The dissertation explores the adoption of AI in PM and SD are approached in the growing IT companies in Nepal. Although there is an acknowledgment that AI technologies can be used to boost productivity, make decisions and identify workflows more efficient, the implementation of the given technology in developing countries, including Nepal is rather uneven. Based on TAM and incorporating its constructs in their application, including the organizational support, ease of use, and security concerns, the study investigates the perceived usefulness, ease of use, and readiness of the situation concerning the AI implementation by IT professionals in Nepal. A mixed-methods approach was used, which focused on utilizing both the quantitative and quantitative results of the survey of 325 respondents as well as the qualitative data about the industry by interviewing experts in that domain. The evidence indicates that the attitude toward AI in terms of potential benefits is rather positive, still, there are still considerable obstacles: the unavailability of proper infrastructure, the absence of special knowledge, legal gaps, and internal insistence. Moreover, privacy and ethical concerns further complicated implementation. Despite all these difficulties, there are indicators of efficiency, speed of project completion, and innovation within early AI adopters. This paper finishes by making conception of policy suggestions and strategic guidelines that would be necessary in the implementation of sustainable and sensitive AI incorporation in Nepal IT sector with a focus on institutional alignment, capacity-building, and local adaptation models.
Table of Contents
1. CHAPTER 1 INTRODUCTION AND BACKGROUND
1.1 Introduction
1.2 Background
1.2.1 Artificial Intelligence (AI) in Nepal
1.2.2 Global Perspective Towards AI
1.3 Problem Statement
1.4 Research Questions
1.5 Research Hypothesis
1.6 Purpose of Research
1.7 Objective of the Research
1.8 Scope of Research
1.9 Significance of Research
1.10 Overview of Project Structure
1.11 Project Plan
1.12 Chapter Summary
2. CHAPTER 2 LITERATURE REVIEW
2.1 Artificial Intelligence: Conceptual Foundations and Global Perspective
2.1.1 Historical Development and Evolution of AI Technologies
2.1.2 AI Applications and Technological Trends Worldwide
2.1.3 Global Adoption of AI in SD
2.1.4 Global Adoption of AI in PM
2.2 Drivers and Determinants of AI Adoption
2.2.1 Theoretical Frameworks Explaining Technology Adoption
2.2.2 PU and Performance Benefits of AI
2.2.3 PEoU and Integration Challenges
2.2.4 Organizational Culture, Leadership, and AI Adoption
2.2.5 External Environmental Factors Influencing AI Adoption
2.3 Barriers and Challenges in Adoption of AI
2.3.1 Technological Barriers and Infrastructure Gaps
2.3.2 Human and Organizational Resistance
2.3.3 Ethical, Legal, and Regulatory Challenges
2.3.4 Regional and Digital Divide Challenges
2.4 AI Adoption in Nepal: National Context and Local Realities
2.4.1 Nepal’s National AI Policy 2081: Vision and Gaps
2.4.2 Readiness of Nepalese IT industry for AI Integration
2.4.3 Emerging AI Applications in Nepal’s Private Sector
2.4.4 Implicit AI Adoption in Nepalese Society
2.5 Security, Privacy, and Ethical Consideration in AI Adoption
2.5.1 Data Privacy and Security Challenges in AI Systems
2.5.2 Ethical AI and Algorithmic Bias: Challenges in Transparency and Fairness
2.5.3 Cybersecurity Concerns in AI Deployments: Safeguarding against Malicious Attacks
2.6 Insights from the PMI Global Survey on AI Adoption in PM
2.7.1 Lessons Relevant for Nepal’s Context
2.8 Theoretical Framework for this Study
2.8.1 Technology Acceptance Model (TAM)
2.9 Related Work (Supporting Base Papers)
2.10 Literature Review Matrix
2.11 Chapter Summary
3. Chapter 3 RESEARCH METHODOLOGY
3.1 Introduction
3.2 Conceptual Model
