Reducing the Environmental Impact of Artificial Intelligence (AI)

Businesses can reduce the environmental impact of AI by using energy-efficient model designs, sustainable architectures, and renewable energy sources to balance innovation with eco-conscious practices.

By adopting energy-efficient architectures, optimizing AI models for performance, and pushing for cloud providers to embrace renewable energy, businesses can help reduce the carbon footprint of their AI solutions.

Artificial intelligence is reshaping our world. Its transformative power fuels innovation across industries — delivering new value to organizations and consumers alike. As the proliferation of AI accelerates, people are starting to ask important questions: How does AI impact the environment? And furthermore, how do we keep pushing for progress without leaving a heavy carbon footprint on the planet?

AI’s Eco Impact

Artificial intelligence software runs in data centers that consume large amounts of energy and often cause significant carbon emissions. According to Bloomberg, there are more than 7,000 data centers worldwide. Collectively, they can consume as much power annually as the entire electricity production of Australia or Italy. The growing use of AI will further increase this already substantial energy consumption of data centers.

The use of AI can be separated into two main tasks: training and inferencing. During training, AI models learn from vast amounts of data that can take months depending on data complexity and volume. Once an AI model has been trained, it consumes energy each time it generates a new response or “inference.” The International Energy Agency (IEA) has reported a ChatGPT inquiry requires up to 10 times the electricity of a Google search to respond to a typical request. This energy consumption adds up and can quickly surpass the energy used for training.

The WEF estimates training comprises about 20% of an AI model’s overall energy use across its lifespan, while inferencing makes up the remaining 80%.[…]