The energy and cleantech sector is among the top industries in which workers worldwide have received AI training, according to a report from human resources giant Adecco.
Adecco tracked the attitudes of global workers towards AI, delving into their comfort with the technology, whether and how it assisted workers in their daily tasks, and determining worker perspectives on other workplace issues, in its “Working through Change: Adapting to an AI-Driven World of Work.”
The energy and cleantech energy led the pack of industries, which also included manufacturing and logistics, transportation, and financial services, when it came to the mean average in minutes of daily time saved due to AI technologies.
Respondents in the energy and cleantech group saved an average of 75 minutes per day, while manufacturing and logistics reported saving 63 minutes a day due to AI, while aerospace and defense came in last at 52 minutes daily.
However, when it came to being able to use the time saved by AI on more creative tasks, energy and cleantech workers came near the bottom of the pack. Only 23% of workers in this category answered positively, while 33% of technology workers – the sector which led in this category – said they were able to devote more time to creative tasks after using AI.
As for any negative impacts of AI, only 12% of workers in the energy and cleantech sector responded that AI has made them lose a job, equal to the number of workers in the technology field who said the same. Only 7% of workers in life sciences and health care said that AI was responsible for a job loss, while 21% in the transportation sector said that a job loss could be attributed to AI.
Investments in AI applied to the cleantech space have ballooned, according to the “Cleaning Up with AI” report jointly released this month by Cleantech Group and CleanAI. Investments to apply AI solutions to the sector accounted for 12% of all investments and deals in the last 6 years, amounting to US$28.5 billion.
On a global scale, early-stage cleantech firms garnered an estimated US$7 billion in the 2018-2023 period, while late-stage cleantech firms attracted an estimated US$21.5 billion in the same period.
A majority of these funds (70%) have been raised in Seed and Series A funding rounds.
However, to double this growth, another US$138 billion will be needed for further investment in the next six years, the report said. Researchers behind the report estimate that capital invested in early-stage cleantech startups will reach US$22 billion in the 2024-2029 period, while investment in more advanced cleantech is expected to collect approximately US$116 billion.
Growing uses for AI in energy and cleantech work
Cleantech stretches across industries and sectors, and AI has already had a demonstrable impact in the agriculture and food, energy and power, material and chemicals, resources and environment, and transportation and logistics sectors.
In all sectors, the main uses of AI have assisted operators to assist in resource allocation, forecasting, optimizing processes, and measuring outcomes. For agriculture, Stacked Farm has used AI to control its indoor farms, while in energy, Nuru uses the technology for microgrid control. Environmental consultancies ClimateAI and electrical grid consultancy Rhizome use AI for climate modelling.
On forecasting, AI is used by Birds.ai to perform predictive analytics and maintenance for energy firms, EV charging firm Electric Era uses AI to optimize the grid and its EV charging stations.
Niqo helps agricultural enterprises optimize their applications of agrochemicals via AI, while Liminal uses the technology to perform battery ultrasound scanning. Smart Steel uses AI to optimize steel-making processes, while transportation logistics company Fast Trek employs the technology in optimizing routes.
On the measurement front, Imubit uses AI to measure and optimize chemical process refining, while Emitwise, a carbon management software firm, uses the technology to track carbon footprints. Notraffic, a mobility platform aiming to digitize transport, employs AI to manage and analysis traffic patterns.
Cleantech also a major contributor to Canadian GDP
In 2022, environmental and cleantech industries contributed 3.5% to the Canadian gross domestic product, generating C$80 billion that year. Canadian exports in this sector amounted to C$20.9 billion, or 2.2% of all Canadian exports.
Export Development Canada, a government entity devoted to strengthening Canada’s goods and services exports, has committed C$10 billion until 2025 to assist Canadian cleantech companies with their export objectives. By December 2023, EDC said it had exceeded its target of providing more than C$12 billion in financing and insurance services.
Future challenges for AI and cleantech
The success of the widespread implementation of AI into cleantech services depends on developing a workforce which is comfortable in further optimizing AI and understanding how the technology can be best deployed, Innovation Consulting Group said.
Energy and money need to be poured into both finding the right people with the right expertise, they noted, as well as ensuring AI has the correct infrastructure to be tested properly.
Solutions will also need to be found to minimize AI’s tremendous energy and water use, the EDC’s senior economist Prerna Sharma said in the report.
There’s no question that AI can help reduce emissions and improve sustainability, the EDC said, as AI can help lower emissions from 2.6 to 5.3 gigatonnes of greenhouse gas emissions by 2030.
However, AI – particularly generative AI – comes with a tremendous environmental cost at the moment.
“Training a single model, for example, uses more electricity than 120 U.S. homes consume in an entire year, or emit as many emissions as 110 U.S. cars emit in an entire year,” the EDC said in the report.
Water use of AI generative systems is similarly worrying, consuming between 1.8 and 2.7 litres of water for each kilowatt hour of energy expended, the Organisation of Economic Cooperation and Development (OECD) found.
But there are ways to improve AI’s environmental toll, he says, pointing to advanced cooling technologies, direct-to-chip cooling and implementing systems to recycle water and minimize freshwater demand.
On the energy side, energy-hungry AI uses could fuel the development of small modular reactors (SMRs). According to the Nuclear Energy Institute, American nuclear companies are expected to double their production in the next 30 years, with the majority of this new energy coming from SMRs.
In Canada, an increased use of SMRs could save 41 megatonnes of emissions between 2030 and 2050, according to the Canadian Energy Regulator, when comparing energy use based on unabated natural gas generation.
