Table of Contents
List of Figures
List of Abbreviations
1.1 Goals and Objectives
1.2 Research Question
2 Theoretical framework and literature review
2.1 Leadership and management
2.1.1 Conceptual framework
2.1.2 Development and current situation
2.1.3 Leadership objectives and issues in corporations
2.2 Artificial Intelligence
2.2.1 Conceptual framework
2.2.2 Development and current situation
2.2.3 Machine Learning and deep learning
2.2.4 Objectives of artificial intelligence in corporations
2.3 Technologies impact on corporate leadership
2.3.1 The influence of artificial intelligence in companies
2.3.2 The impact of artificial intelligence on corporate leadership
3 Empirical Research: Expert Interviews
3.1 Development of Interview Guidelines
3.2 Selection of different multinational Experts
3.3 Method of Analysis
3.4 Presentation of Results
3.5 Key Findings from Empirical Research
4.1 Analysis of the literature review and expert interviews
4.2 Limitations and Further Research
5 Conclusion and Practical Implications
List of Figures
Figure 1: AI Umbrella term
Figure 2: Development of interview guideline according to Kaiser
Figure 3: Influence of AI in company`s future
Figure 4: Current use of AI
Figure 5: Impact of AI on leadership style
Figure 6: Changing or supporting role of AI on leadership
List of Abbreviations
illustration not visible in this excerpt
Artificial intelligence is rapidly changing the world of work and, with it, the way leaders run companies and institutions. In recent years, more and more companies have implemented artificial intelligence (AI) in different areas. The question that arises and what the following work is aimed at is the question of what influence an implementation of AI has on leadership and what this means for the entire management. The resulting research gap is examined, analysed and evaluated through a systematic literature review of current scientific sources and through expert interviews with international executives.
The literature evaluation and the expert interviews led to the conclusion that many executives welcome the topic of AI and are open to a possible implementation in the corporate structure. However, it could also be analysed that some experts expect a certain change and shift in leadership style towards a more technical leadership style. The future, therefore, calls for leaders who are open to technical implementations such as AI but also leaders who simultaneously promote the uniquely human skills of employees and integrate AI into their leadership style.
Keywords: leadership, artificial intelligence, machine learning, deep learning management, executives, organisational change, corporate strategy
Leadership is a management topic that has been known for many decades and has been researched and analysed many times. In recent years, however, the term "leadership" has increasingly been associated with the strong and growing influence of "artificial intelligence". This leads to a generally increasing interest and raises the question to what extent these two topics fit together and how they can be combined (Cortellazzo et al., 2019). Especially in the last few years, the economy has never grown as fast as we can see in today's business world. Businesses must master themselves to keep up with the times in the rapidly growing economy but also be able to address the challenges and problems of day-to-day business. In these challenging times, it is more important than ever that leaders make the right decisions and are fully equipped to interact in the fast-growing and technical economy. Organisations must implement a strong leadership culture and prepare their leaders as much as possible to interact successfully in this world (Am et al., 2020).
Especially in the last few years, technology has developed rapidly, and the rise of AI has developed strongly, which brings with it completely new requirements for companies and leaders (Haenlein et al., 2019). Since the topic of AI has become so important in recent decades, the requirements and opportunities for managers and companies have also changed. Executives today must be able to deal with big numbers, data, infrastructure, results, facts, technical understanding and many other tools to lead a company into a successful future and remain competitive (Moldoveanu and Narayandas 2019; Iansiti and Lakhani, 2020). However, the influence of AI also offers various impacts and opportunities, such as increasing process efficiency, gaining insights through data processing, process transformation and operational performance in the company (Enholm et al., 2021). Besides that, AI can also have negative effects, such as biases, ethical and moral problems, and safety risks are unintended side effects (Russel and Norvig, 2021, p.1057; Iansiti and Lakhani, 2020). Weighing the pros and cons of using AI is one of the future challenges companies and leaders will face. Therefore, a detailed and clearly communicated strategy is needed to get the maximum benefit from it (Peifer et al., 2022).
The increasing influence of AI will change the world once and for all. The change will be more significant than most people realize today. AI will change the entire working environment, and companies are required to react to this and adapt to technical developments as best as they can (Marr, 2020, p. 9; Iansiti and Lakhani, 2020). However, leading organisations through these times of change require new managerial wisdom. In the future, managers will have to combine the topic of AI and, at the same time, implement good leadership in order to lead their employees successfully. For this type of managerial expertise, companies and their executives need to be broad in order to adapt to the rise of AI and to make themselves significantly more competitive (Iansiti and Lakhani, 2020).
1.1 Goals and Objectives
In the last recent years, the fast-growing development of artificial intelligence has led to significant attention. The topic of artificial intelligence is strongly associated with the field of management and corporate leadership. The state of research indicates that research in leadership and artificial intelligence has had to change steadily over the last few years and that there has been a substantial shift. Driving forces for this have been, for example, the rapidly growing and changing economy and digitalization. The Corona pandemic has recently also influenced how companies are managed and how they deal with technological and digital development. A commonality between leadership and artificial intelligence can be expected to increase in the future. In particular, it shows that traditional corporate leadership and its executives face new challenges when the question arises of whether to implement AI. The classical construct of leadership is faced with new and future challenges in connection with the rapidly growing development of artificial intelligence. Due to the increasing presence of both topics and the literature that follows a particular trend that tends to the commonality of artificial intelligence and leadership, little is known about the direct influence and impact on corporate leadership and their leaders. Since these research question and their effects and influence must be researched more closely, the motivation for this elaboration of the present bachelor thesis is directed to this topic.