3.2.1 Independent Variable
3.2.2 Moderating Variables
3.2.3 Dependent Variables
3.3 Research Strategy
3.4 Research Design
3.4.1 Descriptive Research
3.4.2 Exploratory Research
3.4.3 Data Analysis using SPSS
3.5 Data Collection Procedure
3.5.1 Data Collection
3.5.2 Questionnaire Development
3.6 Sample Selection
3.7 Sampling Method
3.8 Pilot Study
3.9 Data Validation and Reliability
3.10 Ethical Consideration
3.11 Chapter Summary
4. CHAPTER 4 DATA ANALYSIS AND INTERPRETATION
4.1 Pilot Test Result
4.2 Reliability Testing using Cronbach’s Alpha Reliability Test
4.3 Descriptive Analysis
4.3.1 Respondent’s Background
4.3.2 AI Usage for PM and SD
4.3.3 Perceived Usefulness of Artificial Intelligence (PUoAI)
4.3.4 Perceived Ease of Use of AI (PEoUoAI)
4.3.5 Compatibility with workflows
4.3.6 Organizational Support for AI Adoption
4.3.7 AI Mindset and Openness to Innovation
4.3.8 Security and Privacy Concerns
4.3.9 BI to Adopt AI
4.3.10 Overall Descriptive Analysis (Independent and Dependent Variables)
4.4 Inferential Analysis
4.4.1 Correlation Analysis
4.4.2 Linear Regression Analysis for Hypothesis Testing
4.5 Chapter Summary
5. CHAPTER 5 DISCUSSION AND FINDINGS
5.1 Interpretation of Findings
5.1.1 Challenges Faced During Data Collection
5.1.2 Demographic Data
5.1.3 Dependent and Independent Variables
5.1.4 AI Usage for SD and PM (Current Situation)
5.2 Research Questions and Findings
5.3 Hypothesis Testing and Findings
5.4 Implication of Findings
5.5 Chapter Summary
6. CHAPTER 6 CONCLUSION AND RECOMMENDATIONS
6.1 Conclusion
6.2 Recommendation, Strategies and Solutions
6.2.1 Strengthening Organization Commitment and Support:
6.2.2 Investment in Infrastructure Development
6.2.3 Address Security, Privacy, and Ethical Concerns:
6.2.4 Adopt Phased Implementation Approach:
6.2.5 Focus on Building an AI-Skilled Workforce:
6.3 Contribution and Impact of the study
6.4 Future Research and Possibilities
6.5 Chapter Summary
Objectives and Research Themes
This dissertation examines the adoption of Artificial Intelligence (AI) within Project Management (PM) and Software Development (SD) processes in growing IT companies in Nepal. The primary research goal is to identify the factors influencing AI adoption and to balance the potential benefits, such as increased productivity and efficiency, against significant local challenges like infrastructure limitations, skill gaps, and data security concerns.
- The impact of perceived usefulness and ease of use on AI adoption behavior.
- Challenges related to infrastructure, regulatory gaps, and organizational readiness in Nepal.
- The role of organizational culture and leadership in fostering AI innovation.
- Ethical and privacy concerns affecting the implementation of AI-driven tools.
- Strategic recommendations for sustainable AI integration in the Nepalese IT sector.
Excerpt from the Book
1.1 Introduction
Within the last five years, the field of AI has had a swift development path to large-scale integration in several industries, significantly changing the organization practice in the field of PM and SD (Hashimzai & Mohammadi, 2024). Modern world research constantly emphasizes the transformational potential of AI that enables the optimization of processes, improve the accuracy of forecasting, automation of routine operations, and innovation (Ajiga et al., 2024). In PM, the interactive functionalities of AI, like NLP, predictive analytics, and virtual assistants, are gradually being used as PM tools to predict risks, improve scheduling and enhance decision-making under uncertainty. In SD, AI also helps do intelligent code generation, defect prediction, automatic software testing and knowledge management thus potentially making tremendous gains in the productivity and quality of software in similar ways (Russo, 2024).
