Artificial intelligence – The environment’s ally

In the first of a two-part series, George Crowdy, Senior Fund Manager at Royal London Asset Management, discusses how we are in the midst of a monumental transition: AI’s prowess is being used to address the major issues that have hindered our planet for decades. As semiconductor technology continues to squeeze more "power per watt," is the environmental cost of AI likely to be outweighed by the "green dividend" it pays back to earth?

From predicting extreme weather to optimising energy use, AI is tackling various environmental challenges. But behind AI’s eco-heroics lies a concern: AI craves a lot of energy. So, is AI an environmental boon or a burden? The answer is a bit of both – but there’s plenty of reason for optimism.

AI grappling climate change issues

AI’s ability to process vast amounts of data makes it a powerful tool to help solve complex environmental problems. Take climate modelling, for example. Traditional climate forecasts required supercomputers churning through equations for days; now AI-driven models can forecast weather faster and potentially more accurately by learning patterns from decades of climate data. The UK’s weather service and tech companies are testing AI systems that produce rapid, high-resolution predictions of storms and heatwaves – a potential gamechanger for disaster preparedness. AI’s pattern-spotting skills are also saving energy: Google has been able to achieve more than six times more computing power per unit of energy versus five years ago through various efficiency measures [1] .

In wildlife conservation, AI is an impressive forest guardian. Autonomous drones and acoustic sensors can listen for chainsaws in protected rainforests, instantly alerting rangers to illegal logging. In Africa, camera traps armed with AI software distinguish endangered animals from poachers, enabling quicker interventions to protect species. Smart agriculture has also seen success: Farmers now deploy AI-powered apps and sensors to monitor soil moisture and pest outbreaks in real time. This means using less water, fewer chemicals, and boosting crop yields through precision farming.

Even the electric power grid is getting an AI upgrade. In renewable energy, unpredictable sun and wind pose a challenge. AI systems can now balance energy supply and demand by predicting output from solar panels and wind turbines, helping utilities store energy when it is plentiful and distribute it efficiently when it is needed. By some estimates, smarter grids could deliver double-digit percentage energy waste reduction, highlighting what a greener future might look like.

The invisible footprint of AI

No technology is perfect and AI’s own environmental impact is a real consideration. Those algorithms run on physical hardware – thousands of servers humming away in data centres worldwide, consuming electricity and generating heat. Training a single advanced AI model involves immense computing power.

Data centres often rely on energy-intensive air conditioning and vast amounts of water for cooling. Collectively, all data centres according to the International Energy Agency (IEA) – including those for AI – consume over 1% of global electricity and emit roughly 0.5% of worldwide greenhouse gases [2].

Greener computing

The good news is that tech companies and scientists are acutely aware of this challenge – and they’re innovating at breakneck speed to make AI hardware more energy-efficient. One big trend is specialised semiconductor chips designed just for AI tasks. Unlike general-purpose computer processors, these chips can perform the necessary calculations with far less waste. Each new generation of chip – now built with transistors just a few billionths of a metre wide – typically packs more computing punch per watt. There are even experimental analogue and photonic chips that process data using electrical impulses or light instead of traditional transistors, promising leaps in efficiency.

Simultaneously, engineers are reimagining how big data centres get cooled and powered. Smarter cooling systems, often themselves guided by AI, dynamically adjust cooling loads and even use outside air or liquid cooling to curb power use. Companies are also investing in renewable energy and planning new data centres near wind and solar farms to ensure the juice powering our AI helpers is as clean as possible.

Can AI solve its own carbon footprint?

Ultimately, making AI environmentally friendly is about balance and ingenuity. If we do it right, AI stands to save far more emissions than it produces. According to the IEA, by 2035, AI-driven improvements in energy, transport, and agriculture could help slash global carbon pollution by billions of tonnes – potentially dwarfing the extra emissions from data centres themselves [3]. In other words, if AI’s superpower is solving complex problems, one of the biggest problems it may solve is its own carbon footprint.

How can investors benefit?

We have always homed in on identifying the most exciting long-term investment themes and then finding the lowest-risk and predictable ways of benefitting from them. On this basis, we have identified attractive investment opportunities in semiconductors; this sector is the backbone of all digitalisation and in the enterprise software space which is characterised by very high recurring revenues. We have also identified investment opportunities in companies exposed to the data centre build out, which is where the lines between our ‘atoms’ and ‘bytes’ approach start to blur.

We believe that AI is undergoing a multi-decade investment boom and presents a wide range of investment opportunities for our sustainable fund range. As with all new trends or technological developments, there will be winners and losers, making a targeted approach essential. 

[1] Source: https://sustainabilitymag.com/news/how-is-google-balancing-ai-demand-with-sustainability.

[2] Source: https://www.carbonbrief.org/ai-five-charts-that-put-data-centre-energy-use-and-emissions-into-context.

[3] Source: https://www.iea.org/reports/energy-and-ai/ai-and-climate-change.

Past performance is not a guide to future performance. The value of investments and the income from them may go down as well as up and is not guaranteed. Capital at risk. Investors may not get back the amount invested. The views expressed are those of the speaker at the date of publication unless otherwise indicated, which are subject to change, and is not investment advice.