1.2 Research Question
Corporate management ensures a company's management, and according to the literature, this will be challenged more than ever in the future by new developments such as artificial intelligence. However, the current movement in the research literature tends to say that artificial intelligence is essential for future companies and their leaders and that AI can contribute to improving corporate success. Despite the diverse literature on the subject and the challenging tasks of leaders in companies, the direct influence of artificial intelligence on corporate leadership and their leaders has been little researched. However, when leadership is repeatedly associated in the future with artificial intelligence, theresearch questionarises of what direct influence and impact artificial intelligence has on corporate leadership and its leaders in the first place.
Based on the general assumption in the research literature that if artificial intelligence is essential for future companies, their management and their leaders, it is hypothesised that AI will make a positive and significant contribution to the entire company, management and its executives. On the other hand, it can be assumed that managers will be open and optimistic about the subject of artificial intelligence. Accordingly, it is expected that the influence of artificial intelligence in companies will result in better corporate leadership and leadership capabilities.
Therefore, this thesis aims to close this gap and analyse whether the statements of the research literature correspond with the leader's views in practice, what direct influence artificial intelligence has on corporate leadership, and what insights can be derived from this. Furthermore, it is also a matter of evaluating these analysed connections with the help of empirical research. The intended result of the elaboration is that it leads to valuable recommendations for practice, which can be used for further research.
The research paper is divided into two main parts to achieve the above research objective. It is divided into a literature review in the first place and secondly by an empirical research method. In the beginning, a theoretical research follows, based on a structured and systematically relevant literature review of primary and secondary sources of English and German literature. Besides subject-related books, different online scientific databases were searched for relevant information. In all results, care was taken to ensure that the literature corresponds to current publication dates.
At the beginning of the work, the task consisted of examining various literature on corporate leadership and artificial intelligence in order to collect possible sources. This first step helped to get a rough overview of the two topics. In the next step of the literature research, the broad topic of Artificial Intelligence was examined in more detail. An attempt was made to collect different sources regarding a possible influence and connection to corporate leadership. After the literature research was completed, all results were categorized and combined. The basic structure and sub-headings were determined based on the sources and results.
In the following chapters, the elaborated results of the literature research are shown. The topic of leadership and management, beginning with (2.1), is explained in the basic concept and the development up to today's time in (2.1.1 and 2.1.2). In (2.1.3), the leadership objectives and issues in corporations will be explained. A short summary of this chapter is given in (2.1.4). The next chapter (2.2) is about Artificial Intelligence, where the conceptual framework (2.2.1), as well as the development and current situation (2.2.2), is shown. The further subitems are Machine Learning and Deep Learning in (2.2.3), and the objectives of artificial intelligence in companies will be presented in (2.2.4). A summary of this chapter is given in (2.2.5). The impact of technologies on corporate leadership (2.3) is the last chapter of the literature review. In (2.3.1), the direct influence of artificial intelligence in companies is explained, and the impact of artificial intelligence on corporate leadership will be presented in (2.3.2). A summary of this chapter is given in (2.3.3).
Chapter 3 uses the empirical research method of expert interviews. The decision was made to use an empirical research method based on the current developments in both areas. Conducting expert interviews has the advantage of generating additional data through empirical findings that support the research objectives and further supplement the literature research (Kaiser, 2021). The theoretical results of an interview with six experts were used as a basis for this. The experts are specifically selected based on their level of knowledge, position and influence in the company. Preference is given to interviewing experts in a company's direct management team. The expert interviews were conducted according to the current scientific methodology of qualitative empirical research, which is described in subsections (3.1 to 3.3). The following results of the empirical research method will be presented in (3.4), and the central findings are shown in detail in (3.5). In Chapter 4, all findings from the literature review and the expert interviews (4.1) are compared and analysed. The implications and results are presented in (4.2), and possible limitations and further research suggestions will be highlighted in (4.3). To conclude the thesis, a final conclusion based on the previous findings with practical implications is explained in chapter 5.
2 Theoretical framework and literature review
2.1 Leadership and management
2.1.1 Conceptual framework
Leadership and management is a widely discussed topic in the past and current literature. Many researchers agree on the importance and critical role of the concept in organisational success. However, they do not agree or settle on a single definition of the key terminologies. Hundreds of theoretical and empirical studies have been published by scholars and writers who attempted to define leadership. Richard Daft even quotes the famous statement from James McGregor Burns in his book:“Leadership is one of the most observed and least understood phenomena on earth"(Daft, 2018, p. 4; Burns, 1978). That occurs because leadership is such a complex construct in itself, making it very difficult to define.
