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Introduction

Artificial Intelligence (AI) has revolutionized various industries, including healthcare, finance, and marketing. One of the key applications of AI is in Decision Support Systems (DSS), which help individuals and organizations make informed decisions based on data analysis and algorithms. AI-powered DSS leverage machine learning, natural language processing, and other AI technologies to provide recommendations and insights to users. This thesis explores the role of AI in decision-making and its impact on organizational performance.

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter Two: Literature Review
2.1 Evolution of AI in Decision Support Systems
2.2 Theoretical Frameworks in AI-Powered DSS
2.3 Applications of AI in Decision-making
2.4 Benefits and Challenges of AI-Powered DSS
2.5 AI Ethics and Bias in Decision-making
2.6 AI Adoption in Organizations
2.7 AI Success Stories in Decision Support Systems
2.8 AI and Human Decision-making
2.9 Hybrid DSS: Combining AI and Human Intelligence
2.10 Future Trends in AI-Powered Decision Support Systems

Chapter Three: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Sampling Techniques
3.4 Data Analysis
3.5 Ethical Considerations
3.6 Research Limitations
3.7 Reliability and Validity
3.8 Research Variables

Chapter Four: Discussion of Findings
4.1 Overview of Data Analysis Results
4.2 Comparison of AI-Powered DSS in Different Industries
4.3 Impact of AI on Decision-making Processes
4.4 User Satisfaction with AI Recommendations
4.5 Challenges Faced in Implementing AI-Powered DSS
4.6 Organizational Adoption of AI Technologies
4.7 Recommendations for Improving AI-Powered DSS
4.8 Future Research Directions

Chapter Five: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions to the Field
5.3 Implications for Practitioners
5.4 Limitations of the Study
5.5 Suggestions for Future Research

Thesis Overview:

The use of Artificial Intelligence (AI) in Decision Support Systems (DSS) has gained significant attention in recent years, with organizations looking to leverage AI technologies to improve decision-making processes. This thesis aims to explore the role of AI in decision-making, specifically focusing on AI-Powered DSS and their impact on organizational performance.

The introduction provides an overview of the research topic, highlighting the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. The literature review explores the evolution of AI in DSS, theoretical frameworks, applications, benefits, challenges, ethics, adoption, success stories, and future trends in AI-Powered DSS.

The research methodology chapter outlines the research design, data collection methods, sampling techniques, data analysis, ethical considerations, limitations, and research variables. The discussion of findings chapter presents the results of data analysis, comparison of AI-Powered DSS in different industries, impact on decision-making processes, user satisfaction, challenges, organizational adoption, recommendations, and future research directions.

The conclusion and summary chapter provides a summary of findings, contributions to the field, implications for practitioners, limitations of the study, and suggestions for future research. Overall, this thesis aims to contribute to the existing literature on AI-Powered DSS and provide insights for organizations looking to implement AI technologies in their decision-making processes.

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