Data center server market to hit $471 billion by 2035

The massive expansion of the data center server market reflects the infrastructure reality required to support next-generation video delivery and AI-driven personalization. As streaming platforms integrate generative AI for content discovery and automated editing, the shift toward accelerated computing and high-bandwidth networking becomes a baseline requirement rather than a luxury. This infrastructure surge suggests that while software innovation captures headlines, the competitive moat in streaming is increasingly tied to physical compute density and energy-efficient hardware at the edge. Watch for a rise in ARM-based server adoption as platforms seek to balance these high-performance AI workloads with escalating power and cooling costs.

Hewlett Packard Enterprise and Dell Technologies are positioning themselves at the center of this server expansion, with both vendors reporting record backlogs tied to AI-accelerated compute orders. In its fiscal Q2 2026 earnings call, HPE disclosed that its AI server revenue had surpassed $10 billion in trailing twelve-month bookings, a figure that underscores how quickly GPU-equipped rack systems are displacing traditional general-purpose servers in data center refresh cycles. Dell Technologies similarly reported that its AI-optimized PowerEdge portfolio accounted for the majority of its infrastructure revenue growth in the first half of 2026, driven by hyperscaler orders for Nvidia GB200 NVL72 systems. Supermicro has carved a niche by offering liquid-cooled server configurations that reduce power consumption by up to 40% compared with air-cooled equivalents, a critical advantage for operators building out capacity for video encoding and AI inference workloads at scale.

The competitive dynamics among server vendors are being shaped by cloud provider capital expenditure commitments and the rise of custom silicon. Nokia and AWS recently demonstrated how cloud-hosted network functions can reduce infrastructure costs for operators, a model that streaming platforms are increasingly adopting for their own CDN and transcoding layers. Oracle and IBM have both expanded their bare-metal and GPU-as-a-service offerings to capture workloads that hyperscalers do not serve, while Huawei continues to grow its server footprint in Asia-Pacific markets despite ongoing export restrictions. Lenovo has focused on edge server deployments for low-latency video processing, targeting media companies that need compute closer to end users. The common thread is that every major vendor is now competing on AI workload readiness rather than raw unit volume, which compresses margins on traditional servers while commanding premium pricing for accelerated systems.

Technical benchmarks from independent testing confirm that the server market's growth is being driven by fundamentally different workload profiles than previous cycles. Ericsson launched its AI in RAN commercial software subscription in June 2026, claiming up to 20% higher downlink throughput across more than 15 live deployments, illustrating how AI inference workloads are now consuming server capacity across telecom and media infrastructure simultaneously. For streaming specifically, the shift toward GPU-accelerated encoding (using Nvidia A100 and H100 class processors) means that a single rack can now handle workloads that previously required three to four times the physical footprint. Fujitsu has reported that its PRIMERGY servers with integrated AI accelerators are being deployed by Japanese broadcasters for real-time 8K transcoding, while Cisco Systems is integrating its UCS platform with Nvidia DGX systems to serve enterprise video analytics use cases. The net effect is that the $471.9 billion projection reflects not just more servers but a fundamental change in what those servers do and how much value each unit generates.