Artificial Intelligence (AI) is increasingly reshaping higher education institutions, yet limited evidence exists regarding how AI Technology Adoption contributes to Sustainable Performance. This study examines the relationships among AI Technology Adoption, Transformational Leadership, Innovation Capability, and Sustainable Performance in higher education institutions. Drawing on the Technology-Organization-Environment (TOE) framework, Transformational Leadership Theory, Dynamic Capability Theory, and the Triple Bottom Line (TBL) perspective, a research model was tested using survey data collected from 500 academic and administrative staff across higher education institutions in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. Structural Equation Modelling (SEM) was employed to examine the proposed relationships. The findings reveal that AI Technology Adoption and Transformational Leadership exert positive effects on Sustainable Performance, both directly and indirectly through Innovation Capability. Innovation Capability was also found to partially mediate the relationships between AI Technology Adoption, Transformational Leadership, and Sustainable Performance. By positioning Sustainable Performance as a key institutional outcome, this study extends existing research on AI in higher education beyond technology implementation and demonstrates the role of Innovation Capability in translating technological and leadership resources into Sustainable Performance.
The rapid advancement of artificial intelligence (AI) is transforming higher education by reshaping teaching, research, and institutional management. As universities increasingly adopt AI technologies, effective leadership has become essential for fostering innovation and facilitating successful digital transformation. This study examines the relationship between transformational leadership and faculty innovation, with artificial intelligence integration serving as a mediating variable. A quantitative, cross-sectional research design was employed, and data were collected through a structured questionnaire administered to faculty members from public and private universities. The proposed research model was analyzed using Structural Equation Modeling (SEM). The findings indicate that transformational leadership has a significant positive effect on both AI integration and faculty innovation. Furthermore, AI integration significantly enhances faculty innovation and partially mediates the relationship between transformational leadership and faculty innovation. These findings suggest that transformational leaders create supportive environments that encourage faculty members to adopt AI technologies, thereby improving innovative teaching, research, and academic practices. The study contributes to the growing literature on educational leadership and digital transformation by highlighting the strategic role of AI integration in promoting faculty innovation.
Dr. Ijaz Hussain, Fakhar Abbas, Muhammad Abubakar Zeeshan et al.· TAMSAAL· 0 citations
Artificial intelligence is increasingly transforming organizational decision-making, yet the mechanisms through which AI Leadership contributes to innovation outcomes remain insufficiently understood. Drawing on dynamic capabilities theory, this study examines the relationships among AI Leadership, Digital Capability Development, Human Capital Transformation, and Innovation Efficiency. Data were collected through a cross-sectional online survey administered via the Prolific academic research platform with an international sample of 3416 employees. Exploratory factor analysis, confirmatory factor analysis, and structural equation modeling were then employed using a split-sample validation approach. The results indicate that AI Leadership positively influences Digital Capability Development, while Digital Capability Development positively affects both Human Capital Transformation and Innovation Efficiency. Contrary to expectations, AI Leadership demonstrates a significant negative direct effect on Human Capital Transformation. Mediation analysis reveals that Human Capital Transformation partially mediates the relationship between Digital Capability Development and Innovation Efficiency, whereas Digital Capability Development and Human Capital Transformation jointly provide a significant sequential mediation pathway linking AI Leadership and Innovation Efficiency. The findings suggest that innovation efficiency does not emerge directly from AI Leadership but through a multistage transformation process involving capability development and workforce adaptation. The study contributes to digital transformation and innovation research by demonstrating that innovation efficiency emerges through a sequential organizational transformation process rather than directly from AI Leadership.
