In the era of digitization and technical breakthroughs, artificial intelligence (AI) has progressively found its way into the field of customer relationship management (CRM), bringing benefits as well as difficulties to businesses. AI, particularly in the context of CRM, employs machine learning (ML) and deep learning (DL) techniques to extract knowledge from data, recognize trends, make decisions, and learn from mistakes with minimal human intervention. Successful firms have effectively integrated AI into CRM for predictive analytics, computer vision, sentiment analysis, personalized recommendations, chatbots and virtual assistants, and voice and speech recognition. AI-driven chatbots, one of the AI-powered CRM systems, arose as a disruptive approach to customer service, and as such, unfolded with economic and managerial ramifications in CRM. Given the literature’s focus on other AI-driven systems, there is an obvious need for an investigation of industry applications and the implications of AI-driven chatbots in CRM. The purpose of this study is to explore and elucidate the economic and managerial implications of AI-powered chatbots within CRM systems. This investigation aims to provide a comprehensive understanding of how these technologies can enhance customer interactions, streamline business processes, and impact organizational strategies. To reach this goal, this study conducts a comparative qualitative analysis based on many interviews with experts and contributors in the field. Interviews with CRM specialists yielded insights into the use of AI-driven chatbots in CRM and their impact on the industry. The primary advantages identified in this study were the impact of AI-powered chatbots on cost, efficiency, and human performance. In addition, AI chatbots have proven useful in a variety of industries, including retail and tourism. Nonetheless, there were limitations to its usage in the healthcare system, particularly in terms of ethical problems.

This study investigates the interaction of information and communication technology (ICT) and higher education in driving sustainable development, with a special emphasis on the rising significance of generative AI tools such as ChatGPT. This quantitative study, conducted in a Lebanese private university, looks into the impact of ICT, specifically generative AI, on promoting sustainability in higher education. A questionnaire was distributed to university instructors to determine how these technologies contribute to sustainable practices in academic environments. The results, which were evaluated using descriptive statistics and correlation analysis, show that ICT tools, professional instructor development, and the upkeep of educational infrastructure all contribute considerably to Lebanon’s sustainable development. Furthermore, integrating generative AI into educational processes has the potential to improve personalized learning, resource efficiency, and content production, all of which contribute to sustainability goals. The study concludes by exploring the findings’ broader implications, acknowledging their shortcomings, and suggesting future research possibilities.

Because of the advancement of electronic commerce, online shopping has emerged, merging commercial and social activities and enhancing the social presence and value of the online environment. To improve the understanding of the changes in the consumer behavior during the COVID-19 pandemic, this study proposes a set of characteristics connected to the social side of online shopping and their influence on client purchasing attitude in addition to the quality of the platforms that are being used (service quality, system quality and information quality). For this matter, a survey of 289 Lebanese people was circulated in 2021 and a quantitative method was used to answer three research questions. Types of goods purchased and frequency of buying on-line were tested to check the presence of any gender differences, in addition to the relationship between the variables studied in the model. According to the research, social presence, social value, and tendency to compare products on different shopping platforms all have a significant correlation with the attitude towards online shopping, where the system quality was the least significant. When it comes to purchasing frequency and product types, the data gathered imply that gender disparities are considerable. This study does not consider the consumer’s living environment or whether there are any age differences between the generations shopping online.

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Sustainable territorial development seeks to balance economic growth, social well-being, and environmental preservation across spatial contexts. In fragile and resource-constrained regions, achieving this balance remains particularly challenging. With the growing diffusion of artificial intelligence (AI), digital tools are increasingly presented as potential enablers of sustainability-driven territorial strategies. This study explores the role of AI in supporting sustainable territorial development across rural and urban areas of North Lebanon, a region characterized by infrastructural deficits, governance constraints, and socio-economic vulnerability. Adopting a qualitative research design, the study draws on semi-structured interviews with five key stakeholders from the public sector, civil society, business, and sustainability expertise, complemented by an illustrative case study of the proposed AI-enabled redevelopment of Klayaat (René Mouawad) Airport. The findings reveal that while stakeholders recognize AI’s potential to enhance resource optimization, smart agriculture, urban mobility, and disaster preparedness, its effective adoption remains constrained by limited digital infrastructure, insufficient policy frameworks, funding shortages, and gaps in digital literacy. Interpreted through the lenses of the Triple Bottom Line and Diffusion of Innovation theories, the results show that AI-driven sustainability outcomes in fragile territorial contexts are highly conditional on institutional readiness, governance capacity, and contextual alignment. The study contributes to the literature by providing context-specific insights into AI-enabled sustainable development in a developing and crisis-affected region, highlighting the need to complement technological innovation with policy reform, capacity building, and inclusive territorial governance.