Applicable Knowledge for Sustainability. The Status of Artificial Intelligence in Industrial Production and the Impact of Future Sustainability

Climate change requires society to focus more strongly on sustainability. This requires an adjustment both on the demand side and on the supply side. Consumers must be given incentives to optimise their consumption according to sustainability aspects. In the supply of capital goods and consumer goods, firms must do their part to ensure that environmental savings are made possible and cost-efficiency. However, there must be doubts that a more resource-efficient production technology leads to the desired environmental effects. Policymakers ignore the Jevon’s paradox. The Jevon’s paradox states that an improved technology that leads to resource savings disproportionately increases the intensity of use. In absolute terms, there is a higher consumption of resources after the technology is introduced. This effect is currently ignored, for example, by all forecasts on demand for lithium for electromobility. Regardless of this, it is fundamentally better to optimise the technologies. However, this raises the question of whether the Jevon’s paradox cannot be undermined by artificial intelligence. Artificial intelligence applied to production promises the possibility to replace partial optimisations with total optimisations. By pursuing an absolute maximum (maximum maximorum), the intensity of use is limited. Therefore, this chapter is concerned with understanding the primary effects of artificial intelligence in production and highlighting the potential effects on sustainability. Purpose:Increasing the sustainability in industrial production is getting more and more important. Furthermore, the technology of artificial intelligence is getting more and more important as well. For this reason, it is time to understand how artificial intelligence and sustainability are linked with one another in the context of production. Need for the study:This chapter aims to deliver a solid argumentation regarding the prospects and the relevance of the usage of artificial intelligence in the context of production. Moreover, it specifically aims to show how artificial intelligence affects the sustainability of production. Method:Literature analysis. Findings:The findings are that artificial intelligence does enforce cooperative action within the industry via the effects on productivity variables, transaction costs, and production elasticities. Furthermore, the Jevon’s paradox does not seem to apply to artificial intelligence. Therefore, it is suggested that more empirical research has to focus on this topic. Practical Implications:This chapter highlights the importance of artificial intelligence for the topic of sustainability.