雲端服務供應商容量預測市場數據概覽：2026 年第一季

本報告分析了雲端服務供應商的容量，並按營運商、地區、工作負載類型和其他細分市場提供了全球資料中心容量趨勢和預測，以及按營運商細分市場的詳細分析。

實際優勢：

• 了解營運容量、可用容量和內部容量隨時間變化的趨勢，並自信地制定容量策略。
• 透過清楚了解工作負載成長模式和臨界點，優化 AI 基礎設施投資。
• 對營運商細分市場（超大規模雲端、新雲端和主權雲）進行基準測試，以指導合作夥伴關係和競爭定位。
• 預測將影響部署時間表的區域趨勢和電力相關限制。
• 辨識新興的以 AI 為中心和主權雲端驅動的基礎設施市場中的策略機會。

關鍵問題解答：

• 到 2035 年，哪個業者細分市場將引領容量成長？
• 超大規模雲端、新型態雲和主權雲的區域發展趨勢有何不同？
• 網格存取和授權瓶頸將在哪些方面影響擴充？
• 不同類型的業者將採取哪些不同的容量預留策略？
• 人工智慧工作負載何時會在全球和區域層面超越傳統工作負載？

研究亮點：

• 2025年至2035年全球資料中心容量按營運商、地區和工作負載類型細分的詳細分析：在役容量、可用容量和內部容量
• 按營運商細分的全面分析：一級和二級超大規模雲端服務商、新型雲端供應商和主權雲
• 對成長軌跡和臨界點的詳細研究（包括人工智慧工作負載何時超越傳統工作負載）

目錄

本產品建議與以下相關報告搭配閱讀： "雲端服務供應商容量預測" MD-CSPC-101

主要發現

最新資訊

研究方法

主要預測

Actionable Benefits:

• Plan capacity strategies with confidence by understanding how active, available, and provisioned capacity evolve over time.
• Align Artificial Intelligence (AI) infrastructure investments with clear visibility into workload growth patterns and inflection points.
• Benchmark operator segments (hyperscalers, neoclouds, sovereign clouds) to guide partnership and competitive positioning.
• Anticipate regional dynamics and power-related constraints that will shape deployment timelines.
• Identify strategic opportunities in emerging AI-centric and sovereignty-driven infrastructure markets.

Critical Questions Answered:

• Which operator segments will lead capacity growth through 2035?
• How do regional trajectories differ for hyperscalers, neoclouds, and sovereign clouds?
• Where will grid access and permitting bottlenecks impact expansion?
• How does headroom strategy vary across operator types?
• When will AI workloads overtake legacy workloads globally and regionally?

Research Highlights:

• A detailed breakdown of global data center capacity states-active, available, and under-the-roof by operator, region, and type of workload, from 2025 to 2035.
• Comprehensive analysis of operator segments: Tier One and Tier Two hyperscalers, neocloud providers, and sovereign clouds.
• Detailed research into growth trajectories and inflection points-including when AI workloads will overtake legacy workloads.

Who Should Read This?

• Cloud and data center strategy leaders: To optimize capacity planning and investment roadmaps.
• Enterprise Chief Technology Officers (CTOs)/Chief Information Officers (CIOs) and AI leaders: to align AI deployment strategies with infrastructure readiness.
• Infrastructure developers and ecosystem partners: to anticipate regional build-out and power constraints.
• Government and public sector planners: to shape sovereignty programs and national AI strategies.

TABLE OF CONTENTS

This product is meant to be read in conjunction with Cloud Service Provider Capacity Forecast MD-CSPC-101

Key Findings

Whats New

Methodology

Significant Forecasts