APIs, as leading AI startups use OpenAI to power their AI solutions, therefore making them Azure customers as well,” he noted.

 2. Cloud computing still has many stages

But it’s not all about futuristic AI: there are plenty of businesses still involved with classic cloud migration projects. Microsoft said it now has 21,000 customers using its Arc multi-cloud service, up 140% year-over-year. And Nadella pointed out that there are plenty of companies at different phases of their cloud migration journey, using the recently announced partnership with Oracle as an example.

“Once we announced that the Oracle databases are going to be available on Azure, we saw a bunch of unlock from new customers who have a significant Oracle estate that have not yet moved to the cloud, because they needed to rendezvous with the rest of the app estate in one single cloud,” he said. “In some sense, even the financial services sector, for example, is a good place where there’s a lot of Oracle that still needs to move to the cloud.”

3 Welcome to the age of Copilots

After its Bing Chat AI tool, probably Microsoft’s best known generative AI tool is its GitHub Copilot tool, which helps developers by recommending lines of code and even entire functions, and which it has said can increasing developer productivity by up to 55%. It now has over one million paid Copilot users and Nadella said more than 37,000 organizations have subscribed to Copilot for Business, up 40% quarter-over-quarter, with “significant traction” outside the US.

 But Microsoft’s ambitions stretch beyond developers to use this concept of a ‘copilot’ throughout its applications.

 “We’re using this AI inflection point to redefine our role in business applications,” Nadella said. “We’re becoming the Copilot-led business process transformation layer on top of existing CRM systems like Salesforce.”

 For example, Microsoft’s Sales Copilot is personalize customer interactions based on data from third party CRM systems. Meanwhile Microsoft said tens of thousands of employees at businesses including Bayer, KPMG, Mayo Clinic, and Visa are using Copilot as part of its early access program to improve their productivity when using Microsoft’s Office applications.

" Whether it’s in finance, or in sales... we’re seeing productivity gains like we saw with developers in GitHub Copilot," Nadella told the call.

 4. Microsoft’s AI stack strategy is taking shape

Behind this lies Microsoft’s tech strategy for AI which aims to create a level of consistency throughout the stack.

“The approach we have taken as a full stack approach all the way from whether it’s ChatGPT or Bing Chat or all our copilots all share the same model. In some sense, one of the things that we do have is very, very high leverage of the one model that we used, which we trained, and then the one model that we’re doing inferencing at scale,” Nadella said.

“And that advantage sort of trickles down all the way to both utilization internally, utilization of third parties. And also over time, you can see this sort of stack optimization all the way to the silicon, because the abstraction layer to which the developers are writing is much higher up than low level kernels, if you will.”

That doesn’t mean Microsoft doesn’t have people doing training for open source models or proprietary models, he said, “But the thing is, we have scale leverage of one large model that was trained and one large model that’s being used for inference across all our first-party SaaS app, as well as our API in our Azure AI Service.”

 5 But there could be trouble ahead for some

 Plenty of tech companies are investing rapidly in generative AI, but that doesn’t necessarily make it a one-way bet for everyone, and Nadella sounded a note of caution for other companies attempting to rethink their operations to incorporate AI.

 He said that in this “platform transition” companies need to be disciplined on both the tech stack and capital spending.

 “The lesson learned from the cloud side is this. We’re not running a conglomerate of different businesses. It’s all one tech stack up and down, Microsoft’s portfolio.

 "And that, I think, is going to be very important, because that discipline, given what the spend will look like for this AI transition, any business that’s not disciplined about their capital spent accruing across all their businesses could run into trouble.”