Dell’Oro Group has lowered its forecast for the telecom server market relative to its October 2022 report due to a few factors, including economic headwinds leading to reduced spending on mobile network infrastructure, challenges with the adoption of Open RAN and MEC, and a realization that it’s previous estimates for servers deployed for Operation Support Systems (OSS) and Business Support Systems (BSS) were overstated.
The new forecast anticipates the telecom server market to experience a 19% five-year CAGR, reaching $12.5 billion by 2027, slightly outpacing the overall data center growth rate of 15%. This adjustment comes as the firm has raised its projections for the data center market, driven by increased investments in accelerated computing for artificial intelligence (AI) applications.
Additional highlights from the November 2023 Telecom Server Forecast include:
- Centralized data center use cases, encompassing MCN and other internal IT workloads, are expected to grow at an 11% CAGR in revenue from 2022 to 2027, while edge data center cases, covering MEC, RAN, and Broadband Access, are anticipated to grow by 38% during the same period.
- Server revenue for edge data centers is expected to achieve a significantly higher growth rate compared to that of centralized data centers for telecom applications. The report anticipates changes in the ecosystem as telecom edge infrastructure adoption increases. Servers in centralized data centers for telecom applications will resemble those from traditional IT vendors like Dell, HPE, and Lenovo. In contrast, we anticipate a wider range of solutions from both server and telecom equipment vendors for edge data centers. These systems will be designed to handle harsh environmental conditions and security challenges in remote areas.
- The report anticipates the implementation of AI at both the network core and edge. At the core, AI engines could be utilized to automate real-time and near-real-time decision-making based on raw data from internet traffic and allocate network resources in real-time dynamically. At the edge, new AI use cases, primarily related to computer vision, that could enable applications such as industrial automation, autonomous driving, security, and various consumer services.
