As World Environment Day approaches on 5th June, it’s a timely reminder to pause and reflect – not just on how we treat our planet, but on the environmental implications of the technologies we use every day. One of the most powerful and fast-evolving of these is AI.
From streamlining operations to predicting customer behaviour, AI is revolutionising industries at breakneck speed. But what’s the hidden environmental cost of asking ChatGPT a question, or using AI to power smart recommendations or autonomous systems? And more importantly – can AI also be part of the solution?
At the heart of AI’s environmental impact is its hunger for energy. In order to train, run, and store AI models including ChatGPT, a high level of energy consumption is required. The data centres powering these tools often rely on fossil fuels and also consume substantial quantities of fresh water to prevent servers from overheating. This raises concerns regarding water shortages and carbon emissions.
As AI continues to be implemented across sectors to enhance efficiency and innovation, so does its resource demand. As a result, this puts greater pressure on sustainability targets.
It’s no secret AI is transforming market research – helping us gather data faster, uncover insights more accurately, and make smarter decisions. Always-on platforms, predictive models, and AI-driven surveys have driven impressive efficiencies. But every completed survey, chatbot interaction, or refreshed dashboard adds to the digital carbon footprint.
As insight professionals, we have a responsibility to balance innovation with environmental awareness. We must ask ourselves: what is the true cost of speed and scale in research? And how can we build more sustainable systems while continuing to innovate?
More consumers are evaluating a brand’s environmental policies and efforts when choosing a product or a service. As researchers, we play a crucial role in shaping how brands understand, measure, and respond to these expectations. And we’re also being asked to answer some big questions:
To answer these, we need to deliver robust insight and ensure that the methods and technologies we use align with the sustainability goals we’re helping brands pursue.
AI is here to stay and there is opportunity to move towards ‘sustainable AI’ as a compromise between encouraging the adoption of AI technology whilst also ensuring that the carbon footprint of AI technology is minimised.
Major tech firms like Google, Microsoft, and Amazon have already pledged to run their data centres on 100% renewable energy by 2030. New cooling methods – like free air and dry cooling – also reduce water consumption. And advances in “ultra-low-power” AI systems offer promising paths to reduce the energy demands of AI models.
This also opens up exciting possibilities for market research teams:
It’s not all doom and gloom. AI has potential to be utilised as a key tool to promote sustainability in new and innovative methods, so much so that the UK government is investing nearly £4 million into AI solutions to assist in reducing carbon emissions to help achieve the goal of net zero emissions by 2050. For example:
These examples highlight how AI can enable smarter, greener systems across industries.
This World Environment Day, we have a chance to reflect on the future of both technology and the planet.
As researchers, we sit at the intersection of innovation and insight. While AI opens up exciting new possibilities, it also places great responsibility on us to ensure our tools, methods, and mindsets support a sustainable future.
Rather than seeing AI and sustainability as opposing forces, we should view them as two sides of the same challenge and the same opportunity.
Lucy Barlow
Insight Executive
Reading Time: < 1 minute
