The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/1355-2554.htm Next-generation business models Next- generation for artificial intelligence start-ups business models for AI in the healthcare industry Ignat Kulkov Abo Akademi University, Turku, Finland and Cambridge Judge Business School, University of Cambridge, Cambridge, UK Received 27 April 2021 Revised 9 July 2021 29 September 2021 Abstract Accepted 4 October 2021 Purpose - Value creation based on artificial intelligence (Al) can significantly change global healthcare. Diagnostics, therapy and drug discovery start-ups are some key forces behind this change. This article aims to study the process of start-ups' value creation within healthcare. Design/methodology/approach - A multiple case study method and a business model design approach were used to study nine European start-ups developing Al healthcare solutions. Obtained information was performed using within and cross-case analysis. Findings - Three unique design elements were established, with 16 unique frames and three unifying design themes based on business models for AI healthcare start-ups. Originality/value - Our in-depth framework focuses on the features of Al start-up business models in the healthcare industry. We contribute to the business model and business model innovation by systematically analyzing value creation, how it is delivered to customers, and communication with market participants, as well as design themes that combine start-ups and categorize them by specialization. Keywords Artificial intelligence, Healthcare, Value creation, Business model design Paper type Research paper 1. Introduction Many researchers consider artificial intelligence (AD) to be a key technology in the new industrial revolution; it can change interaction between business participants and society as a whole (Brynjolfsson and Mcafee, 2017; Buch et al, 2018; Fleming, 2018). The use of AI capabilities has already been felt by industries such as design, manufacturing, logistics and others that actively respond to changes and improvements (Gero and Sudweeks, 2012; Chien et al., 2020; Klumpp, 2018). According to early research, Al capabilities are actively used in healthcare, particularly in diagnostics, therapy, healthcare management and drug development (Ivan and Velicanu, 2015; Fleming, 2018; Hamet and Tremblay, 2017). Compared to other industries, healthcare is more conservative, where the cost of error would be high. Therefore, most healthcare innovations are carefully monitored by registering and approving authorities, as well as by physicians who use new opportunities. Nevertheless, new technologies, including Al, are the future, and maybe the present in healthcare Jiang et al., 2017; Kulkov, 2021). The capabilities of Al are assumed to contribute to increasing access to quality healthcare, reducing errors and increasing medical personnel training (Mak and Pichika, 2019; Miller and Brown, 2018). The classic definition of AI was offered by Mccarthy (1959), namely, AI is a type of machine that is inherent in intelligent behavior. In other words, AI is the science of how to teach computers to do something that a person can do more successfully at the moment Ignat Kulkov. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create International Journal of derivative works of this article (for both commercial and non-commercial purposes), subject to full Entrepreneurial Behavior & Research attribution to the original publication and authors. The full terms of this licence may be seen at http:/ Emerald Publishing Limited 1356-2564 creativecommons.org/licences/by/4.0/legalcode DO 101 1081JEBR-04-2121-CAM