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This study examines the impact of artificial intelligence (AI) on the dynamics and ethics of the workplace environment at PT COLAB PROSPERITY JAYA, a company engaged in the coconut product export industry. Using a qualitative approach, this research involved in-depth interviews with employees at various levels to explore how AI affects work efficiency, decision-making, ethical issues, and employee interactions. The results indicate that AI improves efficiency and supports decision-making with accurate data. However, there are serious ethical concerns, especially regarding data privacy and algorithmic bias. Furthermore, although AI facilitates task management, it also has the potential to reduce social interactions that are crucial for creativity and teamwork. This study suggests the need for stronger policies and ethical training to ensure that AI is integrated in a responsible and fair manner, emphasizing the importance of balancing the benefits of technology with human values in the development and application of AI in the workplace.

In the era of Big Data, securing sensitive information and ensuring data integrity have become paramount concerns due to the unprecedented volume and intricacy of data. Traditional security algorithms face significant challenges in adapting to the distinct characteristics of Big Data. This literature review explores the evolution of data security algorithms tailored explicitly for the Big Data landscape, aiming to address the increasing demand for robust security solutions capable of handling the unique challenges posed by the massive scale and complexity of data. By scrutinizing existing literature, the review unveils advancements, trends, and innovations developed by researchers and practitioners to mitigate vulnerabilities associated with handling vast datasets. The review also sheds light on emerging technologies and cryptographic techniques specifically designed for Big Data security, contributing to enhanced confidentiality, integrity, and availability in the face of evolving cyber threats. While these developments offer advantages such as improved data protection and threat detection, the review highlights challenges, including algorithmic bias, computational complexity, privacy trade-offs, and a shortage of skilled workforce. By considering these factors and emphasizing continuous improvement and ethical considerations, organizations can responsibly leverage data security algorithms to enhance information security in the era of Big Data.

This study is a qualitative literature review aimed at exploring the challenges and opportunities of integrating generative artificial intelligence (GAI) in human resource management (HRM) practices. GAI, as an advanced technology, holds significant potential to enhance operational efficiency in HRM through the automation of administrative tasks, improved accuracy in performance evaluations, and the development of more interactive and adaptive employee training. However, its implementation also faces several challenges, including employee resistance to change and the unpreparedness of technological infrastructure. Furthermore, ethical issues such as algorithmic bias in recruitment processes are a major concern, potentially exacerbating inequities if not properly monitored. This research identifies that the success of integrating GAI into HRM depends on the organization’s readiness to address technological and ethical challenges, as well as the importance of careful planning. The findings provide valuable insights for organizations in designing effective strategies for GAI integration to improve performance and organizational dynamics while addressing potential risks.