The first quarter earnings reports from hyperscale public cloud providers highlight the challenges of repositioning themselves for the generative AI transformation promised by large language model (LLMs) even as those vendors must adapt to customers’ tighter tech budgets. Forrester clients can find our perspective here.
Microsoft’s bid to seize the initiative in cloud with an AI-everywhere Azure hasn’t yet shown up in earnings. While the company reported $22.1 billion in quarterly revenue for the Microsoft Intelligent Cloud segment — a marginal lead over the $21.4 billion claimed by AWS — Microsoft has rolled non-Azure properties and businesses into Intelligent Cloud. Microsoft’s reporting segments therefore make a head-to-head Azure-AWS comparison difficult. There’s no evidence that the Microsoft-OpenAI relationship has propelled Azure into actual leadership in the public cloud quarterly revenue totals.
But the advent of the AI cloud does have the potential to shake up the market by allowing current leaders and new challengers to focus on higher-margin AI services. The hyperscalers have been in a bruising battle for market share for years, region by region, server rack by server rack, even as the advent of the Kubernetes cloud native ecosystem put downward pressure on prices for most core services. At the same time, enterprise software companies like SAP and Salesforce disintermediate the hyperscalers by sitting on their infrastructure but locking them out of the higher-margin, business-facing services. Google has had to endure years of enormous losses before finally making it into the black in the first quarter, thanks to both organic growth in enterprise accounts and some accounting changes. Cloud providers are seeking relief from such price wars by charging premium prices for AI services that are now in great demand.
Alibaba’s restructuring is a leading indicator of how cloud providers will respond to the AI wave. Alibaba Cloud will be spun off into one of six different subsidiaries of the parent company and will seek private investment and, eventually, an IPO. This provides Alibaba with the potential to access capital to develop differentiating AI services for customers in China, APAC, and other regions where Alibaba has been historically strong. Alibaba used its earnings call to highlight its AI offerings.
This demarcation of Alibaba Cloud from the broader Alibaba Group leaves Microsoft alone among the four hyperscalers in obscuring how much money it makes from enterprise cloud services. Investors haven’t much cared, given Microsoft’s overall success and huge market capitalization. However, big Azure customers — which includes some of the world’s largest corporations and government entities — may want a clearer look at Azure’s numbers before they sign up for big-ticket AI projects and pay more for AI-boosted versions of generic cloud services.
Meanwhile, the market share leader, AWS, used its first quarter earnings call to highlight efforts to help customers save money to adapt to budget constraints. Supporting its customers this way can engender loyalty to AWS as it musters resources to match Microsoft’s ChatGPT offerings and Google’s Bard in the generative AI race.
Tech leaders who haven’t already prioritized evaluation of cloud provider AI offerings should do so — and those who are already engaged should assess at least quarterly. Set aside nice-to-have but potentially expensive AI-powered commodity services in favor of AI-assisted applications development in the near term and LLM and foundational AI model adoption for strategic efforts.