Regarding the units of comprehensive leadership, Bennis (1989) describe leadership using the term beauty, noting that leadership is difficult to define but easy to recognise when you see a leader's beauty. Northouse (2022) additionally states that leadership is an interpersonal relationship that a leader develops with their followers in an organisation in order to develop an organisational culture that resonates and is recognised by everyone in the organisation. Leaders, therefore, have interpersonal knowledge, skills, motivation and attitudes to enter into a special relationship with followers and employees and to achieve a common goal.
From a different perspective, influence is always mentioned when discussing the terms leader and leadership. Leaders can be seen as inspiring individuals who lead and influence others emotionally and psychologically based on how they demonstrate their leadership qualities. This way of thinking has been adopted by other researchers as well, who agree that a leader is someone who must be able to influence an individual or group through action, motivation, and cognition alone which includes their beliefs, thoughts, and perceptions (Grunberg et al., 2018, p. 645-646). Daft similarly defines leadership as Grunberg did. Daft states that making use of influence to motivate individuals to achieve corporate goals is known as leadership. Leading entails developing a culture and values, conveying goals to employees throughout the company, and creating a desire to achieve and perform at a high level (Daft, 2021, p. 10). Based on the above definition of a leader, leadership can therefore be described as the ability to influence others through motivation, cognition and action. Referring to the contemporary definition of leadership as presented in the literature, a comprehensive definition of leadership can be explained as a psychosocial process involving interpersonal and group dynamics to affect all psychological aspects of others. Therefore, a successful leader is someone who leads the processes by playing a central role in adjusting goals, people and context (Grunberg et al., 2018, p. 645-646).
The area of management is another term that has remained ambiguous for years since its introduction. Like the above-mentioned topic of leadership, the understanding of management is similar because it is described in the literature in many different definitions. The authors Daft and Marcic (2019) write that the essence of management is to inspire and align the efforts of others to tackle varied and future challenges. Another essential element of management is acknowledging the significance and contribution of others. Mary Parker Follett, a management theorist from the early 1900s, defined management as the method of achieving goals by utilising the efforts of individuals (Arthur and Freeman, 1989). Additionally, Peter Drucker, a well-known management expert, has stated that the responsibilities of managers include setting the direction for their organisation, providing guidance, and determining the best way to utilise organisational resources in order to achieve objectives (Drucker, 1973). Daft provides this direction by defining four fundamental functions of management that have the overall aim of achieving organisational goals:
1)Planning(goal setting) involves setting targets for future organisational success, determining the necessary actions, and utilising resources to reach them. In simpler terms, managerial planning establishes the organisation's desired future position and the means to reach it.
2)Organising(task responsibility) encompasses assigning duties, passing tasks into different departments, delegating authority, and allocating resources throughout the company.
3)Leading(influence) is the act of utilising one's influence to motivate employees to achieve organisational objectives. It also encompasses creating a shared company culture and values, communicating those goals throughout the organisation and inspiring employees to perform at their best.
4)Controlling(monitoring) activities include monitoring employee actions, evaluating progress towards organisational objectives, and making necessary adjustments. The four fundamental management functions have the overall aim of achieving organisational goals (Daft, 2021, p. 8 ff.).
To achieve those organisational goals, it can be said that management is an essential ingredient to any leader's success in any company. Management can be seen as the cornerstone of any organisation, which is why there should be a perfect flow of information and support for the two components of an organisation. The role of management in an organisation is to facilitate the goals of an organisation and its connection to leadership. Management provides the structure and framework for leaders to utilise in order to achieve organisational success through effective leadership. On the other hand, leadership is the core ingredient of management and serves as the foundation for organisational success. In this regard, leadership provides the necessary motives to motivate people through a motivational approach to achieve organisational success. Management, on the other hand, provides leaders with resources, tools, money and commitment in order for them to succeed in their individual tasks (Sonmez et al., 2020). Therefore, the two topics of leadership and management go hand in hand; neither can leadership or management replace the other (Daft, 2018, p. 14).
2.1.2 Development and current situation
In the Harvard Business Review, author Nitin Nohria argues that leadership and management throughout history are primarily context-specific. In this case, the same manager or leader who was successful in one era might not be successful in another for various reasons (Nohria, 2022). The topic of leadership has been the focus of various studies for centuries.Modern leadership can be traced back to the teachings and principles of the Greek philosopher Plato. He argued that leaders are born into the Athenian ruling class to lead a highly educated class. In Plato's lifetime, leaders had to take personal responsibility for their actions and prioritize essential issues such as honesty and reasoning using philosophical perspectives. Plato clearly distinguished in his writings between governing by law and the art of governing by persuasion (Scott and Freeman, 2021). Between 1469 and 1527, however, Plato's views were further developed by other thinkers, most notably the Italian theorist and philosopher Machiavelli, who broadened the guide's scope. One of Machiavelli's famous books was "The Prince", which provides guidance on how leaders and managers of his day should act and behave. The book's primary outcome is that leaders should maintain their power by maintaining a healthy balance of fear and love. Machiavelli believed that leaders should be feared rather than loved, which explains why leaders of the 14th, 15th, 16th, 17th and 18th centuries were dictatorial and used military power to maintain their leadership positions. Roughly five hundred years after the publication of Machiavelli's book, his ideas about what leadership and management entail remain highly controversial to this day (Viroli, 2016).
