Continuity with the surrounding architecture often matters more than GPU performance. “Hyperscalers retain significant advantages in breadth and integration,” adds Scott Sanders, corporate vice president of engineering at Sonar, a code quality and security company. “For organizations whose AI workloads sit inside a larger enterprise, hyperscalers offer continuity that a specialized provider can’t easily substitute.”
Resilience is another area to consider. “While performance and cost for AI may improve, risks include portability challenges, operational overhead, and reliance on niche providers,” says Nigel Gibbons, director and senior advisor at NCC Group, a cybersecurity consulting firm. “This means enterprises must balance optimization against resilience, support depth, compliance coverage, and long-term vendor viability, particularly for mission-critical or regulated workloads.”
Lastly, while neoclouds offer competitive prices now, they are highly reliant on the fluctuating GPU hardware market, placing their top unique differentiator on shaky ground. “Unlike railroads or even fiber optics — capital intensive booms of the past that spurred massive investment — GPUs don’t retain their value for decades,” Futuriom notes. “In fact, they depreciate fast — sometimes as fast as four to five years.”
