An Assessment of Automated Decision-Making in Nigerian Business Environments: A Case Study of Corporate Organizations in Kebbi State
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- NGN 5000
Background of the Study
Automated decision-making, powered by artificial intelligence and machine learning algorithms, enables businesses to streamline operations, reduce biases, and improve decision accuracy. From resource allocation to customer segmentation, automation transforms traditional decision-making processes into efficient and data-driven frameworks (Thomas & Adebayo, 2023).
In Kebbi State, corporate organizations face the challenge of improving operational efficiency and competitiveness in a dynamic business environment. Despite the availability of automated decision-making technologies, adoption levels remain inconsistent. This study explores the impact of automated decision-making on business performance and operational efficiency in corporate organizations in Kebbi State.
Statement of the Problem
Traditional decision-making processes in many corporate organizations are time-consuming, prone to errors, and lack scalability. Although automated decision-making offers solutions to these issues, its adoption is hindered by factors such as high implementation costs, lack of technical expertise, and resistance to change (Abdullahi et al., 2024). This study evaluates the effectiveness of automated decision-making in improving business performance in Kebbi State.
Objectives of the Study
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To assess the adoption level of automated decision-making technologies in corporate organizations in Kebbi State.
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To evaluate the impact of automated decision-making on operational efficiency and business performance.
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To identify challenges faced by corporate organizations in adopting automated decision-making.
Research Questions
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What is the adoption level of automated decision-making technologies in corporate organizations in Kebbi State?
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How does automated decision-making influence operational efficiency and business performance?
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What challenges hinder the adoption of automated decision-making in corporate organizations?
Research Hypotheses
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There is no significant relationship between automated decision-making adoption and operational efficiency.
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Automated decision-making does not significantly impact business performance.
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Challenges to adopting automated decision-making are not significant in corporate organizations in Kebbi State.
Scope and Limitations of the Study
The study focuses on corporate organizations in Kebbi State, analyzing their use of automated decision-making technologies. Limitations include varying levels of technology adoption and access to proprietary business data.
Definitions of Terms
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Automated Decision-Making: The use of algorithms and AI to make decisions without human intervention.
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Operational Efficiency: The ability to deliver services effectively while minimizing costs and resources.
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Corporate Organizations: Large businesses or entities engaged in various commercial activities.
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