Assessing the Use of Artificial Intelligence in Internal Auditing of Conglomerate Firms: The Case of Dangote Group Plc
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Assessing the Use of Artificial Intelligence in Internal Auditing of Conglomerate Firms: The Case of Dangote Group Plc
Abstract
The emergence of Artificial Intelligence (AI) has transformed internal auditing by enhancing fraud detection, risk assessment, reporting accuracy, and operational efficiency. However, despite its growing adoption globally, many large conglomerates in developing economies continue to struggle with fully integrating AI into internal audit functions. This study examines the prospects and challenges of incorporating Artificial Intelligence in internal auditing within large conglomerate companies, with specific focus on Dangote Group Plc. A descriptive research design was adopted, and data were collected through structured questionnaires administered to internal auditors, IT personnel, and risk management officers within the organization. The study also reviewed secondary data, including audit reports, organizational policies, and industry publications. Findings reveal that AI presents significant prospects such as improved detection of anomalies, automation of repetitive audit tasks, enhanced predictive analytics, real-time monitoring, and strengthened internal control systems. However, challenges identified include high implementation costs, lack of technical expertise, data privacy concerns, resistance to change, and infrastructural limitations. The study concludes that while AI holds substantial potential to revolutionize internal auditing in large Nigerian conglomerates, strategic investments, capacity building, policy development, and phased implementation are essential for maximizing its benefits. The research recommends the adoption of AI-driven audit software, continuous training for audit personnel, and robust data governance frameworks to ensure successful integration in the internal audit processes of Dangote Group Plc and similar organizations.
Keywords: Artificial Intelligence, Internal Auditing, Conglomerates, Dangote Group Plc, Predictive Analytics, Audit Automation, Organizational Controls
TABLE OF CONTENTS
Abstract
Table of Contents
List of Tables
List of Figures
List of Abbreviations
CHAPTER ONE: INTRODUCTION
1.1 Background to the Study
1.2 Statement of the Problem
1.3 Objectives of the Study
1.4 Research Questions
1.5 Research Hypotheses
1.6 Significance of the Study
1.7 Scope of the Study
1.8 Operational Definition of Terms
CHAPTER TWO: REVIEW OF RELATED LITERATURE
2.1 Conceptual Review
2.1.1 Concept of Artificial Intelligence
2.1.2 Internal Auditing and Its Functions
2.1.3 Types of AI Tools Used in Internal Auditing
2.1.4 Prospects of AI in Internal Auditing
2.1.5 Challenges of Implementing AI in Internal Audit Functions
2.1.6 Overview of Large Conglomerate Companies in Nigeria
2.1.7 Internal Audit Structure of Dangote Group Plc
2.2 Theoretical Review
2.2.1 Technology Acceptance Model (TAM)
2.2.2 Innovation Diffusion Theory
2.2.3 Agency Theory
2.3 Empirical Review
2.4 Gap in the Literature
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Research Design
3.2 Population of the Study
3.3 Sample Size and Sampling Technique
3.4 Sources of Data
3.5 Research Instrument
3.6 Validity of the Instrument
3.7 Reliability of the Instrument
3.8 Method of Data Collection
3.9 Method of Data Analysis
3.10 Ethical Considerations
CHAPTER FOUR: DATA PRESENTATION, ANALYSIS AND INTERPRETATION
4.1 Demographic Characteristics of Respondents
4.2 Analysis of Research Questions
4.3 Test of Hypotheses
4.4 Discussion of Findings
CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Summary of Findings
5.2 Conclusion
5.3 Recommendations
5.4 Contribution to Knowledge
5.5 Suggestions for Further Research
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