Although integration of AI is becoming a demanding but important task in the field, significant progress has already been made towards it. There are still several barriers in well-developed economies, such as technical constraints, data-privacy laws, organizational resistance, and moral concerns (Baqar, 2024). The studies emphasize that, despite the AI systems having the potential of boosting efficiency and triggering innovations, they also create the danger of algorithmic prejudice, poor explainability, and displacement of labor due to the introduction of the technology, especially in cases where software engineers not only overestimate the above risks but in addition are in danger of losing their profession and facing unemployment (Russo, 2024). Organizational culture has been found to play a major role within a firm: in some, where knowledge sharing is encouraged, workforce is trained, and clear suggestions of how to use AI are designed, the adoption levels and smooth integration of AI into the prevailing work processes are reported to be higher (Li et al., 2024). On the contrary, there is little research on the contextual determinations involved in AI adoption in less developed economies.
Summary of Chapters
CHAPTER 1 INTRODUCTION AND BACKGROUND: This chapter provides an overview of the research topic, defining the primary scope, objectives, and research questions concerning AI adoption in Nepalese IT firms.
CHAPTER 2 LITERATURE REVIEW: This chapter presents a systematic analysis of global and local literature on AI adoption, covering theoretical frameworks like TAM and the specific challenges faced in the Nepalese context.
CHAPTER 3 RESEARCH METHODOLOGY: This chapter details the mixed-methods research design, including the conceptual model, data collection procedures through surveys, and analytical techniques used to validate the study.
CHAPTER 4 DATA ANALYSIS AND INTERPRETATION: This chapter offers a comprehensive analysis of the survey results using SPSS, covering reliability testing and descriptive statistics regarding AI perception and usage.
CHAPTER 5 DISCUSSION AND FINDINGS: This chapter interprets the statistical results in relation to the research questions, highlighting the key drivers and barriers for AI adoption in Nepal.
CHAPTER 6 CONCLUSION AND RECOMMENDATIONS: This chapter summarizes the main findings and provides strategic recommendations for stakeholders to foster sustainable AI implementation and long-term industry growth.
Keywords
Artificial Intelligence, Project Management, Software Development, AI Adoption, Technology Acceptance Model, Data Privacy, AI Mindset, Ethical Concerns, Nepal IT Industry, Innovation, Organizational Support, Productivity, Digital Transformation, Algorithmic Bias, Infrastructure Development
Frequently Asked Questions
What is the primary focus of this dissertation?
The research focuses on the adoption of AI technologies in Project Management (PM) and Software Development (SD) specifically within growing IT companies located in Nepal.
What are the central thematic areas covered?
The study covers drivers of adoption (perceived usefulness/ease of use), barriers (infrastructure, skill gaps, privacy concerns), organizational support, and the role of innovation mindset.
What is the core research objective?
The objective is to identify and analyze the factors influencing AI adoption in the Nepalese IT sector and to propose strategic guidelines to balance challenges and opportunities.
Which methodology is employed in this study?
The author uses a mixed-methods approach, combining quantitative data from surveys (325 respondents) with qualitative insights gathered from domain experts.
What does the main body of the work address?
The work addresses the theoretical background through literature review, defines a conceptual model based on TAM, and performs rigorous data analysis to validate hypotheses about AI adoption intentions.
Which keywords characterize this research?
The research is characterized by terms such as AI Adoption, Technology Acceptance Model, Project Management, Software Development, and Data Privacy.
Why is Nepal's specific national context significant for this study?
Nepal's unique challenges, such as its nascent startup ecosystem, infrastructure gaps, and lack of specialized AI legislation, make it an essential case study distinct from developed economies.
What is the practical value of the proposed strategic guidelines?
The guidelines provide actionable steps for organizations, such as phased implementation and investment in workforce upskilling, to mitigate integration risks and achieve long-term growth.
- Quote paper
- Pratyush Maharjan (Author), R. N. Thakur (Author), 2025, Adoption of AI in Project Management and Software Development in Growing IT Companies in Nepal, Munich, GRIN Verlag, https://www.grin.com/document/1737711