Leadership theories in the 19th century
The understanding of leadership continued and developed over a century along the three primary levels of traits, behaviour and situation (Hofert, 2021, p. 51). As people's intellectual abilities improved in the 19th century, researchers sought to identify influential leaders' personalities and innate characteristics (Robbins et al., 2017). This identification led to the Great Man theory (1840) and the trait leadership theories (1930 - 1940) by Thomas Carlyle and Francis Galton (Rüzgar, 2019). In his works, Carlyle examined the characteristics of past great leaders, while Galton focused on the hereditary qualities of leadership. A notable outcome of Galton was that leadership skills were inherited rather than learned, implying that leaders are assumed to be natural-born leaders. The Great Man theory of inherited leadership traits was accepted for most of the 19th and 20th centuries. The trait theory created a new era of leadership in which leaders should not be given instructions to lead but should develop the traits needed to lead themselves (Kilanowski and Augustyniak, 2021). The sociologist Max Weber wrote that leadership cannot be learned. Weber also worked on the level of leadership characteristics and, in his theory, distinguished between three different types of leadership. The autocratic, charismatic and bureaucratic. The autocratic leader leads alone and claims his power, while the charismatic leader influences others through his personality. The bureaucratic leader provides clear rules and regulations (Weber, 1947). Weber, therefore, placed leadership in an organisational context for the first time. It is not the person alone but the situation and context that determines the behaviour, but the same leadership behaviour does not make sense in every situation (Hofert, 2021, p. 51). The representatives of the Great Man Theory had assumed that leadership could not be learned. Weber had not thought about learnability. For Weber, the decisive factor was that the person had to fit into the context (Hofert, 2021, p. 52). That raises now the question if the behaviour can change the situation? That is where Kurt Lewin and his theory come into place.
Leadership theories in the 20th century
As the scientific revolution took hold in the mid-20th century, there was a paradigm shift in leadership research regarding the results of the trait era, and the path of interest led in the direction of leadership behavioural theories (1940 - 1950) (Benmira and Agboola, 2021). The Iowa studies of Kurt Lewin, the pioneer of social psychology, mainly shaped leadership research in the late 1930s. In the study, Lewin examined the effect of different leadership styles on youth groups. Like Max Weber, he defined three leadership styles, except that these also affected the environment, and he used his studies as a basis (Hofert, 2021, p. 52). Lewin defined three leadership styles as autocratic, democratic and laissez-faire. A clear separation between superiors and employees defines the autocratic style. The manager has the authority to issue directives and decide on individual employees activities. The style is characterized by command, obedience and structure. In the democratic style, the focus is on the group of employees. The manager only discusses tasks and goals with the employees. The laissez-faire management style gives the employees all the freedom to make their own decisions, and the manager does not actively intervene (Lewin, 1975, Helmold, 2022, p. 19). Lewin also concluded from his Iowa studies that having any leadership was better than none. With his findings, Lewin offers a classification help but should not lead to dividing leadership behaviour into only three styles. Leadership is more complex, not one or the other, but one and the other (Hofert, 2021, p. 53). The following leadership theorists, Blake and Mouton, began to differentiate between task and employee orientation, with task orientation being close to the authoritarian style and employee orientation close to the cooperative style (Hofert, 2021, p. 53). Blake and Mouton developed this thought and theory in their leadership concept in the 1960s through their Managerial Grid. The two dimensions of task orientation and employee orientation are compared with each other, whereby these are documented with their different characteristics in a behaviour grid on two axes. One axis describes the effort of the employee (employee orientation), and the other axis shows the interest in the task (task orientation) itself (Blake and Mouton, 1964; Lippold, 2019, p. 13). In this model, a leader is no longer just one or the other there are different facets between employee and task orientation. A leadership style with a high degree of employee orientation and task orientation is considered ideal (Hofert, 2021, p. 53).
In the 1970s, Hersey and Blanchard developed the situational leadership theory in their famous book "Management of Organisational Behaviour". This theory includes refining previous thoughts and bringing people's individuality into play. In their theory, Hersey and Blanchard consider, for the first time, the employee to be led and not only the leader's characteristics. The outcome is that employees are diverse and therefore have to be managed and motivated differently. The theorists also stated that motivated and non-motivated employees must be treated differently (Hersey and Blanchard, 1972). The appropriate leadership style is determined based on the development status of the employee determined in this way. The maturity level of an employee is determined by the combination of willingness and ability (Helmold, 2022, p. 23). Four primary forms result from the expression:
1)Both motivated and competent employees can be given responsibility.
2)Employees who could be more motivated and competent need strong and authoritarian leadership.
3)Employees who are motivated but could be more competent need close supervision and an argumentative, explanatory leadership style.
4)Competent but unmotivated people need further assistance (Hofert, 2021, p. 53).
The effectiveness of the selected leadership style must be observed closely. If the task is handled very well, a style should be chosen for a similar task in the future that allows employees more participation and freedom. If the results are unsuccessful or insufficient, a withdrawal of participation and more control and instruction are considered sensible (Helmold, 2022, p. 24). However, the model also leads to one-sided thinking since motivation is thought of one-sidedly and does not consider that people can be motivated differently (Hofert, 2021, p. 54).
