According to a McKinsey survey, generative artificial intelligence (AI) tools — AI systems that can create new content such as images, videos or text — are rapidly gaining popularity in businesses. Many organisations are already using these tools in their operations and even top executives are personally using them for work.
This increased interest in AI has led to a surge in investment in AI technologies. However, the survey also highlights the need for organisations to address the risks associated with using generative AI.
AI is rapidly transforming various industries. However, its growth comes at a cost: energy consumption. The enormous computational power required for AI applications can strain energy grids. This energy consumption is primarily due to the data centres that house the servers and hardware necessary for AI operations.
Consequently, AI is playing a multifaceted role in the energy transition, both accelerating and hindering progress towards a more sustainable future. One notable effect is its influence on the closure of coal-fired power plants.
The development of AI raises questions about the ethical implications of energy consumption, such as the environmental impact of increased energy use, its potential for worsening energy inequality and its effect on society.
The increasing demand for electricity to power AI applications is exerting pressure on energy transition goals, contributing to the delay in shutting down coal-fired power plants globally. This complex relationship can be understood through several key factors.
AI applications, particularly machine learning and deep learning, require vast computational power, often provided by energy-intensive data centres. A large data centre can consume as much electricity as a small city. With the numerous data centres opening in SA we must understand their energy supply and demand patterns.
How often do you command Siri, ask TikTok to auto-create your content, or interact with a company chatbot to answer a query? The International Energy Agency states that a single Google search uses 0.3 watt-hours of electricity, while a ChatGPT query uses about 10 times that amount. This might not seem like a lot, but given that there are billions of searches every day, this could soon be a monumental amount.
Developing specialised hardware such as graphics and tensor processing units to accelerate AI computations has also increased energy consumption.
Globally, the economic benefits of AI, such as increased productivity and innovation, are starting to outweigh the short-term costs of increased energy consumption. This has led governments and businesses to prioritise AI development over immediate energy transition goals.
The AI industry creates jobs and stimulates economic growth, making it difficult for policymakers to justify rapid transitions away from coal-fired power plants.
Coal-fired power plants also provide baseload power, ensuring a stable and reliable energy supply desperately needed by data centres. As AI-powered technologies become more critical to economic activity, there may be a reluctance to transition away from coal-fired power until alternative sources can provide the same level of reliability and at a reasonable cost.
Despite these challenges, AI presents an opportunity to accelerate the energy transition because it can enhance the efficiency and integration of renewable energy sources such as solar and wind power. By predicting energy demand and optimising grid operations, AI can assist with ensuring a stable and reliable energy supply.
AI-powered smart grids enable real-time monitoring and control of energy flow, reducing energy losses and improving grid resilience. AI can identify opportunities for energy savings in buildings, industries and transportation, leading to reduced energy consumption and emissions. AI is also being used to develop new materials for solar cells, batteries and other energy storage technologies, improving their performance and reducing costs.
While AI offers potential for addressing climate change through energy efficiency and renewable energy integration, its growing energy demands are starting to hinder progress and shift transition goals. Balancing the economic benefits of AI with the need to transition away from fossil fuels is becoming a critical challenge for policymakers and industry leaders.
• Mashele, an energy economist, is a member of the board of the National Transmission Company of SA.
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