AI Data Centres Face Power Challenges by 2027, Says Gartner Report

The rapid growth of artificial intelligence (AI) and generative AI (GenAI) technologies is expected to strain global power supplies. According to a report by Gartner Inc., 40% of AI data centres may encounter operational issues by 2027 due to electricity shortages. The energy demand for these data centres is projected to increase by 160% over the next two years, with power usage rising from 261 terawatt-hours (TWh) in 2024 to 500 TWh by 2027, more than double the 2023 levels.

This surge is driven by the need for larger data centres to support the computing power required for training and deploying large language models (LLMs) that are essential for GenAI applications. However, utility providers are struggling to expand their capacity quickly enough, potentially leading to energy shortfalls that could disrupt data centre operations by 2026.

Challenges and Recommendations

Bob Johnson, VP Analyst at Gartner, highlighted the planning of new larger data centres to manage the vast data needed for LLMs. He noted that short-term power shortages are likely to persist as new power infrastructure takes years to develop, which won't solve current issues.

The anticipated power shortages are expected to increase operational costs for data centres. As electricity prices rise, organisations using AI technologies will face higher expenses. Gartner advises businesses to prepare by negotiating long-term contracts for stable power rates and adjusting project budgets to account for higher energy costs.

Additionally, sustainability goals may be affected. Some power suppliers are extending the use of fossil fuel plants, which could increase CO2 emissions and hinder zero-carbon objectives. Renewable energy sources like wind and solar are insufficient for the 24/7 power needs of data centres without alternative solutions like advanced battery storage or nuclear power.

Mitigation Strategies

To address these challenges, Gartner recommends organisations assess the risks of power shortages on their AI operations and consider alternative strategies. This includes using smaller AI models, edge computing, and more energy-efficient technologies. Businesses should also revise their sustainability goals and explore innovative energy solutions, such as sodium-ion batteries or small nuclear reactors, to support long-term operations.