The research approach, which is also one of the property-oriented leadership theories, essentially distinguishes between two aspects of leadership, transactional and transformational. The transactional and transformational leadership theories dominated the next decades of scientific leadership theory (Lippold, 2019, p. 7). James Downton, an American sociologist, first described transactional leadership in 1973. It was then further developed into a model by James MacGregor Burns in 1978 (Helmold, 2022, p. 24,Burns, 1978). Transactional leadership emerged from the development of Peter Drucker's "Management by Objectives (MbO)" (Hofert, 2021, p. 54). Drucker developed the MbO concept in 1954 in his book "Practice of Management". It describes that employees and supervisors set specific goals together, which are then achieved by the employee within a specified period (Drucker, 1954). Transactional leadership is ultimately about an exchange relationship between managers and employees (Helmold, 2022, p. 25). Managers have specific goals that they pursue for themselves and the company. The manager's task is to clarify to employees what performance is expected of them and what incentives and rewards they will receive in return (Lippold, 2019, p. 7-8). The advantages of the theory are, for example, that goals can be implemented in the company and that goals and rules are structured. One of the most significant disadvantages of transactional leadership is that employees motivation is mainly extrinsic. Extrinsic motivation eventually reaches its limits quickly, and employee motivation is lacking despite the rewards (Helmold, 2022, p. 24).
The theory of transformational leadership has been increasingly studied in academia since the mid-1990s. The historian and political scientist James MacGregor Burns first distinguished between transformational and transactional leadership styles in his study of US presidents and their leadership styles. He found certain successful principles, such as being a role model for others or the ability to convey and create visions (Burns, 1978). The transformational leadership style evolved from the transactional leadership style (Hofert, 2021, p.55). In 1985, Bernard Bass applied the thoughts and insights of MacGregor Burns to leadership for the first time and extended the theory to transformational leadership (Bass, 1985). Unlike transactional leadership (extrinsic), transformational leadership aims at (intrinsic) motivation and promoting individual development (Hofert, 2021, p. 55). By communicating attractive visions, clear communication, leading by example and supporting individual employee development towards goal achievement, transformational managers seek to motivate their employees through such intrinsic leadership (Helmold, 2022, p. 25). The literature often compares transactional and transformational leadership. However, both leadership styles have in common that organisational goals can be achieved. The difference lies in the implementation of goal achievement by the manager. Transactional leadership is a factual and rational exchange process between leaders and employees, which, if successful, takes the form of reward or punishment. The transformational leadership style pursues the intention that the employees work towards the company and the manager and its goals out of inner solidarity instead of receiving external incentives such as salary or bonuses. Both transactional and transformational leadership can lead to the desired leadership success. Most of the time, not only one of the two leadership styles is used, but a combination of both. They can, therefore, also be seen as mutually complementary behavioural characteristics of a manager's leadership style (Helmold, 2022, p. 25). In the past, leadership was often about individuals, whether leadership theories were trait- or behaviour-based. Leadership was strictly related to positional power. The leadership style could often sanction, praise or even punish (Hofert, 2021, p. 58).
Leadership theories in the 21st century
As time progressed, leadership research continued to generate new styles and concepts. The term "new leadership" is used as an example to summarise new leadership approaches and concepts of our time (Lippold, 2019, p. 30). However, a clear definition of new leadership turns out to be complicated. The term is associated with various concepts related to the new and modern world of work. Terms that fall under this area are, for example, shared leadership, agile leadership or digital leadership (Helmold, 2022, p. 7). Shared leadership deals with the concept of how leadership in companies should be shared in order to optimize motivation and performance. In this concept, management is no longer exclusively determined by the supervisor (Lippold, 2019, p. 31). Agile leadership is the concept in which employees determine how they complete tasks and are thus involved in decisions. This concept breaks the classic hierarchical structures (Lippold, 2019, p. 33). Agile leaders are agile, ﬂexible and capable of transforming work environments. They strongly focus on teams. They pursue clear values and promote group self-direction through team development. In this way, they contribute to the adaptability and development of the entire company (Hofert, 2021, p. 95). Digital leadership is a leadership competence that addresses whether a person can act in an organized manner because such competencies are decisive for the performance of the individual and, ultimately, the whole company (Lippold, 2019, p. 38). The three leadership approaches are not mutually exclusive but complement each other in practice. Instead of delegating tasks to employees, they work independently. New leadership is aimed at flat hierarchies, and the traditional manager loses his status as a leader and is transformed into an accompanied coach. It can be stated that new leadership embodies an entirely modern way of managing employees (Helmold, 2022, p. 7).
