Assessing the Role of Artificial Intelligence on Leadership Development at Merafong Municipality

Abstract

The research is focused on assessing the role of artificial intelligence in leadership development at Merafong Municipality in Gauteng Province, South Africa. The current status of artificial intelligence is not adequate in Merafong Municipality and its role in the leadership development is also not clear and this is the research this problem is undertaken in the research for investigation purpose. In order to achieve the aim of the study, the study adopts a qualitative approach and qualitative data will be collected using semi-structured interview from 10 to 15 participants.

Purposive sampling will be used and the samples include union leaders’ordinary staff and managers of Municipality. Data will be analysed using thematic analysis and the research expect that it will highlight the current status of leadership development in South Africa and the challenges related to artificial intelligence that are faced by the leaders. 

Introduction 

Artificial intelligence (AI) is a key technology development that is driven through computers and machines for stimulation of the human learning and problem solving and decision-making process with full autonomy (Zhai et al., 2021). AI integrates two key aspects together namely engineering and cognitive science. Due to high efficiency and creativity of AI, it has wider applications in the different business areas at extensive level including leadership development (Peifer, Jeske and Hille, 2022). There are many ways to define and understand leadership as a concept and as a subject of study.

Leadership is a key practice of the organisations and their managers and leaders to make the followers influence in such a way that they are led and guided to work according to the instructions of the participants (Cummings et al., 2021). The concepts of responsibility and leadership are related in a more specific meaning. A leader is in charge of several things. This applies to both the business and the workers. For the personnel, for instance, the areas of communication, qualification, and information can be mentioned. Employee leadership can be understood in a variety of ways. The diverse range of leadership behaviours that have been established demonstrates this. Additionally, leadership varies depending on each manager’s rank inside the organisation (Boeske, 2023). 

Background

Africa, a continent rich in natural resources and human capital, faces numerous development challenges. The advent of Artificial Intelligence (AI) presents a transformative opportunity for Africa’s growth and development (Arakpogun et al., 2021). However, the successful integration of AI into Africa’s development trajectory is contingent upon addressing several pressing issues.There are several issues evident in currently in Africa.

The three major issues in this series are digital divide, skills gap and infrastructure. Africa’s digital divide remains a significant obstacle to AI adoption (Azaroual, 2024). Limited access to digital infrastructure, internet connectivity, and digital literacy hinders the continent’s ability to leverage AI for development. Africa faces a severe shortage of AI-related skills, including data science, machine learning, and programming. This skills gap undermines the continent’s ability to develop and implement AI solutions. Inadequate infrastructure, including unreliable energy supply and limited data storage capacity, hampers Africa’s ability to support AI-driven development.

Current Issues in South Africa:

Concerns about data privacy, limited adoption of AI, and unemployment and inequality are the three primary problems in South Africa (Arakpogun et al., 2021). Significant income inequality and high unemployment rates are problems in South Africa. Adoption of AI needs to be carefully controlled to prevent making these problems worse. AI adoption in South Africa is still quite low, despite its potential, especially in the public sector. The nation’s ability to benefit from AI is hampered by this slow adoption rate. Uncertainty surrounds AI-driven data collecting and analysis because South Africa’s data privacy laws are still developing.

The Role of AI in Merafong Municipality is widespared. Against this backdrop, the role of AI in Merafong Municipality’s development cannot be overstated. AI can help address pressing challenges, such as improved service delivery where AI can enhance service delivery in areas like healthcare, education, and public safety. The second challenge is economic growth where AI can drive economic growth by improving efficiency, productivity, and competitiveness in key sectors. Third is inclusive development where AI can help bridge the digital divide and promote inclusive development by expanding access to digital services and opportunities.

However, to realize these benefits, Merafong Municipality must address the challenges and concerns outlined above.  For dealing all the above challenges there is a need for adopting a comprehensive approach including multiple stages. Firstly, increasing investment in the digital infrastructure can upgrade digital infrastructure to support AI adoption and development. Furthermore, developing AI-Related Skills andinvesting in education and training programs that develop AI-related skills. Lastly, addressing data privacy concerns andand implementing robust data privacy regulations to ensure responsible AI adoption.

By acknowledging and addressing these challenges, Merafong Municipality can unlock the transformative potential of AI and drive inclusive and sustainable development. The following section presents the problem statement.

Problem Statement 

In the local government sphere, the implementation of the AI requires use of the suitable strategic approach to integrate AI in the leadership development process (Peifer, Jeske and Hille, 2022). Having significant contribution of AI in the banking organisations requires significant measures on the part of strategic managers. For the future leadership development, the starting point is to have a clear awareness about the needs of AI among the leaders and the area of further leadership development in their personality as well as routine practices. In order to have effective implementation of the AI for future leadership development, there is an intense need that the leaders have a deep and basic understanding of the AI and its usage in their development process (Pokorni Braun and Knecht 2021).

