The integration of artificial intelligence (AI) into education in the United Arab Emirates (UAE) is moving rapidly as it becomes increasingly mandatory, yet schools often lack the proper expertise and resources to achieve successful implementation. AI integration is not just about having access to AI large language models and supplying schools with the right machines; it is also about ensuring the right preparation before introducing the tools and connectivity. Existing research has primarily focused on technological capabilities or individual attitudes, offering limited insight into how human, organizational, and well-being factors jointly shape institutional readiness. This study examines the determinants of AI adoption readiness in K–12 education using quantitative survey data collected from 602 teachers across public and private schools in the United Arab Emirates. The study builds on the technology–organization–environment framework and behavioral perception theory to test the influence of multiple factors on perceived usefulness. Professional development availability, school encouragement, access to AI tools, work–life balance, teaching experience, and institutional readiness in schools were examined. The findings of this study suggest that cultural readiness is as important as technical readiness. In addition, it underscores the primacy of perception, leadership support, and infrastructure alignment in shaping the transformation. This study presents an empirically tested explanatory framework that may inform policymakers and school leaders seeking to conduct AI transformation. It also offers practical implications for designing professional development, leadership strategy, and implementation models to support sustainable AI integration.

This paper investigates the effects of knowledge assets on firm’s value. Developing knowledge assets has been gaining momentum in recent years under the lens and scope of knowledge management. However, there is an ongoing debate regarding the optimum level and combination of knowledge assets that would lead to firm’s value maximization. The aim of this paper is to provide a resolution to this debate by investigating how knowledge assets affect firm’s value and competitiveness in a real market context. By means of accounting indicators data, an examination is carried out on the identifiable knowledge assets derived from company annual reports. Consequently, the impact on firm’s value over time is explored via multiple regression analysis using panel data. As a result, the optimal structure/balance between internal and external knowledge assets that lead to maximum market value is explored. The main findings show that knowledge assets generate greater firm value when they are coupled with complimentary assets. Additionally, externally acquired knowledge is equally important as knowledge which has been developed from internal research and development efforts. As a result, it is shown that an optimal balance between internal and external knowledge assets leads to greater firm value. Note that while similar studies tend to explore the impact of knowledge assets on various aspects, such as international and innovation performance, little has been done to investigate the impact of knowledge on the overall value of the firm. The presented study is not limited to product development, but it takes into consideration the capitalization of those products in the real market context. Thereby, managerial implications are explored, and suggestions are given on specific structures of knowledge assets that maximize organizational value.