2.1.3 Leadership objectives and issues in corporations
The topic of leadership, as already mentioned in 2.1.1, is a highly diverse and complex topic that, despite the many published research results, still needs to be fully understood and defined. A lack of understanding of the concept of leadership often begins with the definition itself. Bernard Bass states in his book:“There are as many definitions of leadership as there are those who have tried to define it”(Bass, 1990, p. 11). This statement is consistent with many other references that have attempted to define leadership in other ways. A similar statement is made by Daft, who says that leadership is highly complex and challenging to grasp and define because it is so complex (Daft, 2018, p. 4). The exact understanding of the pure concept of leadership remains a challenge for the leadership itself. However, it must also be mentioned that the definition is independent of whether a company is successful or not. There are more fundamental issues in today’s organisations that affect their operations than defining and understanding leadership itself (Deep Sharma et al., 2019). When it comes to leadership objectives, this is one of the most fundamental and also essential aspects of leadership itself. The definition of goal leadership is rarely discussed in the literature. However, Azad et al., (2017) showed that leadership goals determine the direction of leadership and the goal to be achieved in an organisation (Azad et al., 2017). Daft confirmed in his book that this type of quality leadership is one of the most important and essential factors for the stability of society, companies and organisations in general (Daft, 2018, p. 4). Since the beginning of leadership research, several different leadership goals have been discussed in the literature. According to Daft, the following goals that have the most impact on companies are, on the one hand, employee organisation but also working towards a specific goal, employee motivation, communication, and managing change within an organisational structure (Daft, 2018). It must be mentioned that employee organisation is fundamental to the performance and success of organisations and, as such, should form the core objective of organisational leadership. Therefore, a strong employee organisation ensures in the long term that performance, employee relations and the realisation of company goals are successfully implemented. Good employee organisation is best achieved by bringing together employees with different experiences and skills to achieve a clear goal (Avolio et al., 2009).
When it comes to achieving organisational goals, this is another important organisational leadership factor that leaders should strive for. Leadership must be the achievement of specific corporate goals. Achieving such corporate goals is essential for the basis of leadership. Leadership is the key to achieving organisational goals, and leaders must develop a clear plan to achieve those goals. Organisations with leaders who understand organisational values and goals are more likely to achieve organisational goals faster and more effectively (Gagné, 2018). The best way to achieve these goals is to motivate employees. Daft relates motivation to the forces that drive and excite a person. The motivation of employees, in particular, influences productivity, which is why it is part of a manager’s job to direct his employees motivation towards the company’s goals and visions. Various studies have shown the connection between high employee motivation and organisational performance resulting in profits. Daft also mentions a survey by the GALLUP organisation, which found out that customers are 70% more loyal to a highly motivated and high-performing workforce and that turnover, in turn, falls by 70% while profits increase at the same time by 40%. Managers must take the employees motivation as extremely important to satisfy their employees needs and simultaneously implement a high level of work performance. The reverse conclusion is that if managers do not motivate their employees, the company’s goals suffer significantly (Daft, 2018, p. 228 ff.). A big problem in companies is the way they communicate. In simple terms, communication is exchanging information between a sender and a receiver, for example, through a manager and his employees. The managers determine the communication climate of a company and thus have an immense influence on the employees. Successful leaders actively listen, ask questions, and even practice non-verbal communication, which is often overlooked. That is also confirmed by a study by the AMA-Enterprise, which shows that many managers do not invest any time or energy in the way how they communicate. As a result, the study reveals that nearly 40% of guided employees feel left out, misunderstood and even stated that they do not know what is happening in their organisation. Managers must, therefore, communicate to make the company’s visions clear and build certain values such as trust and manners to positively influence working relationships and communication (Daft, 2018, p. 262). It is the leader’s responsibility to ensure that organisations develop or change as necessary to respond to potential threats, opportunities or environmental changes (Daft, 2018, p. 464). Helmold defines change management as the sum of tasks, measures and activities that bring about a comprehensive, cross-departmental and far-reaching change in a company or organisation. Change management aims to achieve a favourable long-term position on the market and achieve a sustainable competitive advantage through the change to an innovative company. Of all the factors, the most important is the employees, who must be at the forefront of all approaches because the change depends on the active support of the employees (Helmold, 2022, p. 175). As such, leaders must intentionally lead and demonstrate the change clearly so that employees across the company see the change as positive and natural, requiring strong leaders who act as role models (Daft, 2018, p. 456).
One of the most famous concepts for implementing change comes from former Harvard professor John P. Kotter. Kotter (1996) developed the famous 8-step model for change management in his book “Leading Change”. The model consists of 8 interdependent steps that provide an approach to change. All eight steps must be gone through to guarantee the change. Below are the eight steps:
1) Developing a sense of urgency.
2) Building the guiding coalition.
3) Developing a vision for change.
4) Communicating the vision for change
5) Eliminating obstacles.
6) Creating short-term goals.
7) Consolidate successes and derive further changes.
8) Implement changes into the corporate culture.
Finally, the steps can be summarised into three broad phases: Creating a climate for change (1-3), engaging and empowering the organisation (4-6), and sustaining change (7-8). The model is very often used by many managers and well-known consultancies (Helmold, 2022, p. 181 ff.). However, the big problem for leaders is that change management is often not accepted. Leaders must expect resistance and rejection. It is, therefore, very important to find specific ways to enable employees to understand the process of change and to see that it is needed for the company’s success (Daft, 2018, p. 456).
At the moment, several new technological developments are emerging in the corporate world that likely will change the future course of companies. The development of artificial intelligence is one of the major topics and can potentially lead to future challenges. AI’s rising influence can reshape the entire business world and leaders and managers must implement new managerial wisdom to compete in the future (Iansiti and Lakhani, 2020).
