Artificial intelligence (AI) can help businesses become more sustainable, but the benefits must be measured against the environmental costs of the technology.
This was one of the messages that came through loud and clear from the AI Summit London held in the capital last week.
Sustainability experts pointed out some of the ways that AI can be leveraged to help companies achieve their goals in this area.
The technology can capture, map and connect data sets that are currently separate, for example, to help businesses deliver decarbonisation and other initiatives.
AI can be used to accurately predict and manage the demand for energy in various parts of the business and supply chains, and also to pinpoint harmful emissions at specific sites.
Speakers also outlined how AI could help businesses to manage Scope 3 emissions by linking together different data sources.
These are greenhouse emissions that occur outside the company’s direct operations but that are still a result of their activities.
They can account for up to 90% of a company’s emissions but can be very difficult to track without AI, as data may be collected, stored and shared differently among different organisations.
AI is being used to repurpose materials in the HS2 project
Specific examples provided included AI being deployed within the HS2 project to work out new use cases for concrete and other materials being dug up.
AI-powered image recognition can also be used to analyse methane emissions from specific factories or other sites from satellite data and images much more quickly than without the technology.
AI has its own environmental impact, however, such as the power needed to train algorithms on huge data sets and subsequently run them.
Training the well-known GPT models, for example, used an equivalent of the energy needed to power every household in the UK for an hour.
It’s estimated that on the current trajectory, half of the world’s generated energy could be funnelled into AI use by 2040.
Companies can take a number of steps to mitigate this energy use, such as working with IT teams and suppliers throughout the chain to understand where data is stored and make this more sustainable.
The IT sector should start to address environmental impact at an earlier stage of an AI’s development, however, while regulatory intervention may also be needed.
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