Jul 2026· International Journal of Advanced Research· 0 citations
TL;DR
The findings reveal that human - AI collaboration has a significant positive effect on project management performance, particularly in improving cost efficiency, schedule adherence, and quality delivery, indicating that organisations with strong digital infrastructure, skilled personnel, and supportive leadership derive greater benefits from AI integration.
Abstract
The integration of artificial intelligence (AI) into project management is reshaping organisational practices by enhancing decision-making, efficiency, and project outcomes. This study examines the relationship between human-AI collaboration and project management performance in Nigeria, with organisational readiness as a moderating variable. A quantitative, cross-sectional survey design was adopted, and data were collected from 120 project managers and team members across construction,information technology, banking, and telecommunications sectors. Data were analysed using descriptive statistics, correlation, regression, and moderation analysis. The findings reveal that human - AI collaboration has a significant positive effect on project management performance, particularly in improving cost efficiency, schedule adherence, and quality delivery. Additionally, organisational readiness significantly moderates this relationship, indicating that organisations with strong digital infrastructure, skilled personnel, and supportive leadership derive greater benefits from AI integration. These results reinforce the relevance of Socio-Technical Systems Theory and the Technology Acceptance Model in explaining AI-enabled project environments.
This study aims to investigate how artificial intelligence (AI) can enhance Lean Construction Management to achieve efficient and sustainable project delivery in Pakistan. It examines current practices, perceived benefits and the organizational, technical and cultural barriers that influence AI adoption within the construction sector.
A mixed-methods design was used, combining a systematic literature review, a Delphi-based expert consultation with 12 regional specialists, semi-structured interviews with 50 professionals and a quantitative survey of 125 valid responses. Statistical analyses, including correlation tests, were conducted to assess relationships between AI use, Lean outcomes and adoption factors.
Results reveal a strong positive correlation between AI tool usage and improved Lean outcomes, particularly in project planning, real-time monitoring and waste reduction. Predictive analytics and image-recognition technologies produce the greatest operational benefits. Despite growing interest, adoption remains limited due to high upfront costs, inadequate digital skills, data and integration challenges and organizational resistance to change. Capacity building and supportive policies are viewed as essential enablers.
This study provides the first empirical validation of AI-Lean integration in Pakistan’s construction sector. It demonstrates a strong positive correlation (r = 0.865) between AI tool usage and Lean outcomes, introduces a novel “fragmentation-of-adoption” concept specific to resource-constrained settings, and integrates the technology acceptance model, unified theory of acceptance and use of technology and diffusion of innovations theory into a unified adoption framework. These contributions offer a replicable evidence base for emerging economies, moving construction innovation literature beyond conceptual propositions to context-specific, empirically grounded practice.
M. Ali, Javed Ahmed Khan Tipu, E. Shaqour et al.· Construction Innovation· 0 citations
This study examines the role of Artificial Intelligence (AI) in enhancing supply chain project management and operational performance in a dynamic business environment. As supply chains become increasingly complex, data-intensive, and disruption-prone, organizations are adopting AI-driven tools to improve forecasting accuracy, optimize inventory, streamline logistics, and strengthen decision-making. The purpose of this research is to assess the level of AI adoption, identify key application areas, and examine the relationship between AI familiarity and AI adoption while considering the broader roles of organizational readiness and governance mechanisms. A quantitative research design was employed using a structured questionnaire administered to 42 respondents, including supply chain professionals, project managers, data/AI analysts, students, and other business or technology-related participants. Data were analyzed using descriptive statistics, correlation analysis, and regression techniques. The findings indicate that approximately 57% of respondents reported current AI adoption within their organizations, while the mean AI familiarity score was 3.6 on a five-point scale, reflecting moderate awareness. Correlation analysis revealed a positive relationship between AI familiarity and AI adoption (r = 0.61), suggesting that increased knowledge supports adoption behavior. The results also highlight the perceived importance of AI training, organizational preparedness, and governance frameworks in maximizing implementation benefits. This study contributes to business analytics, operations management, and decision sciences by providing empirical insight into AI-enabled supply chain transformation. The findings offer practical implications for managers, policymakers, and industry stakeholders seeking to strengthen AI readiness, improve operational efficiency, and promote responsible AI adoption for sustainable supply chain excellence.
