The study aims to investigate how artificial intelligence (AI) influences women-led startups in Saudi Arabia, aiming to understand their unique experiences, challenges, and opportunities within the AI technology landscape. This study used a qualitative method, conducting 16 in-depth interviews with women entrepreneurs operating businesses in Saudi Arabia. The analysis was performed using thematic analysis with NVivo 12, uncovering key themes and insights. The findings reveal that cultural norms, societal expectations, limited awareness, and financial constraints are directly associated with women’s involvement in AI-driven businesses. Cultural biases emerged as impediments, underscoring the need for targeted interventions such as awareness campaigns and educational initiatives to dismantle ingrained biases and foster an environment that recognizes and celebrates the contributions of women in the tech and AI sectors. Educational programs, collaborations between academia and industry, and mentorship initiatives were identified as pivotal components to prepare women entrepreneurs to navigate the intricate landscape of AI adoption. Financial inclusion emerged as a critical pillar, advocating for equitable access to funding and resources tailored specifically for women-led AI startups. The study further emphasizes the importance of fostering supportive ecosystems that extend beyond financial aid. Creating networks for mentorship, guidance, and collaboration provides women entrepreneurs with platforms to share experiences and resources, enhancing resilience and the potential for success in the AI landscape. Acknowledgment The authors extend their appreciation to the Arab Open University for funding this work through research fund No. AOUKSA-524008.

This study investigates the factor affecting traditional retailer’s intention to opt e-commerce in the context of digital retail business in Saudi Arabia. Employing a cross-sectional survey methodology, structured questionnaires were administered to traditional retailers, providing a snapshot of their perceptions and intentions regarding e-commerce adoption. The data analysis was conducted utilizing the PLS-based structural equation modeling method. The study reveals that perceived usefulness is a pivotal driver, positively impacting the intention to opt e-commerce. Moreover, attitude towards e-commerce is significantly influenced by perceived usefulness and ease of use, highlighting the importance of user-friendly platforms. Conversely, high perceived costs can deter a positive attitude. Overcoming technological barriers is also instrumental, as they can foster a more favorable attitude. Intriguingly, organizational and environmental barriers had limited direct impact on attitude, indicating that internal and individual factors play a more substantial role in shaping the attitudes of traditional retailers in Saudi Arabia. The insights garnered from this research hold substantial significance for the traditional retail industry, government authorities, and all relevant stakeholders invested in facilitating the successful incorporation of e-commerce into Saudi Arabia's established retail sector. This integration is pivotal in ensuring a competitive edge within the dynamic landscape of digital retail. Understanding these factors is vital as the retail landscape continues to evolve, bridging the gap between traditional and digital retail models.

This study aims to examine how employee involvement, leadership, and innovation-related actions are linked in small businesses in Saudi Arabia. As Saudi Arabia works on diversifying its economy and considers innovation essential for growth, this research seeks to identify key factors and processes that promote innovation in companies. A survey was conducted across different small businesses in Saudi Arabia to gather information from employees. Advanced statistical methods, like structural equation modeling (SEM), were used to analyze the data and understand the relationships being studied. The results show a strong, positive link between how engaged employees are and their innovation-related actions in Saudi Arabian small businesses. The study also reveals how crucial leadership is in this process, demonstrating how leaders can either encourage or hinder employees' ability to contribute to innovation. These findings are useful for small business owners and leaders in Saudi Arabia, guiding them on how to foster an environment that supports innovation and improves their competitive edge in the global market. This research is also valuable for policymakers, business leaders, and academics interested in promoting innovation and long-term growth in this vital part of Saudi Arabia's economy.

This study investigates the relationships between women economic empowerment, self-efficacy, and women technology entrepreneurship intention among women operating online businesses in Saudi Arabia. A cross-sectional study design was utilized, with data collected from 256 women entrepreneurs engaged in various online business ventures through a convenience sampling technique. This sample was chosen due to its direct relevance to the study’s objective of understanding the entrepreneurial intentions of economically active women in the digital space. The analysis, conducted using structural equation modeling, revealed several important findings. Women economic empowerment was found to have a significant positive effect on self-efficacy (β = 0.607), indicating that increased economic resources and opportunities enhance women’s confidence in their abilities. Additionally, self-efficacy was identified as a significant predictor of women technology entrepreneurship intention (β = 0.44), suggesting that women with higher self-confidence are more likely to pursue technology entrepreneurship. Moreover, women economic empowerment was found to have a direct effect on technology entrepreneurship intention (β = 0.351). Importantly, self-efficacy mediated the relationship between economic empowerment and entrepreneurial intentions (β = 0.267), highlighting that economic empowerment influences entrepreneurial aspirations both directly and indirectly through its impact on self-efficacy. These findings underscore the importance of economic support and confidence-building initiatives in promoting technology entrepreneurship among women. The study suggests that targeted policies and programs should focus on enhancing economic opportunities and building self-efficacy to foster greater participation in technology entrepreneurship. AcknowledgmentThe authors extend their appreciation to the Arab Open University for funding this work through research fund No. (AOUKSA-524008).

This study explores the interplay between artificial intelligence (AI), leadership, employee engagement, and economic performance within the manufacturing sector of Saudi Arabia. Adopting a cross-sectional design, data was collected in March 2025 from employees using an online survey questionnaire. Convenience sampling was employed to gather responses from a diverse workforce, ensuring accessibility and feasibility. Data analysis was conducted using Structural Equation Modeling (SEM) with SmartPLS to examine the hypothesized relationships. The findings reveal that AI significantly influences leadership and employee engagement, highlighting its role as a strategic enabler in enhancing decision-making, innovation, and employee motivation. Leadership, in turn, positively impacts economic performance, while employee engagement shows a strong direct effect on economic performance. The study also identifies significant indirect effects, where AI influences economic performance through leadership and employee engagement. These results underscore the importance of integrating AI with effective leadership practices and a culture of engagement to drive organizational success. The study highlights AI's indirect effects on organizational dynamics and offers practical insights for leveraging AI to enhance leadership, employee engagement, and economic outcomes. For organizations in the manufacturing sector and beyond, the findings highlight the need for a holistic approach to AI implementation, combining technological innovation with human-centric strategies to achieve sustainable growth and competitive advantage.