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The top cloud services providers are in the early stages of what will continue to be a ferocious competition to lead the rapidly expanding generative AI (GenAI) market and all are going hard through the hoop to ensure that the much-sought-after developers pick their platforms to work on.
As Rob Enderle, principal analyst of The Enderle Group, told The New Stack, “If you don’t have developers, you not only lose them as customers, it reduces the attractiveness of your cloud offering significantly with other potential customers, potentially making your cloud service irrelevant.”
At its AWS New York Summit this week, Amazon Web Services, perceived in some circles as being behind the GenAI curve and trailing the likes of Microsoft and its Azure cloud, introduced two tools that have similar goals: to enable developers and other less-technical workers to spin up enterprise apps through GenAI prompts.
“We’re giving customers tools that put the power of generative AI into all employees’ hands, providing more ways to create personalized and relevant generative AI-powered applications, and working on the tough problems like reducing hallucinations so more companies can gain benefits from generative AI,” Swami Sivasubramanian, vice president of AI and data at AWS, wrote in a blog post.
Amazon Q Apps, is a new feature in Amazon Q Business, that employees can use to build their own GenAI apps to answer questions, create and summarize content, and leverage enterprise data. Amazon Q Apps lets employees to quickly create AI-powered apps based on company data by describing the desired app in a prompt in Amazon Q Business, a GenAI assistant launched in April. The new tool, which is generally available, will instantly generate it.
During the preview period for Amazon Q Apps, users were able to create apps for everything from summarizing feedback and creating onboarding plans to writing copy and memos, according to Sivasubramanian. He pointed to data security company Druva, which created an app via the tool for almost instantly summarizing information for requests-for-proposals, reducing RFP response times by 25%.
Meanwhile, AWS App Studio is now in preview. It’s an AI-based service aimed at technical people like IT project managers, data engineers, developers, and enterprise architects, who can use natural language to describe the application they want to build, outline what it should do, and include the data sources to leverage, and the App Studio will build it in minutes — a process he said would take a developer days.
“App Studio’s generative AI-powered assistant eliminates the learning curve of typical low-code tools, accelerating the application creation process and simplifying common tasks like designing the UI, building workflows, and testing the application,” Sivasubramanian wrote. “Each application can be immediately scaled to thousands of users and is secure and fully managed by AWS, eliminating the need for any operational expertise.”
In addition, AWS also dropped more capabilities into its Amazon Bedrock generative AI framework, including expanding the data sources developers can use for Retrieval Augmented Generation (RAG), which already includes document repositories, databases, and APIs. Now AWS is including connectors for Salesforce, Confluence, and Microsoft SharePoint — which is in preview — giving developers broader business data options for customizing their AI models. The company also is adding vector search for Amazon MemoryDB, joining other AWS services like OpenSearch Service and OpenSearch Serverless, Aurora, and Amazon Relational Database Service.
Bob O’Donnell, chief analyst with TECHnalysis Research, told The New Stack that he questioned AWS’ claim that Amazon Q Apps or App Studio can instantly spin up an application based on a few commands in a prompt — he doubted any cloud provider’s tools can do that yet — but said the company was on the right track by reducing the capabilities required for developers or anyone else to build AI applications in the cloud.
The introduction of the two tools is “a big step both philosophically and technically,” O’Donnell said, adding that it will be important to ensure that everyone in a company can access and use the massive amounts of data being generated and collected.
Like Enderle, he said that building out a rich developer AI toolset will be important to AWS and every other cloud services provider.
“At the end of the day, what’s needed to get traction in AI for every cloud provider is their app development tools,” O’Donnell said. “That’s what they need because the magic of AI doesn’t happen until you get those AI apps.”
Enderle added that “almost all AI apps are cloud-based, so all of the cloud providers are focused on making their offerings for these developers as attractive as they can. AI uses a ton of resources, thus it can generate an equally large amount of revenue.”
AWS isn’t unique in what it’s doing. Microsoft, Google, Oracle, IBM, and others also are aggressively expanding their portfolio of developer services with tools that can allow a wide range of people to more quickly and easily build AI applications. In a blog post in May, David Seda, general manager of Azure AI, noted the steep learning curve for a company’s own AI apps, with 52% of companies pointing to the lack of still workers as the biggest hurdle to implementing and scaling AI.
“To reap the true value of generative AI, organizations need tools to simplify AI development, so they can focus on the big picture of solving business needs,” Seda wrote, pointing to Azure AI Studio — Microsoft’s generative AI platform — as “bringing together the models, tools, services, and integrations you need to get started developing your own AI application quickly.”
The same month, Burak Gokturk, vice president and general manager of cloud AI and industry solutions for Google Cloud, touted his company’s four-year-old Vertex AI platform, saying that over the past year “we’ve expanded our offering for generative AI, bringing developers the widest variety of foundation models from any hyperscale provider, robust infrastructure options, and tooling for model development and MLOps.”
Unsurprisingly, Gartner in its Magic Quadrant for cloud AI developer services in April named AWS, Microsoft, Google, and IBM as market leaders. And it’s a fast-growing market. NexusTrend Research analysts this month said they expect the global cloud AI developer services market to jump from $61 billion last year to $108.96 billion by 2031, an annual average rate of 8.64%, noting that “companies operating in the Cloud AI Developer Services market are rapidly scaling their operations and enhancing their capabilities to meet this burgeoning demand, setting the stage for sustained growth over the forecast period.”
The accelerating innovation and adoption of generative AI technology and services also is impacting the cloud infrastructure services space, according to the Synergy Research Group. Global spending in the first quarter was more than $76 billion, a 21% year-over-year increase. AWS continued to hold the top spot, with 31 percent of the market, with Microsoft at 25% and Google with 11% rounding out the top three, with the last two having stronger year-over-year numbers than AWS.
All three will continue pushing out new developer-focused AI services, with none getting a clear advantage over the other, TECHnalysis’ O’Donnell said.
“It’s going to be a horse race, where they’re likely jumping over each other,” he said.
