Investigating the impact of AI in operating successful business
Shah, Darshil (2022)
2022
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024051311059
https://urn.fi/URN:NBN:fi:amk-2024051311059
Tiivistelmä
In an era of rapid technological advancements, integrating Artificial Intelligence (AI) into business frameworks has emerged as a critical success factor. This thesis seeks to investigate the profound implications of AI adoption for fostering operational excellence and long-term growth across a variety of business contexts.
The first chapter establishes the context for the research by explaining its background, significance, and rationale, as well as identifying relevant research aims, objectives, and questions. It also outlines the dissertation's structural framework while acknowledging its limitations.
Chapter 2 conducts a thorough review of existing literature, defining various types of AI applications in business, explaining their significance, exploring relevant theories, and identifying challenges and strategies for effective integration, thereby establishing a solid conceptual framework.
Methodologically, Chapter 3 discusses the research philosophy, approach, design, data collection methods, analysis techniques, and ethical considerations, which ensure the study's rigour and validity.
Chapter 4 engages in a nuanced discussion, combining empirical findings with research objectives to reveal insights into the impact of AI on business operations, and Chapter 5 builds on these discussions to make actionable recommendations for improving AI-driven business strategies. These recommendations include improvement strategies and future research directions, contributing to the ongoing discussion about AI's transformative potential in the business landscape.
Finally, this thesis provides a multifaceted exploration of AI's impact on business operations, grounded in a rigorous methodological framework and concluding with practical recommendations for both business practitioners and scholars.
The first chapter establishes the context for the research by explaining its background, significance, and rationale, as well as identifying relevant research aims, objectives, and questions. It also outlines the dissertation's structural framework while acknowledging its limitations.
Chapter 2 conducts a thorough review of existing literature, defining various types of AI applications in business, explaining their significance, exploring relevant theories, and identifying challenges and strategies for effective integration, thereby establishing a solid conceptual framework.
Methodologically, Chapter 3 discusses the research philosophy, approach, design, data collection methods, analysis techniques, and ethical considerations, which ensure the study's rigour and validity.
Chapter 4 engages in a nuanced discussion, combining empirical findings with research objectives to reveal insights into the impact of AI on business operations, and Chapter 5 builds on these discussions to make actionable recommendations for improving AI-driven business strategies. These recommendations include improvement strategies and future research directions, contributing to the ongoing discussion about AI's transformative potential in the business landscape.
Finally, this thesis provides a multifaceted exploration of AI's impact on business operations, grounded in a rigorous methodological framework and concluding with practical recommendations for both business practitioners and scholars.