Vuk Mirčetić, Aleksandar Ignjatović Pertini, Stefan Milojević et al.· Administrative Sciences· 0 citations
Higher education institutions are experiencing major transformation as digital technologies, data-driven management and knowledge-based economies reshape how universities create and deliver value. Universities increasingly function as complex organizational systems that coordinate knowledge resources, academic services and institutional activities across multiple stakeholders. Within this context, institutional performance depends not only on academic excellence but also on the ability to develop governance capabilities and manage innovation processes effectively. This study examines how leadership, internal control, technological capability and Total Quality Management influence organizational innovation and institutional performance in Christian faith-based higher education institutions in Indonesia. Using a quantitative approach with Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from 213 academic and administrative staff members. The findings indicate that technological capability and quality management play a significant role in enhancing organizational innovation, while leadership and internal control do not have direct effects on performance. Organizational innovation emerges as a key mechanism that mediates the relationship between governance capabilities and institutional performance. These results suggest that institutional performance is achieved through the effective transformation of internal capabilities into innovation outcomes. The study offers a novel perspective by integrating governance mechanisms within an innovation-driven performance framework in faith-based higher education institutions. The study contributes to higher education management literature by demonstrating that technological capability and quality management improve institutional performance mainly through organizational innovation in Christian faith-based higher education institutions.
Yakub Hendrawan, Perangin Angin, A. Buchdadi et al.· International Research Journ...· 0 citations
The growing integration of artificial intelligence (AI) is reshaping leadership practices in small and medium sized enterprises, yet the mechanisms underlying this transformation remain insufficiently explored. This study examines how AI adoption contributes to leadership transformation through improvements in decision quality within SMEs. Drawing on transformational leadership theory and research on responsible AI governance, a conceptual model is tested using survey data collected from 302 leaders of Tunisian SMEs. The analysis employs Partial Least Squares Structural Equation Modeling, which is appropriate for assessing complex mediation and moderation effects. The findings indicate that more intensive AI use enhances decision quality, supporting the development of more participative and future oriented leadership practices. Transformational leadership is positively associated with employee engagement and organizational performance. Moreover, a responsible AI climate strengthens the relationship between AI adoption and leadership transformation, highlighting the importance of ethical and transparent AI governance in supporting sustainable leadership development outcomes globally.
This study adopts a quantitative research design using data collected from 302 leaders of Tunisian SMEs through an online survey. Structural equation modeling (SEM) with the SmartPLS 4 software was applied to test the proposed conceptual model and hypotheses. The model examines the direct effects of AI use on decision quality, leadership transformation, and organizational performance, as well as the moderating role of a responsible AI climate. Reliability, validity and multicollinearity tests were conducted to ensure the robustness of the measurement and structural models.
The results reveal that the use of AI significantly enhances decision quality and promotes transformational leadership among SME leaders. Decision quality partially mediates the relationship between AI use and leadership transformation. Transformational leadership, in turn, has a positive and significant impact on both employee engagement and organizational performance. Furthermore, the presence of a responsible AI climate strengthens the relationship between AI use and leadership transformation. These findings highlight the strategic and ethical importance of AI adoption in fostering effective and adaptive leadership within Tunisian SMEs.
This study is limited to Tunisian SMEs, which may restrict the generalization of findings to other cultural or organizational contexts. The use of a cross-sectional design limits causal inference. Future studies could adopt longitudinal or comparative approaches to validate these results across industries and regions. Despite these limitations, the research provides strong empirical evidence on the role of AI in shaping leadership behaviors. It also opens new avenues for exploring how digital technologies and ethical climates jointly influence managerial practices and organizational development.
The study provides actionable insights for SME leaders and policymakers in emerging economies. It emphasizes that integrating Artificial Intelligence (AI) into managerial processes enhances decision quality, promotes transformational leadership and strengthens employee engagement. Managers should focus on fostering a responsible AI climate that supports ethical use, transparency and trust. Training programs should develop leaders' digital and analytical skills to align technology with human values. These findings guide organizations in leveraging AI strategically to achieve sustainable performance and foster innovation-driven growth.
This study highlights the social value of adopting AI responsibly within small and medium-sized enterprises. By fostering transparent and ethical AI practices, organizations can strengthen trust between leaders and employees, promote fairness in decision-making, and enhance overall workplace well-being. Responsible AI leadership also contributes to reducing resistance to technological change and encourages inclusive participation in digital transformation. Ultimately, the findings underline that ethical and human-centered AI adoption not only drives organizational performance but also supports broader social sustainability and responsible innovation in the digital economy.
