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<\/p>\nNeoclouds have emerged as the fastest-growing niche within the data center landscape, with the sector\u2019s revenues nearly doubling on an annual basis. But these AI cloud specialists also carry additional risks that data center developers, operators and investors are still figuring out how to navigate.<\/p>\n
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Neoclouds \u2014 AI-focused cloud providers like CoreWeave<\/a> that offer on-demand access to the graphics processing unit\u00a0computing critical for AI \u2014 have seen a compound annual growth rate in revenue of 82% since 2021, according to a new report from JLL<\/a>.\u00a0<\/p>\n The report described the neocloud segment’s growth as \u201cunrivaled,\u201d even within the booming cloud service and data center industry. It is being driven by\u00a0seemingly insatiable corporate demand for AI that traditional cloud providers like Amazon Web Services<\/a>, Microsoft<\/a> and Google<\/a> have been unable to meet alone.<\/p>\n But even as these startup AI cloud specialists offer many customers advantages over the established as-a-service giants, there are concerns that fundamental aspects of the neocloud business model bring risks that data center landlords and investors may not be comfortable with.\u00a0<\/p>\n \u201cFunding will be a major factor to translate the potential of neoclouds into a reality capable of handling the AI load,\u201d Muhd Syafiq, director of JLL<\/a>\u2019s Asia-Pacific Data Center Research group, said in a statement. \u201cBuilding GPU infrastructure is capital-heavy, and investors should have a clear vision for delivering a viable business model and support from key clients before undertaking an entry into the neocloud space.\u201d<\/p>\n The nascent neocloud sector is dominated by a few major players, with CoreWeave by far the most prominent. Other key firms include Crusoe<\/a>, Nebius, and Lambda<\/a>. Additionally, the rapidly evolving ecosystem has\u00a0approximately 190 smaller individual operators.\u00a0<\/p>\n The industry\u2019s steep growth rate isn\u2019t the only indicator of its momentum. CoreWeave, despite a\u00a0lukewarm entrance onto public markets<\/a> in March, has seen its share price triple since the IPO. Meanwhile, over $10B in private investment was\u00a0allocated to the industry last year, a trend that has continued into this year with upstarts like Nebius landing funding rounds of over $1B, according to JLL.<\/p>\n GPU cloud specialists have come to fill a market need as corporate giants clamber for AI computing power. Not only are GPUs expensive and difficult to acquire, but they also require specialized data centers with advanced cooling systems capable of handling high power densities. Firms with AI computing needs that either operate their own data centers or utilize colocation may not be able to support GPUs with their current infrastructure.\u00a0<\/p>\n The major hyperscalers also have their own GPU cloud products. But neoclouds have emerged as a preferred option, or as a supplement to the established cloud giants, due to superior speed to market and lower pricing, according to JLL.<\/p>\n For firms that need GPU computing at a large scale quickly, neoclouds offer rapid deployment. While traditional hyperscalers add GPU capacity through large-scale data center buildouts that can take years, neoclouds can often have GPU infrastructure up and running within months.\u00a0<\/p>\n But neoclouds\u2019 primary competitive advantage is price. According to Uptime Institute<\/a>, these GPU-specialty providers offer, on average, a\u00a066% cost reduction<\/a> compared to hyperscalers, the result of being able to locate computing in cheaper locations than traditional cloud firms due to fewer latency restrictions and avoiding infrastructure costs needed for non-AI cloud services.<\/p>\n Neoclouds also offer shorter contract terms tailored to the way companies generally use AI-specific computing. This makes them far more cost-effective compared to hyperscalers for firms whose GPU computing needs are variable or intermittent.\u00a0\u00a0<\/p>\n \u201cNeoclouds have developed an advantage over traditional cloud providers by moving faster and pricing lower with flexible terms,\u201d Andrew Batson, JLL\u2019s head of data center research for the Americas, said in a statement. \u201cAs AI shows no signs of slowing, its success will rely on accessibility to GPU infrastructure, which neoclouds specifically cater to.\u201d\u00a0<\/p>\n Still, some of these advantages for customers present risks for data center developers, operators and investors with neoclouds as tenants, particularly the shorter contract terms compared to hyperscalers.\u00a0<\/p>\n While traditional data center leases span 10 to 15 years, neocloud GPU contracts are typically just two to five years. In some cases, the contracts are far shorter than that. It\u2019s a meaningful mismatch in an industry with asset payback periods of seven to nine years. One\u00a0industry insider compared this to the fundamental flaw that damaged\u00a0firms in the coworking office sector.\u00a0<\/p>\n \u201cI have a serious concern about those GPU-as-a-service companies,\u201d Jeffrey Moerdler<\/a>, a longtime data center attorney and member at Mintz, said\u00a0at Bisnow\u2019s DICE Capital Markets event in July.\u00a0<\/p>\n