Denise Nalini, Dr. S.Barathi, Dr. Rubidhadevi· The Journal of Theoretical A...· 0 citations
In the era of the Fourth Industrial Revolution, the use of artificial intelligence (AI) in human resource management (HRM) is increasingly recognized as a powerful tool for improving organizational performance and efficiency. However, despite growing interest in this area, there is still limited and fragmented evidence explaining exactly how AI adoption leads to these improvements. Guided by the Technology Acceptance Model (TAM), the Resource-Based View (RBV), and Dynamic Capabilities Theory (DCT), this study investigates how AI adoption in HRM contributes to organizational performance and efficiency through improvements in HR process efficiency. A cross-sectional survey was conducted among 452 HR personnel and employees working in information technology (IT)-related organizations in Lagos State, South-West Nigeria. Three hypotheses were tested using path analysis. The findings reveal that AI adoption in HRM is positively associated with both organizational performance and organizational efficiency. In addition, HR process efficiency was found to play a mediating role in these relationships, indicating that improvements in HR processes are a key pathway through which AI generates organizational benefits. Overall, this study contributes to the HRM and information systems literature by providing deeper insight into AI-enhanced HRM and offering evidence to support the integration of AI into organizations’ day-to-day operations.
O. Akintola, S. O. Chukwuedo, Imad Yasir Nawaz et al.· Journal of Business and Digi...· 0 citations
Aim: The objective of this article was to systematically analyse the literature on AI-related competencies of project managers and assess how these competencies were addressed in the context of project management. Methodology: The study was conducted in accordance with the PRISMA 2020 guidelines, using bibliometric analysis (VOSviewer) and qualitative content analysis. The bibliometric analysis included 38 publications, and the qualitative analysis covered 26 works, coded into four competency categories: technological, cognitive, decision-making, and ethical-organisational. Results: The literature focuses primarily on the technological dimension of AI, while project managers' competencies are only marginally and inconsistently described. Technological and decision-making competencies dominate, cognitive and ethical-organisational competencies remain underdeveloped, and there is no consistent model of AI competencies for project managers. Implications and recommendations: Project management competency models should be expanded to include AI-related competencies, such as AI literacy, data work, algorithmic decision-making, and technology ethics. The DigComp 2.2 framework can support their systematisation. Originality/value: The article identifies the gap between the growing role of AI and current project management competency models and outlines directions for further research.
Katarzyna Marek-Kołodziej· Prace Naukowe Uniwersytetu E...· 0 citations
In modern industrial arena Artificial Intelligence (AI) has become the integral tool to escalate the organizational performance such as improving operational efficiency, effective decision making and achieving sustainable competitive advantage. In the area of Human Resource Management (HRM), AI has been an indispensable part specially in the sector of staffing and recruitment, employee training and motivation, employee performance measurement, ensuring proper industrial relations and managing diversified workforce. However, in spite of enormous use of AI tool is HRM sector, there is not enough evidence that it creates significant impact on the enhancement of employee performance in an organization. This study examines the relationship between adopting AI in the sector of HRM to measure the organizational performance. Based on the Resource-Based-View (RBV) and Technology-Organization-Environment (TOE), the study states a theoretical model aligning AI adoption, AI aided HRM practices, organizational and employee performance. In this research design quantitative approach have been used where structured questionnaire were the main tool to gather data from various HR experts from various industries. In this study 380 respondents have been taken as sample and data were analyzed via spss and smart PLS to evaluate the reliability, validity and the effects of mediation. It is probable that uses of AI will have a positive impact in the employee and industrial performance. However, AI aided HRM has shown an enormous implication in the overall activities of an industry not fully but partially. The findings of the study expected to widen the opportunity further in the near future so that AI aided HRM activities can further perform better to achieve an organizations objective as smoothly as possible. This study has also shown the practical procedures for future leaders or managers to find a gateway from all the odds that may arise from this type of situation.
S. Siddiquee· International journal of res...· 0 citations
Humanitarian projects in conflict zones face extreme complexity caused by, inter alia, volatility, fragmentation, and accountability pressures. Such complexity often renders conventional project implementation approaches inadequate. This study, focused on the conflict zone of North-West Nigeria, investigated the extent to which artificial intelligence (AI) tools can enhance the effectiveness of management governance and governance of humanitarian projects. Grounded in sociotechnical systems (STS) theory, the study surveyed 300 project personnel across Kebbi, Katsina, and Jigawa States, and conducted interviews with 25 of the personnel. Statistical analysis of the quantitative data from the survey found that the adoption of AI tools had a statistically significant correlation with project management effectiveness (β = .46, p < .001), with organisational readiness and ethical governance found to serve as significant partial mediators. The qualitative findings from the interview data identified AI tools’ positive roles in project management and governance—through support for (human-led) decision support, transparency, and anticipatory governance—but also revealed tensions around equity, attentional displacement, and the marginalisation of national actors.
Akaninyene Unaam, Etini A. Unaam· The African journal of infor...· 0 citations