emerging
AI Data Center Footprint Growth
Data center electricity demand and GHG emissions are rising due to increasing AI adoption, necessitating sustainable solutions.
Timeframe
near-term
Impact areas
Detailed Analysis
The increasing adoption of AI, particularly in hyperscale data centers, is driving a significant increase in electricity demand and associated greenhouse gas emissions. Deloitte's modeling framework projects this growth under different adoption scenarios, highlighting the need for energy efficiency measures and sustainable energy sourcing. The study emphasizes the importance of understanding the evolving energy consumption characteristics of data centers, including server utilization, facility efficiency, and the shift towards more power-intensive hardware like GPUs.
Context Signals
IDC estimates that 10% of global data center electricity demand can be attributed to AI in 2023.
Projected server CAGR of 28% (Baseline) and 44% (High Adoption) between 2023 and 2028.
Sigmoid functions used to model long-term AI technology adoption.
Edge
Potential for accelerated growth beyond initial projections due to unforeseen breakthroughs in AI technology.
Increased focus on edge computing and distributed AI processing could mitigate the centralized data center footprint.
Opportunities for new business models focused on sustainable data center solutions and energy optimization.
