Merging two revolutions: A human-artificial intelligence method to study how sustainability and Industry 4.0 are intertwined

Industry 4.0 is an important contributor to industrial innovation and sustainability. Nevertheless, few studies empirically analyse how it acts as a binding force of both business practices. This study examines 1501 sustainability reports using a mixed human-artificial intelligence method based on Python's text mining libraries. This method takes advantage of AI's capabilities to extract information from large samples of data and of human critical thinking to find patterns in those data. Specifically, the method is used to evaluate the adoption of Industry 4.0 technologies, analyse how they are deployed worldwide, and investigate their sustainability outcomes. In terms of overall frequency, robots and cybersecurity are the most often reported technologies. Broken down by the firm's region, Asian firms have the highest rate of adoption, while African firms are lagging. Regarding the themes, Industry 4.0 is mainly adopted to improve production processes and customer experience. A small percentage of firms, particularly in Europe and North America, utilize Industry 4.0 to reduce the environmental footprint of their operations. Furthermore, results indicate that Industry 4.0 and sustainability are following two routes. Some firms have massively adopted Industry 4.0 to increase operational efficiency and reaped environmental gains as an indirect consequence of improved operations. Others have chosen to balance the adoption of technologies aimed to increase productivity with innovations whose explicit aim is the reduction of their operations' environmental footprint, such as additive manufacturing. Eastern firms tend to follow the first route while western firms the second. African and South American firms are still at a very early stage in their Industry 4.0 and sustainability journey. At the global level, Industry 4.0 is still far from being utilized as a catalyst to develop sustainability-driven business models.