McGregor Burns once said: “Leadershipis one of the most observed and least understood phenomena on earth”(Daft, 2018, p. 4; Burns, 1978). Although it is difficult to define leadership, it can be said that it is the ability to influence people through motivation and specific actions in order to achieve company goals. Another goal of management is to lead employees to become more efficient. This can be implemented if the leader provides clear employee organisation, communication, motivation and changes in the company. The topic of management can be understood as a goal-oriented strategy that uses specific resources, people and various concepts to effectively achieve organisational goals. Leadership research has developed various concepts over many decades. In practice, many leadership approaches build on each other and must be understood as such. A current example is "new leadership", in which modern leadership approaches are combined. This includes, for example, modern styles such as shared, agile and digital leadership. When it comes to leadership goals, they are an essential aspect of good leadership. According to Daft, the key goals for corporate success include the organisation of employees, the achievement of goals, motivation, communication and the management of change. The rapid changes in the economy and in particular the technological progress lead with their developments to new challenges for leaders and companies in the future. In particular, the development of artificial intelligence will bring new challenges and change the way companies are run. In order to remain competitive, managers must become aware of this and develop new management wisdom.
2.2 Artificial Intelligence
2.2.1 Conceptual framework
Since the beginning of the digital age, many revolutionary technological advances have been made. The rapid rise of artificial intelligence is one of the most concise and recent technological advances that is already gaining wider acceptance and use in various sectors of the economy, including healthcare, automobile, energy, agriculture, businesses, and many more. The rapidly growing and developing artificial intelligence is currently the strongest and fastest-growing sector of the current century (Caner and Bhatti, 2020). The definition of artificial intelligence can be defined in many different ways. Various attempts have been made to define artificial intelligence in terms of fidelity to human performance. In contrast, others have had a completely different definition preferring an abstract, more formal definition of artificial intelligence to put it under the term of rationality, which aims to do the right things (Russel and Norvig, 2021, p. 19). However, the concept is generally considered to be the science of programming machines that are able to think, display complex human-like behaviours and make decisions (Caner and Bhatti, 2020; Collins et al., 2021; Dick, 2019).
Based on a historical definition made by the well-known computer scientist and pioneer of AI, John McCarthy, he defined AI as the science of developing machines that behave as if they would have intelligence (Ertel, 2021, p. 1). Compared to that, Stuart Russel, a leading computer scientist and famous researcher in the field of AI, defines AI:"As the study of agents that receive percept from the environment and perform actions"(Russel and Norvig, 2021, p. 7). Russel and Norvig continues and explains that the "agents" are synonyms for specific individual actions and systems like "decision-making agents, or deep learning systems” (Russel and Norvig, 2021, p. 7 ff.).
In its simplest form, AI refers to the ability of computer systems or machines to develop intelligent behaviours that enable autonomous action and learning. The AI collects data to solve specific problems, directs calculation processes according to defined rules of action (algorithms), and then makes decisions or predicts specific results (Marr, 2020, p. 12). It can be said that AI is a set and sequence of capabilities that enable machines (computers) to make intelligent decisions. These capabilities are different from what traditional computer programming was because they were not designed for full automation. Instead, they are now designed to copy existing human capabilities and actions with greater efficiency, accuracy and speed and to improve them. Several issues have caused important decisions in this area. First, while earlier research focused on using artificial intelligence as a tool for human endeavour, recent developments and trends have shown an increasing shift towards using artificial intelligence as an autonomous agent capable of acting without necessarily requiring human input (Collins et al., 2021). However, it is also important to emphasize that artificial intelligence is not limited to specific applications but has been implemented into different technological systems and for different purposes. The applications are generally related to the increasing use of artificial intelligence in many big companies such as Google, Facebook, Microsoft and Amazon (Marr, 2020, p. 9 ff.). The strong influence of artificial intelligence is having a powerful impact on the innovations of our time, society as a whole and businesses in general (Iansiti and Lakhani, 2020). Marr additionally states in his book that Artificial intelligence will change the world once and for all. The change will be more profound than most people realize today. AI will expand and transform the work environment regardless of the profession, branch, or industry (Marr, 2020, p. 9; Fountaine et al., 2019, p. 4).
As much as artificial intelligence is a significant innovation in itself, it has fundamentally changed the innovation landscape. Implementing artificial intelligence has revolutionized so many different industries, sectors and entire organisations worldwide (Cockburn et al., 2018; Gentsch, 2019). However, artificial intelligence is not only an invention that improves efficiency, accuracy and decision-making in numerous fields, but it also opens a strong pathway for further innovation. The various innovations through artificial intelligence have contributed significantly to the recent technological advancements in the modern era (Cockburn et al., 2018). The impact of artificial intelligence on the innovation landscape can be significant. However, artificial intelligence must be continuously improved and researched to maximize its benefits. New projects to improve and optimize AI must be constantly required to support this progress and produce new technological innovations. In the end, AI has enabled companies to develop intelligent services that can participate in regular conversations and interactions. There are, for example, well-known applications of our time such as Siri, Cortana and Google's Assist. In addition to that, AI has helped large tech companies around the world to automate for example their customer service systems such as chatbots and optimize access and response to similar requests across different platforms (Fadziso, 2018).
