Technology holds the key to a less resource-intensive economy

The transition to a more sustainable economy hinges on further decoupling economic growth from resource consumption. We are buoyed by the potential for innovative technology, including applications of artificial intelligence (AI), to catalyse this transformation.

Insatiable demand for AI places strain on energy and water resources, but these challenges can be managed – and, in many cases, already are. More fundamentally, the digitalisation of processes, efficient cloud computing and advanced semiconductors can combine to radically reduce the resource intensity of the global economy. We believe companies at the vanguard of innovation in these areas can present compelling long-term investment opportunities.

Managing the environment impacts of technology

Data centres accounted for 1.5% of global electricity consumption in 2024 and are forecast to consume twice as much by 2030.¹ Some estimates are higher, based on projections of exponential power demand growth associated with the training of large-scale ‘frontier’ AI models.²

Irrespective, the direction of travel looks clear. Capital expenditure on data centres is expected to rise two-fifths in 2025 to US$475bn, led by the ‘hyperscale’ cloud computing operators.³ Meanwhile, demand for AI services is soaring: 71% of companies surveyed by McKinsey in 2024 reported using generative AI, up from 33% in 2023.⁴

Accelerating adoption of AI and the expansion of supporting infrastructure creates environmental impacts that must be managed, though.

The proliferation of AI-focused data centres – each of which typically consumes as much electricity as 100,000 homes – places pressure on local electricity grids.⁵ In Ireland, strains have led to a de facto moratorium on new data centres in the Dublin area until 2028. Servers’ cooling needs meanwhile mean that a hyperscale data centre can directly use around 2.5bn litres of water each year, equivalent to the consumption of about 80,000 people.⁶

Ultimately, managing costs and ensuring security of supply will drive the adoption of resource-efficient solutions by data centre operators. Water-saving technologies, from water recycling solutions to closed-loop liquid cooling systems, are well-established and are being adopted by the likes of Microsoft to reduce water-related risks.⁷ Meanwhile, technology companies are the largest buyers of renewable electricity sold under long-term power purchase agreements (PPAs).⁸

Source: Impax analysis based on data from IEA, April 2025; Goldman Sachs, May 2024; and Alvarez & Marsal, November 2024. Data centre workload data for 2024 is estimated. Data centre workload is the computing, storage, memory and network resources required to undertake computational tasks or processes.

Innovative technologies driving resource efficiency

We identify three notable ways in which the technology sector is shaping the AI-era economy in a more resource-efficient fashion, creating opportunities for investors focused on the transition to a more sustainable economy.

First, more efficient cloud computing. Best-in-class data centres are up to 40% more energy efficient than average data centres, due to their scale, use of advanced chips and efficient management. By aggregating demand from various end users, excess capacity can be minimised. Electricity use per terabyte of installed data storage has fallen by more than 90% since 2010 as a result of storage-drive density.⁹

The expansion of digital infrastructure supports opportunities for the likes of Eaton, a US-listed power management company. Its digital solutions enable advanced monitoring and control of electricity use across various settings, including data centres, enhancing operational efficiency and reducing downtime.

Second, increasingly advanced semiconductors. The energy efficiency of leading AI computing chips has historically improved by 40% a year.¹⁰ Underpinning the extraordinary complexity of ‘leading-edge’ chips – which can limit the power needed to train and run increasingly powerful AI models – are sophisticated designs developed using electronic design automation software from the likes of US-listed Synopsys.

Customised application-specific integrated circuits (ASICs) chips can deliver superior performance and workload efficiency in specific tasks, reducing energy usage and cost further. Among ASICs designers focused on custom solutions for enabling more efficient AI model training and inference is Marvell Technology.

Third, the digitalisation of processes. In the ‘digital factory’, every machine can be connected to cloud-based software solutions. As part of predictive maintenance, real-time performance data can be captured and analysed to identify issues before they shut down production lines, reducing downtime. AI can amplify potential efficiency gains: McKinsey estimates that up to US$2.1tn in economic value could be added by AI in factory automation.¹¹

Emerson, a US-listed designer and maker of automation products and software, is among the leading enablers of industrial digitalisation. The company works with manufacturers to improve operational energy efficiency. Its predictive maintenance AI tool has reduced plant maintenance spending by up to 10%.¹²

Cutting through market hype to identify long-term opportunities

While a short-term market correction would not come as a surprise after recent share price gains, the almost-infinite potential applications of AI give us conviction that this is a durable, multi-decade trend that will fuel demand growth for innovative technologies.

The environmental markets opportunity set has continually evolved over time. The short-term challenges posed by AI are real, but it has vast potential to play a catalytic role in solving resource-related challenges and so in decoupling economic growth from resource consumption. For this reason, we believe that investors in environmental markets should pay attention to companies enabling advances in AI.

The advent of the AI era has ushered in new challenges that only grow with rising adoption. Correspondingly though, the opportunity set for solutions that address the resource intensity of AI – in the content of limited global resources and rising global temperatures – is rapidly expanding. The opportunity set for companies that harness the potential of AI to address the greatest environmental challenges is much greater still.

¹ IEA, April 2025: Energy and AI
² Electric Power Research Institute, August 2025: Scaling Intelligence: The Exponential Growth of AI’s Power Needs
³ Gartner data, cited by the Financial Times, 30 July 2025: Inside the relentless race for AI capacity
⁴ McKinsey, March 2025: The state of AI: How organizations are rewiring to capture value
⁵ IEA, April 2025: Energy and AI
⁶ Impax analysis, based on figures from World Economic Forum, November 2024: Why circular water solutions are key to sustainable data centres
⁷ Microsoft, December 2024: Sustainable by design: Next-generation datacenters consume zero water for cooling
⁸ Moore, M., 3 March 2025: Big businesses step up to buy energy from new wind and solar farms. Financial Times
⁹ Masenet et al, 2020: Recalibrating global data center energy-use estimates. Science. Impax estimates for the period 2019 to 2022, extrapolated from 2010 to 2018 data
¹⁰ Epoch AI, October 2024: Leading ML hardware becomes 40% more energy-efficient each year
¹¹ McKinsey, 2023: The economic potential of generative AI: The next productivity frontier
¹² Aspentech, 2020: Global Pulp and Paper Company Improves Production, Cuts Maintenance Costs

References to specific securities are for illustrative purposes only and should not be considered as a recommendation to buy or sell. Nothing presented herein is intended to constitute investment advice and no investment decision should be made solely based on this information. Nothing presented should be construed as a recommendation to purchase or sell a particular type of security or follow any investment technique or strategy. Information presented herein reflects Impax Asset Management’s views at a particular time. Such views are subject to change at any point and Impax Asset Management shall not be obligated to provide any notice. Any forward-looking statements or forecasts are based on assumptions and actual results are expected to vary. While Impax Asset Management has used reasonable efforts to obtain information from reliable sources, we make no representations or warranties as to the accuracy, reliability or completeness of third-party information presented herein. No guarantee of investment performance is being provided and no inference to the contrary should be made.