The purpose of this paper was to investigate technologies, methods, and approaches that can be used to effectively manage smart city risks in the context of the COVID-19 pandemic. The paper was based on a review of specialized literature sources and expert statements on smart cities in times of crisis, specifically during COVID-19. A systematic literature review served as the research’s methodological foundation; this was supplemented by conceptual data analysis techniques and a modeling method. Our initial search yielded 234 research articles, 38 of which met our inclusion criteria and were included in the review. A further 32 studies fell outside of the criteria for supporting smart cities’ crisis management. The main findings showed that technologies can respond quickly to pandemic crisis risks while also ensuring the availability of urban functionality and that there are numerous risks in implementing technologies to achieve effective management. The main risks were privacy concerns, social inclusion, political bias, misinformation and fake news, and technical difficulties with education and distance employment. The practical significance of the paper lay in proposing a model based on specific technologies and policies aimed at effective risk management in the days of COVID-19.

Introduction. Artificial intelligence (AI) refers to a wide spectrum of breakthroughs that offer multiple advantages to companies in terms of increased sales. Considering the abundance of data and the significant increase in computational resources, organisations have rapidly turned to artificial intelligence (AI) to create financial benefits. Nevertheless, businesses continue to discover it is challenging to implement and employ AI in their everyday activities. Therefore, a comprehensive understanding is required due to the absence of an integrated comprehension of how artificial intelligence creates business value and what kind of corporate worth is anticipated. Aim and tasks. The study aims to review value-generating methods and explain how enterprises might use AI technology in their business activities. To accomplish its main aims, this study offers a thorough literature review. The working hypothesis claims that the use of AI can increase business value. Results. This study examines the research capabilities of AI, its use in the corporate environment, and its initial and secondary impacts. The impact of AI includes process efficiency, generating insights hidden in huge amounts of data, and transforming business processes in terms of procedural actions, operational efficiency, financial efficiency, market efficiency, and sustainability in terms of company profile. In addition to the favourable impacts, several recent cases have shown that unwanted and undesired consequences may develop in the absence of effective management procedures. These effects hurt the reputation of the businesses concerned and, in certain cases, resulted in huge fines and financial losses. Such findings increase the responsibility of AI enterprises to incorporate solutions that reduce the bias in data and algorithms at every stage of implementation. Conclusions. The role of artificial intelligence in the corporate environment in value creation and operational efficiency is extending. AI technologies can be used by companies to increase automation of corporate processes without direct interaction with customers, including applications that mean the use of AI in customer-facing services and products. Learning about the means by which AI might be employed will assist businesses in generating rational choices regarding the strength of implementing technologies in the supply chain. Assessing the possible implications of AI acceptance of artificial intelligence may enable firms to plan more successfully on a technology’s launch.

In the contemporary landscape marked by the pervasive influence of artificial intelligence (AI), technological innovations continue to reshape conventional practices across various domains. Within the realm of human resources management, the intricate process of decision-making has long posed challenges in terms of analytical elucidation. However, the advent of AI technologies has ushered in a new era, offering unprecedented opportunities to augment and refine HR administration practices. This paper delves into the transformative potential of AI applications within human resources management, shedding light on how diverse AI modalities, including narrow and general AI, are revolutionizing traditional approaches. Through a comprehensive review of literature sourced from esteemed databases such as Scopus and Google Scholar, this study identifies key advancements poised to drive future research endeavors. Beyond the realm of recruitment, AI presents a myriad of possibilities spanning talent acquisition, employee training and development, performance assessment, compensation management, engagement initiatives, and even employee well-being programs. The synergy between human capabilities and AI integration emerges as a cornerstone for achieving enhanced outcomes, often serving as a determinant for competitive advantage within organizations while also impacting broader societal dynamics.

Objective: This study aims to investigate the consequences and boundaries of technological innovation's influence on financial literacy in the context of the COVID-19 pandemic. Theoretical Framework: The research investigates the nature of financial literacy and digital financial literacy and its relation to sustainability. Additionally, interrelations between digital financial literacy and Artificial Intelligence and the way COVID promotes digital financial literacy improvement are presented. Method: The research methodology is based on content analysis, comparative analysis and impact analysis. The data collection was carried out through a survey. The survey was carried out using the method of the respondents and the selection included all voluntary respondents. The survey was conducted in an online environment using Google Workspace tools, in particular Google Forms, and was self-administered by the authors. Results and Discussion: The results revealed a positive attitude of users towards digital technologies in the conditions of a pandemic crisis and this inevitably leads to an increase in financial literacy. These results highlight the role of digital financial literacy and technology in achieving better financial behaviour and resilience during the pandemic. They also show the limitations of their effectiveness in certain aspects, such as the formation of financial attitudes. Research Implications: The operational and conceptual consequences of the study are examined, presenting perspectives on how outcomes might be implemented or influenced by methods employed in financial literacy development. These ramifications could include AI adoption, digital culture improvement, and so forth. Originality/Value: This study contributes to the literature by examining the relationship between financial literacy and artificial intelligence in the context of the COVID-19 epidemic. The fast adoption of artificial intelligence and the necessity for increased financial literacy demonstrate the relevance and significance of this research.

The rapid advancement of artificial intelligence (AI) has transformed the digital marketing landscape, particularly with regard to optimising online advertising campaigns. This study explores how AI-driven techniques can enhance the performance and efficiency of digital advertising. It aims to evaluate the impact of machine learning algorithms and automated bidding systems on key performance indicators, such as click-through rate (CTR), conversion rate and return on investment (ROI). The study takes a quantitative research approach, using comparative analysis to compare AI-optimised advertising campaigns with traditionally managed ones across major platforms such as Google Ads and Meta Ads. Data from multiple campaigns is collected over a defined period and analysed using statistical methods, including regression analysis and hypothesis testing. The findings suggest that AI-driven optimisation can greatly enhance campaign performance by facilitating real-time decision-making, precise audience targeting and dynamic budget allocation. Furthermore, the results show that automated systems are more efficient and scalable than manual campaign management. This research makes a valuable contribution to the growing body of literature on AI in digital marketing, providing empirical evidence of the effectiveness of intelligent optimisation techniques. The study also offers marketers practical insights on how to enhance advertising outcomes by integrating AI technologies. Proposed areas for future research include exploring ethical considerations and the long-term sustainability of AI-driven marketing strategies.