Project management plays a critical role in ensuring project success and organizational competitiveness, particularly in Saudi Arabia’s rapidly evolving construction sector. Artificial intelligence (AI) has emerged as a transformative technology with the potential to improve project performance through enhanced operational processes and managerial decision-making. This study examines the impact of AI integration on construction project outcomes (PO), with operational efficiency (OE) and managerial decision-making (MDM) acting as mediating variables. A quantitative research approach was adopted, and data were collected from 216 professionals working in Saudi Arabia’s private construction sector. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings supported all proposed hypotheses, demonstrating that AI integration has a significant positive effect on PO. Furthermore, OE and MDM were found to significantly mediate the relationship between AI integration and PO. The structural model explained 65% of the variance in PO, indicating substantial explanatory power. The findings contribute to the growing body of knowledge on AI adoption in construction project management and provide practical insights for organizations seeking to enhance PO through AI-driven digital transformation initiatives in support of Saudi Vision 2030.

Purpose: This study aims to explore the relationship between artificial intelligence (AI) disclosure and bank profitability, and to assess whether family ownership plays a moderating role in this relationship. It takes into account the trade-off between increased disclosure and near-term profitability pressure, as well as how family ownership reduces that effect. Design/methodology/approach: The study utilizes a balanced panel data of 14 banks included in the Amman Stock Exchange (ASE) for the period 2015–2024, which provides a total of 140 bank-year observations. Ordinary least squares regressions are employed to explore the association between AI-related disclosure and bank profitability, measured by return on assets (ROA) and return on equity (ROE), and the moderating effect of family ownership. In order to mitigate the potential endogeneity concerns and evaluate the robustness of the results, two-stage least squares (2SLS) estimations are conducted. Findings: AI-related disclosure is negatively and significantly associated with bank profitability (ROE and ROA), showing that greater disclosure does not necessarily imply positive financial outcomes. Instead, increased disclosure of AI could signal more aggressive investment, implementation, and organizational change, which can have high upfront costs in the short term before financial gains are seen. Notably, the negative relationship is weaker in family-owned banks, indicating that better monitoring, longer investment time horizon, and greater resource discipline can help mitigate the short-term financial pressures of banks going through transformation due to AI. Originality/value: This study extends the emerging AI disclosure literature by documenting a potential contemporaneous profitability penalty associated with greater AI-related disclosure. To the best of the authors' knowledge, it is among the first studies to examine the adverse profitability implications of AI-related disclosure in the banking sector while simultaneously investigating family ownership as a moderating governance mechanism. It also contributes to the family-business and corporate-governance literature by identifying family ownership as a buffering condition in the AI disclosure–profitability relationship. The findings provide new evidence from an emerging-market banking context that the financial consequences of AI-related transformation depend partly on ownership structure.

Purpose: This study examines how family influence shapes the entrepreneurial passion of next-generation family members in Saudi Arabian family businesses, and asks how gender conditions this relationship. Design/methodology/approach: Adopting a qualitative, multiple-case study design, the authors conducted 17 semi-structured interviews with family members across ten Saudi healthcare-sector family firms. Data were analyzed in two phases: a deductive phase that coded transcripts against the Family Power–Experience–Culture (F-PEC) framework and the dualistic model of passion, followed by an inductive phase that identified emergent themes through constant comparison. Findings: Centralized family power and emotionally over-identified family cultures were associated with obsessive passion, whereas decentralized governance and shared-value cultures were associated with harmonious passion. Gender emerged as a cross-cutting, conditioning influence: female participants more often described their passion as entangled with proving legitimacy and absorbing uneven workloads, particularly under centralized governance. Family experience did not emerge as a salient driver of passion, appearing instead as a taken-for-granted feature of multigenerational firms. Research limitations/implications: Findings are drawn from a single industry and cultural setting and are not statistically generalizable; they offer analytic generalization to similarly collectivist, multigenerational family business contexts. Practical implications: Family governance design, succession planning and gender-inclusive mentorship can be calibrated to cultivate harmonious rather than obsessive passion among next-generation family members. Originality/value: This study extends the F-PEC framework beyond its quantitative origins, integrates it with the dualistic model of passion and surfaces gender as a conditioning, intersecting influence largely absent from prior F-PEC-based research – a data-generated hypothesis warranting further investigation, contributing context-specific insight from an underrepresented Gulf setting.

This case study explores the transformation of a prominent family business operating in the fitness industry in Saudi Arabia as it transitioned from being privately owned to becoming a publicly listed company. By prioritizing strong governance systems, the family has maintained their influence while ensuring professionalism. Their significant investment in digitization has resulted in enhanced operational efficiency, enriched customer experiences, and data-driven decision-making, making the company more resilient. Aligned with Saudi Arabia’s Vision 2030, the company actively promotes public health. Their dedication to human capital development and social responsibility has fostered positive community impacts. Although the company’s environmental initiatives, such as reducing energy and water consumption, are still in their early stages, they reflect a growing commitment to sustainability. The father’s visionary leadership and wisdom are deeply embedded in the company culture, ensuring an enduring legacy of sustainability and adaptability.

The expansion of the knowledge‐based economy has driven rapid growth in the literature on knowledge management (KM) and intellectual capital (IC), covering topics such as learning, business, and innovation. Scholars recognize knowledge as a significant resource that can foster innovation to attain a competitive advantage. However, literature on the role of entrepreneurial orientation (EO) and learning orientation (LO) in enhancing the impact of both KM and IC on innovation is still limited and fragmented. Hence, a theoretical gap in understanding this role limits both theoretical advancement and practical application. Addressing this problem is essential to developing a comprehensive model of how organizations transform knowledge into innovation and ultimately competitive advantage. The study provides empirical evidence on these relationships through a quantitative approach, utilizing a cross‐sectional survey. The sample comprised employees working in the private sector, N = 97. The analysis employed Partial Least Squares Structural Equation Modelling (PLS‐SEM) with SmartPLS to test the hypothesized relations, and IBM SPSS Statistics to conduct descriptive analyses. The findings affirm that EO is a key driver of innovation, emphasizing its central role in channeling knowledge into innovation.