Chapter One — 1.1 Background to the Study

The rapid evolution of Explainable AI has transformed the way organizations design, deploy, and manage enterprise resource planning (ERP) systems. As institutions seek to modernize legacy processes, Explainable AI offers new opportunities to improve service delivery, reduce manual overhead, and respond more effectively to user needs.

In practice, however, adoption of explainable AI within enterprise resource planning (ERP) systems has been uneven, and its actual impact on process automation is not yet well understood in a rigorous, evaluable way — a gap this study is positioned to address.

1.2 Statement of the Problem

Existing approaches to process automation within enterprise resource planning (ERP) systems remain largely reactive and fragmented, with little systematic use of explainable AI despite its demonstrated value elsewhere. This study addresses the resulting gap by designing and evaluating a solution built specifically around explainable AI.

1.3 Objectives of the Study

1. To design and implement a explainable AI-based approach to improving process automation in enterprise resource planning (ERP) systems.
2. To evaluate the effectiveness of Explainable AI in enhancing process automation within enterprise resource planning (ERP) systems.
3. To identify the key requirements and constraints relevant to deploying explainable AI in this context.
4. To assess user and stakeholder perception of the resulting system.

1.4 Research Questions

1. How can explainable AI be applied to improve process automation in enterprise resource planning (ERP) systems?
2. How effective is Explainable AI at enhancing process automation within enterprise resource planning (ERP) systems?
3. What requirements and constraints are relevant to deploying explainable AI in this context?
4. How do users and stakeholders perceive the resulting system?

1.5 Significance of the Study

Beyond its immediate technical contribution, this study offers value to organizations evaluating whether to invest in explainable AI for their own enterprise resource planning (ERP) systems, and contributes to the broader literature on applied software technology / IT by documenting a concrete implementation and evaluation case.

1.6 Scope of the Study

As a MSc-level study, its scope is confined to designing and evaluating a explainable AI-based solution for enterprise resource planning (ERP) systems, focused specifically on process automation; broader deployment considerations fall outside this scope.