However, it is not only in the described areas that AI has found a strong place and developed into true greatness. As mentioned at the beginning, AI has also arrived in the business world and provided technological advances to companies worldwide. The advantage of AI remains that through well-programmed algorithms, a specific desired outcome or goal can be achieved, and in the best-case scenario, it can interact independently based on the previously written algorithm within a given framework (Iansiti and Lakhani, 2020).
2.2.2 Development and current situation
There's an old saying that says imagination is the mother of innovation. This aphorism is especially relevant in the world of science and technology since most inventions are the result of the human imagination. When people talk about AI today, very often it gets the impression that the negative aspects of this whole new technology outweigh the public debate and in the very near future, machines will take over and run the world (Haarmeier, 2021, p. 1). For great computer science pioneers like Alan Turing, this was an opportunity to really think about the possibility of making machines think like humans. The history of artificial intelligence can therefore be traced back to 1950, from the so-called Turing suggestion for the possibility of mechanizing intelligence (Chalmers et al., 2020).
At that time, Turing presented his milestone paper entitled "Computing Machinery and Intelligence," which posed the fundamental question of whether machines can think. In his paper, he wanted to create a machine to show that machines can think. Unfortunately, the Turing Ideology was never realized due to the high computer running costs (Turing, 1950; Anyoha, 2017). The "period of AI" continued in 1956 with the Dartmouth Conference. During the conference, American computer scientist John McCarthy first mentioned the term "artificial intelligence", a term that would later develop into a scientific field (McCarthy et al., 1955). The Dartmouth conference was the first-ever artificial intelligence event designed to bring researchers together and facilitate a collaborative discussion on the future of artificial intelligence. Key figures and initiators for the conference were John McCarthy, Marvin Minsky, and Claude Shannon (Chalmers et al., 2020). However, the conference failed to have any real impact due to individual differences and interests. Unfortunately, the discrepancies of the conference also saw John McCarthy fall short of his idea of collaborative work on artificial intelligence, as the participants could not agree on the standard methods in the field. However, they collectively agreed with McCarthy's idea that AI would be achievable and researchable (Anyoha, 2017).
In the beginning, between 1957 and 1974, the artificial intelligence program started to flourish heavily again. During this time, expectations and stakes were high as researchers had theoretically demonstrated the ability of machines to think like humans and even solve complex problems that humans could not solve. This success and the promising nature of artificial intelligence and stakeholders convinced the US government to invest in the artificial intelligence project. Government investments, particularly the US Department of Defence, have further accelerated and consistently subsidized the program. But the biggest problem was that technological development had faced several obstacles, the main one being the inability of computers to process and store enough information. That led to the fact that the subsidies were stopped (Anyoha, 2017).
In 1980, the Japanese Ministry of International Trade and Industry (MITI) launched in 1982. Called the Fifth Generation Computer Project (FGCP), it reignited the development of AI. Several prominent computer companies invested billions of dollars in the development of a better and much more powerful generation of computers. The goal was to develop hardware and software systems strong enough to be suitable for computing and coding applications. At the same time, there were further developments in the field of expert systems, which were composed of "inference machines" on the one hand and "knowledge bases" on the other. This development is considered to be one of the first successful implementations of AI applications. Unfortunately, a few years later, the goals of the FGCP could not be met, and the promising program was discontinued and fell out of the public interest (Kaynak, 2021). Fortunately, in the years 1990 - 2000, the development of AI made its comeback. During this time, AI achieved many landmark goals, including the development of IBM's Deep Blue, a chess-playing program, and Windows' speech-recognition software. IBM's Deep Blue chess software proved to be extremely useful and was hailed as a milestone when the software defeated the world chess champion Gary Kasparov in 1997 (Anyoha, 2017).
Another considerable improvement was seen regarding the technological improvement of computers. For the first time, tremendous computing power enabled computers to analyse, process and evaluate huge amounts of data sets (big data) and complex data (descriptive, predictive, and prescriptive). The development of AI was booming due to the new computing power, and there were again various subsidies from institutions to support the development. These milestones led to rapid development in the field of AI. The development at the beginning of the 21st century of "machine learning" (ML) was significant for the field of science. The next step in development was Deep Learning (DL), which also led to further advances (Kaynak, 2021). To better illustrate the terminologies, the "umbrella term" as shown below, can be used, which includes the umbrella term with its AI on the top and its wide range of subcategories, such as ML and its subfield of DL (Myers et al., 2020).
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Figure 1: AI Umbrella term; own illustration
At the moment, the world is in the age of “Big Data”, "Machine Learning," and "Deep Learning." A time that is constantly and technologically developing rapidly, and it will influence the future even more (Anyoha, 2017; Russel and Norvig, 2021). As significant accomplishments are achieved, the future of AI remains bright. AI is a key driver of the fourth industrial revolution, a period characterised by increased technological advancements such as quantum computing, the internet of things, robots, and artificial intelligence (Syam and Sharma, 2018; Mhlanga, 2021). Marr states a universal statement for the future to come. He says artificial intelligence will change the world once and for all. There will be a shift more profound than most people realize today. AI will expand or even completely change the world of work regardless of profession, industry or sector (Marr, 2020, p. 9).