This research investigates the relationship between Generative Artificial Intelligence (GAI), media content, and copyright laws. As GAI technologies continue to evolve and permeate various aspects of the media landscape, questions regarding the creation and protection of intellectual property have become paramount. The study aims to highlight the impact of GAI generated content, and the challenge it poses to the traditional copyright framework. Furthermore, the research addresses the evolving role of copyright laws in adapting to the dynamic landscape shaped by artificial intelligence. It investigates whether existing legal frameworks are equipped to handle the complexities introduced by GAI, or if there is a need for legislative and policy reforms. Ultimately, this research contributes to the ongoing discourse on the intersection of GAI, media, and copyrights, providing insights that can guide policymakers, legal practitioners, and industry stakeholders in navigating the evolving landscape of intellectual property in the age of artificial intelligence.

Nowadays, customer service in telecommunications companies is often characterized by long waiting times and impersonal responses, leading to customer dissatisfaction, increased complaints, and higher operational costs. This study aims to optimize the customer service process through the implementation of a Generative AI Voicebot, developed using the SCRUMBAN methodology, which comprises seven phases: Objectives, To-Do Tasks, Analysis, Development, Testing, Deployment, and Completion. An experimental design was used with an experimental group and a control group, selecting a representative sample of 30 customer service processes for each evaluated indicator. The results showed a 34.72% reduction in the average time to resolve issues, a 33.12% decrease in service cancellation rates, and a 97% increase in customer satisfaction. The implications of this research suggest that the use of Generative AI In Voicebots can transform support strategies in service companies. In conclusion, the implementation of the Generative AI Voicebot has proven effective in significantly reducing resolution time and markedly increasing customer satisfaction. Future research is recommended to further explore the SCRUMBAN methodology and extend the use of Generative AI Voicebots in various business contexts.

This study aims to examine the pathways through which the user experience (UX) of ChatGPT, a representative of generative artificial intelligence, affects user loyalty. Additionally, it seeks to verify whether ChatGPT’s UX varies according to a user’s need for cognition (NFC). This research proposed and examined how ChatGPT’ UX affect user engagement and loyalty and used mediation analysis using PROCESS Macro Model 6 to test the impact of UX on web-based ChatGPT loyalty. Data were collected by an online marketing research company. 200 respondents were selected from a panel of individuals who had used ChatGPT within the previous month. Prior to the survey, the study objective was explained to the respondents, who were instructed to answer questions based on their experiences with ChatGPT during the previous month. The usefulness of ChatGPT was found to have a significant impact on interactivity, engagement, and intention to reuse. Second, it was revealed that evaluations of ChatGPT may vary according to users’ cognitive needs. Users with a high NFC, who seek to solve complex problems and pursue new experiences, perceived ChatGPT’s usefulness, interactivity, engagement, and reuse intentions more positively than those with a lower NFC. These results have several academic implications. First, this study validated the role of the UX in ChatGPT. Second, it validated the role of users’ need for cognition levels in their experience with ChatGPT.