2026 is likely to be a year of nuance and divergences in the cloud services market, as the influence of AI on the cloud demands more diverse services.
R. Scott Raynovich is the Founder and Chief Analyst at Futuriom.comThe monolithic “AI trade” will be die in 2026. In the cloud services market, 2026 is likely to be a year of nuance and divergences, as the influence of AI on the cloud services and infrastructure markets becomes more fine-grained.
As demands for AI inferencing and enterprise agentic AI evolve rapidly, it will placing new demands on global infrastructure, including specific needs for security and resilience. This is where major hyperscalers and alternative cloudscale providers, which we call altscalers, can benefit if they bring AI services to market with powerful adjacent services, especially in data storage, security, and sovereignty. This evolution will also put pressure in the recently emerging GPU cloud market, including recent IPOs such as CoreWeave and Nebius, as customers demand more sophisticated infrastructure that can respond to their data services and security needs. Having GPUs is not enough—you need to connect them, secure them, and pair them with data services.As AI enters the mainstream of industry, global infrastructure for cloud services will be a differentiator. Infrastructure is difficult to build and creates a moat. Building and using frontier models has become commonplace, meaning LLMs are headed toward commodity—whereas building and hosting agentic AI applications with infrastructure is more of a challenge. An LLM on its own is not enough. The real value in bringing AI services to market will come down to how the technology can be packaged with the comprehensive infrastructure that is needed to build commercial enterprise services—which require integrated capabilities for data storage, security, analytics, networking, and agentic AI support. Our research also shows that specific infrastructure—often proprietary—is needed to bring data to the LLMs and fine-tune them with approaches such as retrieval-augmented generation, which requires gathering data from many places. This trend will favor incumbent service providers, including Amazon Web Services, Google Cloud, and Microsoft Azure. In addition, fast-growing altscalers can succeed when they execute on specific needs. Some examples of altscalers that are succeeding with differentiation are Cloudflare and Vultr. Cloudflare brings ease of use, a global footprint, and integrated security. Vultr also has a global footprint, transparent pricing, simplicity, and a comprehensive blend of services from GPUs to Kubernetes., the best investment performer in 2025 was Cloudflare, with a 60% gain. The jury is out on some of Cloudflare’s competitors in the content delivery in altscaler market, as they have shown less capability to execute, such as Akamai. Akamai has been a big disappointment in the AI boom, with sales growth stalled at 5% annually and a share price that has been flat for the past 12 months.Whether you are an investor or a corporate buyer of cloud services, you’ll have to stay nimble in 2026, because the market has demonstrated how fast it can change. Contrary to popular believe, there wasn’t a consistent “AI Trade” in 2025—it was widely dispersed. The case of Amazon and Google is a great example. Amazon traded basically unchanged in 2025, without the large gains of some AI plays. And while Google was scorned by investors in early 2025, its share performance roared in the second half of the year after it demonstrated its long game of integrating its own Gemini model across applications including search, as well as extensive work on proprietary infrastructure, including its own TPUs to provide an alternative to Nvidia. Google, a pioneer in AI, has a deep trove of AI IP as well as networking technology that can be used to build multicloud connectivity across the WAN. Google surged in the 2H as investors sniffed out that its strategy was winning, including its leverage in integrating Gemini with Google Search. It will likely continue to do well in 2026. This demonstrates the value of a comprehensive, integrated cloud infrastructure. 2026 may include similar surprises. While Amazon has recently been pegged as an AI laggard, this view may be overdone. AWS is still the largest and most comprehensive cloud services business, and it grew 20% in the third quarter of 2025, reaching revenue of $33 billion in sales. At AWS re:Invent in Las Vegas in December, AWS emphasized its broad array of both LLM models as well as hardware, including its own Trainium chips. Amazon is well positioned for the year of AI nuance, with a focus on using AI as a linchpin to connect customers to its broad infrastructure with security, data connectivity, and storage. After years of reluctance, it has also shown a desire to embrace multicloud and hybrid cloud architectures, which are fueled by AI. On an investor call this week with Roth Capital, analyst Rohit Kulkarni called Amazon his top pick among the megacap hyperscalers. It seems like a low-risk way to benefit from growth in AI. His mid-cap pick was a bit riskier: CoreWeave. Unlike the large hyperscalers, CoreWeave is a young cloud provider without profits and laden with billions of dollars in debt.As enterprises explore the use of agentic AI in corporate workflows, Futuriom’s own research shows the depth of complexity and nuance as they build AI-based applications. Three verticals remain on the cutting edge of AI deployment: retail, financial services, and healthcare. Among these verticals, proprietary and hybrid infrastructure is favored. Driving this trend is a keen emphasis on data security and sovereignty. Three verticals remain on the cutting edge of AI deployment: retail, financial services, and healthcare, according to Futuriom research.The hyperscalers and altscalers are well positioned for this need. Look for altscalers like Cloudflare and Vultr to beat out or even consolidate with the new wave of GPU clouds, the cloud providers focused on GPUs that emerged from the cryptocurrency industry. GPU clouds popped up in just a few years to fill the niche for GPU demand, but they will need to quickly diversify to avoid commodification. As we recently noted in a Futuriom research note, leading GPU cloud CoreWeave has made a push into object and distributed storage services, which are optimally located in proximity to GPUs. CoreWeave’s also focusing on Kubernetes optimization.With enterprises demanding cloud infrastructure to support AI—including distributed data, security, and data sovereignty—the AI services battle will come down to more than the best LLM. It will come down to who can most effectively pair LLMs with proprietary data and infrastructure. This will provide plenty of controversy for the perceived leader in LLMs, OpenAI. Our research shows that ChatGPT is still the leading model among enterprises we follow, though models from Google and Amazon run a close second and third in enterprise adoption—and are more than capable. Meanwhile, OpenAI’s growth rate has slowed and its now handcuffed by its gigantic valuation of $500 billion+ as well as its need to sustain circular financing deals with partners such as Nvidia and Oracle. OpenAI will need to expand its enterprises and show that it can become a larger provider of agentic AI tools. Its current revenue run rate of $20-$30 billion, primarily derived from its chatbot service, can’t possibly support a $500+ billion valuation. A clear demonstration of the competitive pressure in frontier models can be seen in AWS’s strategy to provide the largest diversity of models—including its own Bedrock and Nova models, as well as Anthropic’s Claude and models from AI21 Labs, Cohere, Mistral AI, Stability AI, Luma AI, DeepSeek, and Writer. There are many more! In conclusion, it’s still early in the AI era, and investors have perhaps been seduced by the macro story, just as they were seduced by the Internet in 1998-2000. The Internet went on to become the greatest technology trend in history, but picking winners and losers was very difficult. Google did not go public until 2004, well after the first Internet boom and bust. The AI story will be similar. It’s early days, and it’s possible the next Google has yet to come—or that it will be Google. One thing that’s clear in our research is that top executives are finding AI strategies intricate and challenging. Unlike many public reports, our research shows realized gains among enterprises, but this only comes in projects with a high degree of hybrid infrastructure integration and proprietary work. Futuriom provides paid research and marketing services to technology companies, with the goal of providing accurate insight into how cloud and AI infrastructure markets are evolving. These services include subscription research, custom research, and report sponsorships. In the past twelve months, Futuriom has not done any business with the companies mentioned in this article. The author holds no positions in individual technology stocks mentioned in this article.
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