Global Journal of Management and Business Research, A: Administration and Management, Volume 22 Issue 8

Any company going through a period of major change must be supported by convincing leadership, whose task it is to provide employees with security and the confidence to master the transformation process. Leadership must embrace the organization and its members, allowing them to express their needs and motivating them to create a positive vision of an uncertain future. Nevertheless, there are two reasons why the factors and challenges outlined above do not reflect the full range of disturbances and transformations that AI is likely to cause. Firstly, the circumstances associated with the implementation of AI are not different from the challenges related to any change process in the VUCA world. If AI were just another digital invention, this would not be a problem, but it is estimated that the power of AI will change businesses more profoundly than any other technology before. This profundity seems to have no equivalent in the theories of those who analyze the relationship between AI and leadership as an implementation problem of change management. This leads to the second reason why this perspective may not be convincing: it does not mention the power of AI over companies and enterprises. It does not reflect on AI as a possible team member. It does not mention the people, needed to set up, control and monitor AI software. It also fails to mention the various ethical and epistemological dilemmas that AI could pose to executives who are confronted with an opaque yet supposedly omniscient entity called AI. A deeper look at studies promoted by this second perspective will show whether any of these problems are addressed and, if so, what answers are given as to how AI can be thoroughly linked to leadership. c) AI Guiding Leadership While there are numerous studies that deal with the role of leadership in the implementation of AI, what is lacking are ideas about how leadership should change thereafter. This could be due to the fact that the implementation process is what every company is facing today, while the existence of a full-fledged AI is not yet in sight. However, AI is being developed very rapidly, and in other academic fields such as political economy and social sciences the consequences of the widespread use of AI are already being discussed. (LaGrandeur & Hughes, 2017). One of the crucial issues is, for example, where people will get their income from once most types of work have been assigned to machines (Santens, 2017). If these problems are already being considered, it is surprising not to find comprehensive studies on leadership changes once AI has to be led. What was said two years ago is still true: “There is a lack of research surrounding AI performance and human-led supervision” (Smith & Green, 2018, p. 86) which is needed in the next years to build a basis for the AI-induced change of leadership – the change of leadership culture will take its time. Nevertheless, here are the results of the few studies on the topic. The studies are interested in the success factors once AI starts guiding leadership. They argue that in order to come to terms with AI, leaders should consider machines in a way they consider followers and employees (Smith & Green, 2018). This is not to say that AI will soon receive general or even super-intelligence. Rather, it means that any entity that can act independently should be designed as an entity that is integrated into the organization and influenced by the corporate culture and its vision and values. In the case of AI, this includes not only the machine itself, but also the programmers who generate, test, train and monitor AI. (Smith & Green, 2018). Since leadership is about responsibility and accountability to everyone in a company, followers are equally accountable to everyone else, including managers. This must be extended to AI as soon as AI becomes autonomous (Saurav Kumar & Banerjee, 2018). But AI won’t be fully self-sufficient for a long time yet. Until then AI is not conceivable to be independent from programmers and IT engineers. They are part of the actual responsibility of the AI as a pseudo-member of a company. As long as the AI is not able to act completely autonomous, it should rather be understood as “an AI team or an AI/Human blended team” (Farrow, 2020, p. 10). In addition to the algorithm, these teams consist of programmers and post- programming controllers who manage the results and communicate them to those who need the information. Building a responsible relationship between managers and the AI team will require ethical supervision of these teams, including the algorithm itself. Programmers will need to be trained to comply with corporate guidelines, and AI results will need to be reviewed accordingly. In addition, communication standards must be established that can be used by executives, programmers, post-programming controllers, and machines. Due to the complexity of AI- related technology, this can be a particular challenge (Smith & Green, 2018). The realization of compliance standards between AI and humans, including communication and accountability, is a prerequisite for supervision procedures, which are also of particular importance because AI algorithms can make mistakes and cause unintended output. Of course, once AI has become emotionally and consciously intelligent, the more authoritative management attitudes towards algorithms would have to change towards the same management style with which each member of the organization is treated (Smith & Green, 2018). However, this aspect of leadership is too far in the future and therefore outside the scope of this paper. With a fully-fledged AI, leadership will experience a new diversity within the company, which will affect both the self-conception and the corporate image of the organization (Farrow, 2020). AI teams will The Impact of AI on Leadership: New Strategies for a Human - Machine - Cooperation 4 Global Journal of Management and Business Research Volume XXII Issue VIII Version I Year 2022 ( ) A © 2022 Global Journals