Artificial intelligence (AI) will play a far-reaching role in accelerating the transition towards net-zero economies across the Nordic Region and in Europe, according to an analytic report from the Stockholm-headquartered SEB Bank.
Its role, according to the report, will be to support the sustainability transition processes of long-term structural change, towards more robust and continuous business, economic and societal systems.
Predictive analysis on AI forms part of SEB Bank’s The green bond report, which anticipates a dramatic rise in the technology’s star within manufacturing, economic, finance and environmental domains once governments pursue strategies to decouple emission levels from gross domestic product (GDP) and living standards.
The report found that legislative action by governments worldwide will lead to a sharp uptick in global capital investments in AI over the next 10 years, a development certain to drive the clean energy transition, while targeting the elimination of carbon dioxide (CO2) emissions by 2050. It also identifies AI as a key driver to enable the achievement, over time, of a more broadly sustainable production model for the global economy.
Report findings come at a time when Nordic banks and industrial groups, including Topdanmark and Valmet, scale-up investments to reduce their CO2 footprints, through projects that both embrace AI and expand machine learning processes in their business and manufacturing operations.
The advances in AI can have a profound impact on the transition to a clean energy world, said Thomas Thygesen, the head of strategy and sustainability in SEB Equity Research.
“The impact will eventually open the door for a circular production model,” he said. “Although a peak in worldwide emissions appears to be close, the current level of global investment in the clean energy transition still falls far short of what is required to eliminate emissions by 2050. Governments in Western economies appear to be politically constrained right now, so we need to find new drivers. AI can be one such driver.”
Input into SEB’s report comes from the Washington DC-based Institute of International Finance (IIF), a coalition of interest groups from within the global financial services industry that represents actors engaged in asset management, insurance, stock exchanges, commercial and investment banks, asset managers, insurance, sovereign wealth funds, central banks, hedge funds and development banks.
The disruptive nature of AI has the potential to precipitate a paradigm shift from ownership to usership of physical goods and products, the SEB report pre-warns. The primary focus in this regard is AI’s role as a facilitator of change to drive energy transition. In particular, the report recognises the need for a strategic re-think about how datacentres can both support AI and bolster demand for reliable power and water infrastructure.
Consuming approximately 2% of all energy generated in the world at present, datacentres will remain a fundamental component of energy generation and efficiency, said Christopher Flensborg, the director of climate and sustainable finance at SEB.
“We need to reach efficiencies that exceed this consumption rate through solutions like optimised supply chains, operational excellence, smart cities, intelligent transport systems, and advanced grid management. While datacentres have the potential to meet and exceed these efficiency goals, their success will heavily depend on the location, reliability and sustainability of the supporting infrastructure,” Flensborg said.
In the context of its game-changing promise, the SEB report described AI as an “emerging powerful tool” with the potential to drive transformation in gearing up sustainable fiscal management, while offering financial institutions new ways to both navigate complex challenges and bolster decarbonisation efforts across multiple sectors.
Specifically, the latent possibilities of AI are recognised as having the capability to deliver solutions to boost analysis of large quantities of data and improve the accuracy of climate impact and other sustainability metrics. The untapped potential of AI, the SEB report highlighted, can be viewed as a future tool to enable improved risk management and greater cost-efficiencies across industries; advances that can help bolster economic growth and minimise environmental impact.
The report envisages a steady roll-out of AI-led innovations and a deeper self-interest on the part of governments and economic blocs to regulate certain aspects of the technology as more advances in AI are unleashed. AI is expected to become a more dynamic driver for systemic transformation in key areas such as autonomous vehicles, remanufacturing, humanoid robots, and novel renewable materials.
Across these areas, the report observes, AI has the potential to serve as a catalyst to provoke a paradigm shift towards an economic model based on access and circularity. Additionally, unleashed AI advances will likely have the capability to alter the inherent rigidness of linear production and economic models, many resistant to change, by offering superior solutions than current and traditional unit-economics models.
The march of AI as a transformation tool has strengthened significantly across the Nordic region since 2020, when industrial companies and leading financial services groups started to actively make significant capital investments in the technology.
Topdanmark
Denmark
“From skiing holiday insurance coverage to medical assistance, the Globus chatbox adds a lot of value to customer support. Although it does everything but answer the telephone, we are looking for a solution here too. We are working on plugging Globus in to Google Assistant to deliver a service that will enable Globus to actually answer the telephone,” Svendsen said.
In
Finland
“The partnership paves the way for a future where AI-driven solutions transform our industrial processes and unlock new opportunities for growth,” Erikson said.
The solution provided by Etteplan integrates AI-assisted process optimisation, enabling the handling of large volumes of data to facilitate a much steeper, evolving learning curve.