On the part of the organisations, it is vital to clearly define the objectives behind the use and implementation of AI for the leadership development approach. In South Africa, with the acceleration of the digital economy, it is important that businesses have significant integration of the AI for reshaping the business strategies to ensure the business continuity and ensuring the future development of the leadership practices for further business growth and sustainability (Bradshaw, 2025). However, the use of AI in the South African organisations may come up with multiple challenges such as vulnerabilities of cybersecurity, overreliance on automation, data privacy, skills gap and many more (Bradshaw, 2025).

As such, the key problem endevours to assess the importance of the role of Artificial intelligence for the future leadership development process in South Africa specifically in Merafong City Municipality. AI is threatening leadership development due to existence of multiple vulnerabilities and even the leaders are not competent enough to use AI technologies. The organisations and the employees are likely to suffer with these issues.

Literature review 

AI and leadership

In the opinion of Russell, (2022), Artificial Intelligence can be described as any program that can complete any action or task assigned to it which in a normal scenario needs a degree of decision-making and analysis which requires the presence of human intelligence. The technologies that are usually used in an artificial intelligence program consist of machine learning, deep learning and automation along with several other technological concepts. After creation, an AI model is trained on model data which is similar to the final data on which it would have to work. During the training process, the AI model picks up patterns and trends in the training data to develop an understanding of the information that would be passed to it, which is then used by it to generate results on the final data.

According to Northouse, (2023), leadership can be described as the ability of an individual to have a degree of influence on other individuals and having the capacity to motivate and guide other people towards a common goal present with them. Some qualities that are associated with the process of leadership include strategic decision-making, communication, conflict resolution and people management skills. Additional skills such as emotional intelligence and project management skills are also helpful for a person in a position of leadership.

Need for Leadership Development in South African organisations

As noted by Samuel and Moagi (2022), the current economic conditions in South Africa are extremely distressing with the issues of fluctuating market conditions and economic inequality being one of the biggest issues being faced by the country’s government. The need for strong and capable leadership showcases itself in a highly significant form as not only can a goal-oriented and efficient collaborative team help an organization to drive economic recovery but can also help ensure an organization can handle a majority of the challenges presented with itself.

The contemporary South African business scenario is in extreme need of leaders who can not only help their team to adapt to any unexpected changes but who also have an innovative mind set and can lead to the creation of new opportunities for the organization in these unexpected events (Samuel and Moagi, 2022) Furthermore, Anwana, (2024), expressed that the use of AI is a highly suitable option which can not only help the organizations present in the country to ensure that the leadership improvement initiatives being conducted by them are not only highly customized to their needs but are also highly efficient in a way such that it can help in improving the strategic planning and workforce optimization processes of the company.

Importance of AI for leadership development 

In the opinion of Buxmann et al., (2021), the impact of AI on the improvement of leadership situations in an organization is extremely significant. In the corporate sector, the utilization of AI can not only help in improving the decision-making process present with leaders of the company but can also make it more time-efficient. The different metrics that are associated with data-driven decision making like risk assessment and strategic forecasting can be easily generated by AI in a time-effective manner hence, increasing the speed of the decision-making process. Utilizing tools like chatbots can also help ensure that any issues raised within the team can be easily resolved and the leader is kept aware of the different problems their team members face.

According to Bradshaw and McMillan, (2021), in the healthcare sector, the benefits of using an AI tool is highly beneficial. Not only can the use of this tool help the heads of management teams to be well aware of the different resources present to them but can also handle the patient management tasks simply and securely. The use of AI can also help in ensuring that the administrative tasks associated with the healthcare process can be automated which can not only reduce the consumer wait time but can improve overall patient assistance efficiency of the institution.

In this context, two theories of leadership can be significant. A key theory can be the situational leadership theory as per which the leaders must make changes in their leadership qualities and traits considering the particular situation (Winkler, 2010). Considering the need for AI adoption the leaders in South Africa must integrate AI technologies in their leadership practices to foster further improvement. Another leadership theory can be supportive in this context can be transformational leadership theory. The theory affirms that successful leaders are those who embrace required transformation in the business process and the leadership practices (Winkler, 2010). Being transformative in nature, the transformational leaders can adopt the AI technologies to enhance the performance level of the employees.

Research Objectives

The key aim of this research is to examine the role of artificial intelligence in leadership development at Merafong Municipality. 

The primary objectives are;

• To explore the current state of leadership development at Merafong Municipality and need for AI integration.
• To examine the potential applications of AI in leadership development for better leadership development in future
• To investigate the benefits and challenges of AI adoption in leadership development in Merafong Municipality

Research Questions

General Research Question

How significant and supportive is the role of artificial intelligence in leadership development at Merafong City Municipality?

Specific Research Questions

• What is the contribution of the artificial intelligence in the leadership development practices?
• How is Merafong Municipality using artificial intelligence in leadership development practices?
• What more improvements can be fostered in the leadership development practices because of increased use of artificial intelligence in Merafong Municipality?

Research Methodology

In this research, qualitative methodology was used where semi-structured interview method of data collection was used. Under semi-structured interview, the research used open-ended questions-based interview schedule to gain in-depth understanding and knowledge about the research problem undertaken for investigation.