This study offers an original contribution by integrating technological, behavioral and ethical dimensions to explain how AI drives leadership transformation and organizational performance in SMEs. It extends transformational leadership theory by introducing decision quality as a key mechanism and a responsible AI climate as a moderating factor. Empirical evidence from Tunisian SMEs provides new insights into how AI adoption fosters ethical, data-driven, and adaptive leadership practices. The research adds value to both scholars and practitioners seeking to align digital innovation with sustainable and human-centered management.
Sana Ouechtati· Leadership & Organizatio...· 0 citations
Artificial intelligence (AI) is the catalyst of digital transformation in project-based industries, though the means by which AI contributes to success in projects are not well understood. The article examines the association between AI adaptability and project success by exploring the mediating mechanism of IT-enabled decision-making and the moderating effects of transformational leadership. Based on Dynamic Capability Theory and Transformational Leadership Theory, a moderated mediation model is developed and empirically tested using quantitative survey data from AI-enabled project professionals. Direct, indirect, and conditional effects among the variables of interest are investigated using Structural Equation Modeling (SEM). SEM was used to analyze survey data from 300+ project professionals. Results indicated that AI adaptability significantly improved project success (β = xx, p < 0.05), while AI-supported decision-making partially mediated this relationship. Transformational leadership further strengthened the indirect effect of AI adaptability on project success. The findings suggest that AI adaptability positively affects project success, and AI-facilitated decision-making partially mediates this relationship. In addition, transformational leadership has a significant moderating effect on the association between AI adaptability and decision-making, such that this moderation is strengthened at higher levels of transformational leadership in mediating the indirect relationship with project success. These outcomes help support the understanding that, in the context of a project, the true value of the implementation of AI is found in the preparation of the organization, the quality of decisions, and the type of leadership support. The research builds on project management and information systems by offering a new integrative framework to understand the effect of technological capability and managerial leadership on project performance. Practically, the outcomes provide companies with opportunities to leverage their AI projects to enhance the success of their future projects.
Umer Iqbal, Atif Ali, Khansa Zaman et al.· UCP Journal of Engineering &...· 0 citations
Digital transformation has intensified the pressure on higher education institutions to achieve sustainable Institutional Competitive Advantage through the effective management of academic resources and digital technologies. Although Knowledge Creation Capability, Academic Innovation Capability, and Research Collaboration Capability have been widely recognized as important organizational capabilities, the mechanism through which these capabilities are transformed into Institutional Competitive Advantage remains insufficiently understood. This study aims to synthesize empirical evidence concerning the relationships among Knowledge Creation Capability, Academic Innovation Capability, Research Collaboration Capability, Institutional Dynamic Academic Capability, AI Adoption, and Institutional Competitive Advantage. A semi-systematic (narrative) literature review was conducted by synthesizing 78 empirical articles published in Scopus-indexed journals between 2020 and 2025. The conceptual synthesis integrates the Resource-Based View, Dynamic Capability Theory, and the Technology-Organization-Environment framework, while Structural Equation Modeling serves as the analytical perspective for interpreting the relationships reported in previous empirical studies. The synthesized evidence indicates that Knowledge Creation Capability, Academic Innovation Capability, and Research Collaboration Capability constitute complementary antecedents of Institutional Dynamic Academic Capability. Institutional Dynamic Academic Capability functions as the central mediating mechanism that transforms academic capabilities into Institutional Competitive Advantage, whereas AI Adoption strengthens this relationship by enhancing organizational adaptability, knowledge utilization, and strategic responsiveness. Based on these findings, this study proposes an integrated conceptual model that advances the understanding of capability-based academic transformation and provides a theoretical foundation for future empirical research and strategic digital transformation initiatives in higher education institutions.
Hari Moektiwibowo, Supardi Tahir· Dinasti International Journa...· 0 citations