AI as a key technology for sustainable economic activity

Artificial Intelligence (AI) can make an important contribution to a sustainable orientation of the economy and society. The use of the technology opens up new business models for companies that support the success of the energy transition, low-emission mobility or environmentally friendly agriculture, for example. However, the energy consumption of the AI systems themselves is often high. A current white paper by Plattform Lernende Systeme shows how sustainable business models can be created with the help of AI and identifies design options that can reduce the ecological footprint of AI systems. In addition to technological measures, the experts recommend a broad exchange of data between companies, research and public authorities.

Download the white paper (Executive Summary)

Low-emission waste incineration, more efficient use of fertilisers or early detection of health risks in the workplace - Artificial Intelligence can help companies and institutions to act in an ecologically compatible, socially just and at the same time economically successful way. From huge amounts of data, AI systems gain new insights into how companies can make their processes more efficient and resource-conserving and reduce emissions. In this way, products, services and business models are created that make an effective contribution to sustainable development. "Artificial Intelligence is an essential building block for making our society more sustainable. However, AI must also be designed to be sustainable in itself, for example in terms of its own energy requirements," says Oliver Zielinski, head of the Competence Centre AI for Environment and Sustainability (DFKI4planet) and co-author of the white paper.

AI can also promote a sustainable economy outside the workplace. With the help of the technology, data from companies - for example on greenhouse gas emissions or occupational health and safety - can be analysed and the sustainability of the companies evaluated, for example to offer investors a decision-making aid. One possibility for this is an open platform on which companies can make their sustainability data securely accessible and standards for data collection can be disclosed, according to the experts in the white paper "Artificial Intelligence for Sustainable Business Models". Equally necessary is the exchange of data from research, business and authorities for the training of AI applications.

"Digitisation and AI applications based on it have great potential to support economic, social and ecological sustainability goals. The spectrum of applications is wide and includes, for example, better control and use of resources, improvement of working conditions, but also the development and provision of sustainable products and services," says Susanne Boll, Professor of Media Informatics at the University of Oldenburg and head of the Business Model Innovations working group of Plattform Lernende Systeme. "AI systems have a high energy consumption, especially when training large neural networks. The benefit must therefore also always be in proportion to the computing power. Therefore, innovations for sustainable AI must be considered from the very beginning - from the cost-efficient training process of AI models to the use of waste heat from data centres."

The white paper cites the rapidly increasing computing power required to train ever larger AI models as the main reason for the high resource consumption. The CO2 footprint of a search engine training can currently reach about the size of a long-haul flight. In addition, AI applications in use can cause problematic feedback effects, for example if an AI system is used more due to its lower energy consumption and the energy consumption increases in total. Despite the promising potentials, it is important to always consider these so-called rebound effects as well as the necessary energy demand of AI technologies, according to the authors. In individual cases, the decision for operational applications in terms of sustainability could also mean not using AI.

"The wheel does not have to be reinvented over and over again. AI models that have proven themselves can be made available to other AI developers on marketplaces; the effort for training is then eliminated or at least significantly reduced," says Markus Schnell, Senior Director at Infineon and member of the Business Model Innovations working group.

Furthermore, the authors recommend researching new economical learning methods and model calculations, using more efficient hardware for AI applications, as well as a sustainability label with which AI applications with low resource consumption are marked and thus promoted.

About the white paper

The white paper Artificial Intelligence for Sustainable Business Models was written by experts from the Business Model Innovations working group of Plattform Lernende Systeme.

On the website of Plattform Lernende Systeme, co-author Markus Schnell explains in a short interview how AI can contribute to a sustainable development. Further expert statements and detailed interviews as well as the AI map with more than 160 AI applications from Germany that support sustainable development can also be found there.

Further information:

Linda Treugut / Birgit Obermeier
Press and Public Relations

Lernende Systeme – Germany's Platform for Artificial Intelligence
Managing Office | c/o acatech
Karolinenplatz 4 | 80333 Munich

T.: +49 89/52 03 09-54 /-51
M.: +49 172/144 58-47 /-39

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