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

2019). It is overestimated as there still is no well-defined way of creating a human-like machine. On the other hand, AI is underestimated because it is far more powerful and widespread in companies than most people might think. This is where leadership comes in. III. C onnecting P eople and T echnology: how to C reate A P erfect M atch a) Central Elements for a Beneficial Relationship According to the evolution of AI, we are still in the first stage, which is called narrow AI (Hildesheim & Michelsen, 2019). Here, AI is able to perform rather precise tasks independently. The second level is the general AI, a level at which machines become similar to humans. In the distant future, there could also be a third type, called super AI, far beyond human intelligence. To date, only narrow AI has penetrated the realm of the economy. However, despite its widespread use in many industries, AI is yet to be extensively disseminated. Even narrow AI has not been realized completely. This means that the application of AI involves working, experimenting with its possibilities, trying out different algorithms, testing its capabilities, and constantly monitoring and improving results. AI is the opposite of a product that works ‘out of box’ (Boobier, 2018). At present, there are therefore two ways of applying AI. First, AI helps to be efficient in intellectually simple tasks with a high degree of repetition, such as in a smart factory where product assembly is done individually but in an identical framework. Second, AI can be used to analyze huge blocks of unstructured data (Hildesheim & Michelsen, 2019). For companies, both types of AI application mean that they are facing great challenges. Leadership must not only decide which path to take, but also prepare the implementation. In recent research on AI and leadership, this period of implementation has received the greatest attention. Considering that business leaders should anticipate future developments and then motivate their employees to share this vision, the implementation of AI is an outstanding aspect of leadership (Daugherty & Wilson, 2018). The statements of this perspective on how the relationship between leadership and AI should be shaped are explained in chapter 3.2. However, this research perspective reflects little on the change that AI will bring about in the way companies are managed, once AI technology is introduced. Nevertheless, this second perspective is very important because it takes into account the consequences that AI will have for leadership in the future. This is particularly important because AI will intervene more deeply in the way companies are run than any technology has done before (Hildesheim & Michelsen, 2019). Research on this second perspective is discussed in chapter 3.3. b) Leadership during the Implementation of AI Since AI will change organizations profoundly, many employees and managers are reluctant to get involved in AI implementation. Simultaneously, AI is revolutionizing products, business models and markets – not to mention the efficiency gain it is causing. Finding a balance between opportunity and risk, meeting challenges and uniting all employees behind a comprehensive vision is the primary task of company leaders (Cox, 2018). The focus of leadership is on building trust (Williams, 2005). This is the critical value when organizations undergo profound changes, especially due to the fact that people trust people rather than machines or non-transparent processes (Daugherty & Wilson, 2018). Out of many similar approaches, an example from research on the implementation of AI in companies will be presented. It shows eight factors that determine success (Bughin et al., 2017; Wodecki, 2019). These factors not only capture characteristics that leaders should have, but also underline the importance of corporate culture. Leaders should possess: − better analytical skills than their competitors, − a board of directors with strong determination and vision for leadership during change, − a concept for the implementation of change, − a business strategy that is intertwined with a technological strategy. Another four factors relate to the will and ability of a corporate culture to: − cooperate freely and efficiently within the organization, − accept new ideas and adaptation processes, − change products and services for the sake of technological innovation, − pursue comprehensive data governance. By emphasizing the importance of corporate culture in the implementation of AI and the change it brings about, the factors also emphasize the importance of leadership. They also show that leaders direct organizations by instilling common goals, norms and values. In doing so, leaders need to overcome barriers that might hinder the implementation of AI. These include a possible lack of talents, fears among employees, lack of skills, competing projects outside AI, and lack of business cases for AI (Wodecki, 2019). The success factors and challenges identified in the studies regarding the implementation of AI in companies are very similar to those explained (Ashri, 2020; Boobier, 2018; Bootle, 2019; Bughin et al., 2017; Burgess, 2018; Buxmann & Schmidt, 2019; Canals & Heukamp, 2020; Castrounis, 2019; Daugherty & Wilson, 2018; Davenport, 2018; Gentsch, 2018; Gläß, 2018a, 2018b; Iansiti & Lakhani, 2020; Mohanty & Vyas, 2018; Skilton & Hovsepian, 2018; West, 2018; Wodecki, 2019). The Impact of AI on Leadership: New Strategies for a Human - Machine - Cooperation 3 Global Journal of Management and Business Research Volume XXII Issue VIII Version I Year 2022 ( ) A © 2022 Global Journals