In the Fourth Industrial Revolution (4IR) era, the rapid digitalisation of services poses both opportunities and challenges for the banking sector. This study addresses how adopting artificial intelligence (AI) and online and mobile banking advancements can influence customer satisfaction, particularly in Kaduna State, Nigeria. Despite significant investments in AI and digital banking technologies, banks often struggle to align these innovations with customer expectations and satisfaction. Using Structural Equation Modeling (SEM), this research investigates the impact of customer satisfaction with online banking (C_O) on AI integration (I_A) and mobile banking convenience (C_M). The SEM model reveals that customer satisfaction with online banking significantly influences AI integration (path coefficient of 0.40) and mobile banking convenience (path coefficient of 0.68). These results highlight a crucial problem: while technological advancements in banking are growing, their effectiveness is highly dependent on customer satisfaction with existing digital services. The study underscores the need for banks to prioritise enhancing online banking experiences as a strategic lever to improve AI integration and mobile banking convenience. Consequently, the research recommends that Nigerian banks develop comprehensive frameworks to evaluate and optimise their technology integration strategies, ensuring that technological innovations align with customer needs and expectations in the rapidly evolving digital landscape.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

The need to expand the range of banking services in Ukraine is stipulated with technological progress, the European integration processes and the legal regime of martial law introduced in the country. Under the conditions of war, the need to strengthen the security of banking activities and protect the banking system from the influence of any internal and external factors gains meaning. The topical direction of economic and legal research of scientists today is the possibility to introduce digital technologies with elements of artificial intelligence (AI) into the banking activity in Ukraine to improve its protection. The AI law as an independent branch of the Ukrainian law has not been developed so far. The sources of AI law, its functions, tasks, scope, risks and limits of legal responsibility for prohibited practices of artificial intelligence have not been defined. The purpose of the article is to analyze the theoretical and legal provisions that underpin the regulation of AI application in Ukrainian banking. The comparative legal method made it possible, considering the provisions of the draft law on AI of the European Union, to determine the trends in the development of the legal regulation of AI in Ukraine. Following the study, proposals to the legislation of Ukraine were formulated, which will contribute to the legal regulation of banking activities using digital technologies with elements of AI.

This study conducted a systematic literature review on current and emerging trends in the use of artificial intelligence (AI) for community surveillance, using the PRISMA methodology and the paifal.ai tool for the selection and analysis of relevant sources. Five main thematic areas were identified: AI technologies, specific applications, societal impact, regulations and public policy. Our findings revealed exponential growth in the development and implementation of AI technologies, with applications ranging from public safety to environmental monitoring. However, this advancement poses significant challenges related to privacy, ethics and governance, driving a debate on the need for appropriate regulations. The analysis also highlighted the disparity in the adoption of these technologies among different communities, suggesting a need for inclusive policies to ensure equitable benefits. This study contributes to the understanding of the current scenario of AI in community policing, providing a solid foundation for future research and developments in the field.

This paper mainly discusses the application and impact of AI tools in vocational college students' career planning and employment preparation in Chinese Mainland. Through a review and analysis of relevant literature, this article found that artificial intelligence tools can provide students with more information and assistance, thereby improving their career cognition and employment competitiveness. However, if artificial intelligence tools are not open to Chinese users or students overly rely on these tools, it may also bring some negative effects, such as job anxiety and decreased self-awareness. Therefore, the government and teaching departments should strengthen the education of career planning and employment preparation, improve the artificial intelligence system, establish personalized service mode and other measures to provide more comprehensive and personalized career recommendation and employment services for higher vocational students in Chinese Mainland.