The International Chamber of Shipping (ICS) explores, as part of their Leadership Insights newsletter, the subject of how AI’s rapid adoption comes with a steep energy cost.
According to ICS, popular large language models like ChatGPT are thought to consume roughly 2.9 watt-hours each use— almost ten times more than a standard Google search. As AI becomes more integral to global strategies, its energy demands will soar. By 2027, its energy consumption could match that of entire countries, challenging industries, including shipping, to think hard about AI’s role in sustainability objectives.
AI’s double-edged sword
Data centres are the backbone of AI operations, hosting the computational resources to process massive datasets. These centres consume enormous amounts of energy. In 2020, global data centres consumed about 200 terawatt-hours (TWh) of electricity, accounting for about 1% of the world’s total energy use—a figure expected to rise as AI adoption accelerates, ICS notes.
Training models like ChatGPT have been estimated to consume as much energy as driving a car to the moon and back. The technology behind such models is increasing in size and energy consumption by 750 times every two years. At this rate, we might use all the energy on the planet to build chatbots within a decade.
… Professor Thomas Nowotny, Head of the Sussex AI Research Group at the University of Sussex, told ICS Leadership Insights
Nowotny explores alternatives inspired by the human brain, which operates on about 20 watts of power. He envisions a future where AI systems utilise ‘neuromorphic’ computing, achieving low-power, sustainable AI. However, he cautions that its current pace of adoption has reached a critical point, and that energy infrastructure cannot keep up with demand. “The free lunch of AI is over”, he stressed, adding: “Companies need to avoid getting locked into solutions that may not be optimal in the long run.”
As explained by ICS, for shipowners this could have a significant impact on Scope 3 emissions, those indirect greenhouse gas emissions that are incurred elsewhere in the value chain. When any maritime business uses AI-powered services provided by cloud providers or third-party data centres, the emissions from the energy used to power them become part of their Scope 3, whether they like it or not.
According to the “Beyond the horizon: Opportunities and obstacles in the maritime AI boom” report, AI solutions for shipping continue to grow. In the last year, the industry has seen a wave of new AI technologies launched to improve energy efficiency, cut emissions and boost safety. The market is now worth a staggering US $4.13 billion, according to Thetius data, but in order to make the most of this growing market, shipping stakeholders must understand when, where, and why to in vest in AI technologies.
Mitigating AI’s energy footprint.
The challenge lies in balancing AI’s energy demands with the broader sustainability benefits it generates, ICS highlights. In order to feel the benefits of a sustainable AI strategy in environmental social governance, companies must be careful when selecting their data centre partners, ensuring they are equally committed. Major tech companies like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud are all investing heavily in renewable energy at their data centres and Google has publicly committed to net-zero carbon emissions across all of its business and value chain by 2030.
Among its many projects, Maersk Innovation Center has developed AI-based solutions such as digital twins and computer vision to enhance visibility and optimise drayage movements.
Erez Agmoni, Global Head of Innovation for Logistics and Services at Maersk, told ICS Leadership Insights that maritime leaders need to start with clear problem definitions when adopting AI and warns against them jumping on the bandwagon without fully understanding the environmental implications.
You should always start with ‘what problem are we trying to solve here?’ and whether AI will solve it for you. If what you’re looking at is going to solve it great, run a proof of concept test on a small scale and see if you like it, then expand further but don’t just be following trends and buzzwords out there.
… said Erez Agmoni, adding that many of the latest AI developments won’t immediately add value, and businesses must work hard to understand how to shape technology to meet specific challenges.
Balancing innovation with sustainability
As AI’s popularity grows, maritime businesses must collaborate closely with data centre partners to balance their drive for innovation with sustainability, ICS highlights.
Ravindra Rapaka, Director of AI and Product Manager at Aquasight, a US-based technology firm specialising in enhancing water systems, sums it up. He says a truly green AI is not here yet, but companies should enshrine sustainability in any longterm AI strategy. As he told ICS Leadership Insights: “Although the transition from classic AI to Green AI is a new topic, it’s both on time and important, especially for global logistics providers. In the short term, demand for mainstream AI will remain strong because of its entrenched nature, but demand for Green AI will gain because of increasing awareness of the environmental impact and because it’ll be the next big thing for organisations keen to address sustainability.”
