Objective: This study aims to comprehend the current state of integration between artificial intelligence (AI) and the human resources (HR) sector. Specifically, it investigates the implementation of AI in HR, explores the challenges associated with this integration, and examines potential hazards related to data usage, AI's perceived gimmickry, and algorithmic governance. Method: Employing a descriptive research design, this study relies on secondary data as no primary research was conducted. Information was collected from research papers, books, websites, blogs on human resources, and survey reports released by various research groups. Results: The analysis reveals that AI's adoption in the HR sector is still in its early stages despite significant advancements made by start-ups. Challenges stem from various factors, including data complexities, the risk of AI being seen as a mere gimmick, and concerns about algorithmic governance. The multifaceted nature of AI introduces diverse approaches and applications, from algorithms to deep learning and natural language processing. The study also differentiates between strong AI (general intelligence) and weak AI (problem-specific intelligence). The study emphasizes that HR is a pivotal element of any business, directly impacting employee well-being, communication, and productivity. The integration of AI has brought notable improvements by automating low-value HR tasks, freeing resources for strategic work. AI's capacity to analyze vast data volumes rapidly promises enhanced employee experiences across talent management and recruitment. Conclusions: In conclusion, AI's integration into the HR sector is still evolving, with both promise and challenges. The study underscores the need for addressing the complexities of data utilization, avoiding AI's reduction to mere gimmickry, and establishing responsible algorithmic governance. By understanding the nuances of AI integration in HR, organizations can leverage its potential to enhance productivity, communication, and employee experiences.

Objective: In India, incorporating structural transformation in corporate social responsibility for achieving sustainable development goals in the Covid-19 Pandemic has become a priority. Therefore, the present article aims to review the corporate social responsibility activities conducted by Nine Indian companies (two public sector organizations and seven private sector organizations) towards attaining Sustainable Development Goals in times of global pandemic.   Method: For our research, we chose India since it was one of the earliest and worst-hit countries during the recent pandemic. Even though huge Asian corporations are a minority, It is a good fit for our study goal for various reasons. Less and medium-sized businesses, on the other hand, have a far smaller influence on society, Due to their prominence in the press, clients or consumers are more likely to provide feedback if they are proactive. As a second point, major companies have greater resources (e.g., human and financial) to spend on reporting and distributing social and environmental information. The existing study applied bibliometric analysis in the exploratory research. The data collection done through secondary sources in which articles extracted with the use of PRISMA flowchart.   Result: The study's findings state that most selected Indian Companies spend Rupees 50-1000 crores as corporate social responsibility activities and contribute to the Pradhan Mantri Relief Fund as a business response to face challenges in times of pandemic. Moreover, private companies spend more on CSR activities than public companies in India. The study provides suggestions to the government to make the corporate social responsibility activities compulsory for all the profitable companies so that country can maintain a corporate pool of contingent funds that can utilize to meet such times of critical circumstances.   Conclusion: Companies are taking steps to ensure the safety and protection of their personnel. This has been reflected in corporate social responsibility initiatives as well. Corporate social responsibility efforts must include pushing for and facilitating access to health insurance programmes and other equity indicators as a result.

Background: The use of ChatGPT in the learning process is becoming a common practice. Researchers identify opportunities to improve the learning process using AI tools. At the same time, there are many unresolved problems and threats from the use of ChatGPT. These include unreliable information, false information, lack of references to primary sources, lack of intellectual property protection, and especially the problem of plagiarism in academic texts. Objectives: The purpose of the study is to summarise the results of published research on the benefits and threats of using ChatGPT in higher education and to analyse the experience of using AI to write academic assignments by university students in compliance with the requirements of academic integrity. Methods: A survey was conducted among Kyiv National Economic University named after Vadym Hetman (KNEU) students about their experience of using ChatGPT in performing academic tasks and the degree of satisfaction with this tool. Results: The survey involved 58 KNEU students. We have analysed how satisfied students are with using ChatGPT for different learning purposes. Students are most satisfied with using ChatGPT to quickly find information and translate texts. The majority of respondents said that ChatGPT does not always provide accurate and reliable information. Students also pointed to the problem of violating academic integrity when using ChatGPT to complete their assignments. Conclusions: The study shows the general advantages and disadvantages of using ChatGPT in higher education. Particular attention should be paid to the level of borrowing in academic texts prepared with the help of ChatGPT.

Civil Aviation Industry is one of the fastest-growing industries in India. Passengers are most concerned about their choice of airlines for their travel purposes. This research paper mainly focuses on identifying the influence of service quality on customer satisfaction with low-cost carriers in India. The study also explores the gap between low-cost air carriers in India regarding the overall quality of airline service efficiency, customer satisfaction, and other selected attributes. The research is based on a literature review and an initial interpretation of a survey primarily designed to classify the views of passengers who have flown in Indigo, AirAsia, Go Air and SpiceJet. This study would allow Airlines to understand what passengers expect from airlines regarding service quality and provide input to service providers.

Objective: The objective of this research paper is to explore the potential of artificial intelligence (AI) in enhancing and fortifying cybersecurity measures. In light of the increasing cyber threats and the limitations of traditional computer security systems, the paper aims to shed light on the concept of AI and its components. The central goal is to demonstrate how AI can be leveraged to improve cybersecurity, focusing on key areas such as machine learning, data mining, in-depth learning, and expert programs. Method: This research paper utilizes a literature review approach to investigate the intersection of artificial intelligence and cybersecurity. It involves analyzing existing scholarly works and studies to understand the challenges posed by evolving cyber threats and the limitations of conventional security systems. The paper identifies various components of AI that have the potential to enhance cybersecurity measures and delineates their applicability in the digital landscape. Results: The analysis of past literature emphasizes the growing significance of adopting artificial intelligence techniques to bolster cybersecurity practices. The results underscore the inadequacies of traditional security systems in predicting and countering the ever-evolving tactics of cyber attackers and terrorists. Through an examination of various AI components, including machine learning, data mining, in-depth learning, and expert programs, the paper demonstrates the potential benefits that these technologies can offer to the field of cybersecurity. Conclusions: In conclusion, this research paper highlights the escalating threats to cybersecurity in the face of rapid technological advancement. The imperative of addressing these challenges through AI becomes evident as traditional security systems prove insufficient. By harnessing the power of artificial intelligence techniques such as machine learning, data mining, in-depth learning, and expert programs, institutions can significantly enhance their cybersecurity capabilities. The paper underscores the need for a paradigm shift towards AI-driven cybersecurity strategies to effectively predict, prevent, and counteract cyber threats in the digital age.

Despite the growing recognition of Artificial Intelligence (AI)’s potential for global education, the literature lacks strategic analyses on how to maximize personalized learning and ensure equitable access within the vast and diverse Indian educational system. The objective of this study is to analyze this strategic integration of AI into the Indian educational system, focusing on maximizing personalized learning and ensuring equitable access across diverse socioeconomic contexts, while evaluating current initiatives and the relevance of reporting guidelines, such as the use of Self-Sovereign Identity (SSI). The methodology employed bibliographic and documentary research, alongside the analysis of governmental and sectoral policies. The results indicate that the sustainable implementation of AI is critically dependent on the mitigation of algorithmic bias and the rigorous assurance of data privacy. In conclusion, to balance technological innovation with human-centered pedagogical approaches, maintaining the educator’s fundamental role and fostering collaboration among stakeholders for responsible governance are essential.