Artificial Intelligence and Circular Economy: What Is New for Business Model Innovation?

Economic literature has described business models as the rationale for how an organization creates, delivers, and captures value; however, today, much of the research is based on linear “take-make-dispose” models rather than circular models oriented toward a more sustainable and regenerative economic system. When circular economy principles are integrated or translated into circular business model strategies, creating and capturing value steers society’s economy and resource management towards slower, more closed material and energy use cycles, leading to higher productivity. Moving from linearity to circularity involves innovation, and artificial intelligence (AI) has emerged as a significant transformative force. Empirical research suggests that companies that place sustainability issues high on the corporate agenda or strategy are also investing in the development of AI capabilities to enable circular business models (CBM), focusing on value creation through the application of solutions that reduce, reuse, and recycle material and energy resources, extend the use phase or intensify it, and even replace products with services and software solutions. Examples of how AI could help create circular business models include dynamic pricing (reducing the price of food as it approaches its expiry date to reduce food waste), matching algorithms (applicable to sharing or second-hand platforms to efficiently connect people with the things they want, from clothing to flats), or on predictive demands (applicable to reverse logistics to glass or medicine recycling). This contribution analyses how AI facilitates circular business model innovation following a prospective approach, which implies that rather than focusing on presenting a detailed review of the existing literature, it focuses more on linking relevant concepts as a way to gather valuable insights on how firms can leverage AI to advance circularity.