Research Design

Research designs a key blueprint that designs the entire blueprint of doing the research project (Source). In this research, exploratory research design will be used that is supportive to conduct research on a topic on which there was no research conducted in the past and hence found ample scope of investigation (Kumar and Ujire, 2024). The exploratory research design helps to examine the how and why aspects of any research and it is flexible in nature to be applied easily in the scientific research studies and thereby it will be suitable for this research. Exploratory research design was chosen in this research because it helps to investigate a research phenomenon on which no research was conducted in the past and even the topic selected for research in this study was also not explored in the past and thereby it was the best suited design for this research.

Research Approach 

Considering the nature of the research problem undertaken for investigation purpose in this research, it will consider inductive research approach (Source). The key feature of inductive approach is adoption of bottom-up approach where specific data is collected about any research phenomenon and from that data general interpretations are made (Kumar and Ujire, 2024). In this research also, specific data will be collected about the role of AI in the South African organisations for the leadership development in current and future. From this data and its interpretations, generalise conclusions will be driven in terms of determining the effectiveness of AI technologies in driving the future leadership development. Inductive approach drives to conduct the research as a qualitative research study and hence this research will be conducted using qualitative data.

Research Setting

The key research setting selected for this research is South African organisations. The main focus will be given on the organisations that are using AI in their routine business management practices. There is no particular industry of sector selected for this research to conducted research on whilst in general all organisations will be selected. 

Research Procedure 

For the data collection purpose, a systematic procedure will be followed in this research. Firstly, considering the nature of research problem, a data collection instrument will be devised in this research for primary data collection purpose (Mazhar et al., 2021). After devising the instrument, sample selection will be done for collecting the data with. After sample selection, the process of data collection will be accomplished. The collected data will be analysed using the suitable data analysis method and then findings of the data will be presented. The findings and their interpretations will be used to present the key research outcomes and final conclusions. 

Sampling 

For the data collection purpose, selection of the sample will be done via using purposivelyas a suitable sampling technique under non-probability sampling. Purposive sampling is characterised considering the specific attributes of the sample population such as their knowledge level, experience level, time availability and willingness to take part in the data collection process (Andrade, 2021). The target sample population will be union leader ordinary staff and managers of Municipality. The expected sample size for the data collection will be around 8-10 participants. 

Data Collection Method

In the direction of inductive research approach, this research will take use of the qualitative data collection method of semi-structured interview. The semi-structured interview method is supportive to collect the data in a flexible manner (Ruslin et al., 2022). Using semi-structured interview, data can be collected in an in-depth manner and in detailed manner. Having a direct communication with the participants in the semi-structured interview method, the ambiguity and confusion in the data collection process will be eliminated. 

The physical interview with each participant will be done individually at different time intervals. One interview session will consume a time of around 10-20 minutes.

Data Analysis

The data that will be collected via using the semi-structured interview method will be qualitative in nature and hence the analysis of this data will be done via using the thematic analysis method of qualitative analysis. For thematic analysis, Braun and Clarke model will be applied where the analysis will be done under 6 sequential steps. Under these steps, firstly the data will be familiarised and then codes will be generated (Braun and Clarke, 2023). Based on the codes some themes will be identified, and further review of the themes will be done. After reviewing the themes will be finalised and defined. Under those themes, the findings of the interview data will be presented using excerpts of the semi-structured interview. 

Strategies to ensure quality of the data

For ensuring the quality of the data in this research, different strategies will be adopted:

• Firstly, the findings of the interview will be verified and supported with the data findings of literatures. This will ensure to maintain construct validity of the research data findings.
• For maintaining reliability of the data, the interview questions will be asked from the participants who are reliable in nature. 
• In the interview questions, the language will be made in simple English language for giving a good understanding to the participants and avoiding any confusion and ambiguity of the data. 
• In this research, there is no manipulation of the data made so that realistic and authentic data results will be gained. 

Research Gap

In the existing research studies, good exploration has been made about the role of AI in the leadership development, however, the content of AI role in future leadership development in South African local government specifically in Merafong City Municipality is not explored by past scholars which is an evident gap in the past research studies.

Ethical Considerations 

Informed Consent: Firstly, the participants who will take part in the data collection process will be asked to give their signed consent form to ensure their voluntary participation in the overall data collection process. 

Privacy and confidentiality: The participants of the data collection will have high concern with their privacy and confidentiality. For the same purpose, no personal details of the participants will be collected such as their names, home address and mobile numbers to keep it anonymity.

Data Originality: Maintaining the originality of the data will require, avoiding of copying any data in the similar format in research.

Selecting Participants: While selecting the participants, it will be taken care that no member is selected from any vulnerable group category or minor category.

Chapter Division

The chapters in this dissertation are presented as follows:
Chapter 1: Introduction
Chapter 2: Literature Review
Chapter 3: Research Methodology
Chapter 4: Findings
Chapter 5: Discussion of Findings
Chapter 6: Conclusions, Limitations and Recommendations