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Purpose: This chapter examines the impact of artificial intelligence (AI) on employability and dispels the misconception that AI negatively affects job opportunities. The study aims to shed light on the ways in which AI can enhance employability by complementing natural intelligence and enabling employees to demonstrate creativity in various aspects of their work.

Need for the study: In the 21st century, AI has become ubiquitous, and governments worldwide are actively promoting its integration into various industries and systems. However, concerns about the potential negative consequences of AI have emerged.

Methodology: It is reviewing commentary secondary sources of data viz. books, articles, journals, newspaper articles, reports which have been considered to bring forth the advent of AI being an important premise for the construct of employability

Findings: The findings of this study reveal that the perceived negative impact of AI on employability is a misconception. AI technology, such as Alexa, ChatGPT, and OpenAI, has made significant advancements in the market but is still unable to pass the Turing test. Consequently, it is recommended that AI companies take a pause to fully understand and address the consequences associated with AI implementation.

Practical implications: The practical implications of this study are twofold. First, it debunks the myth that AI jeopardises employability associated with natural intelligence, highlighting the importance of human skills in conjunction with AI technologies. Second, it calls for a strategic approach for organisations and governments to adapt to AI while ensuring the workforce remains adaptable and equipped with the necessary skills. This study provides insights for policymakers, employers, and individuals to embrace AI to augment human potential and improve global market productivity.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

This study offers an in-depth examination of Google Bard, an advanced artificial intelligence chatbot created by Google, focusing specifically on its potential impact on academic research. This discussion aims to comprehensively explore the features of Google Bard, highlighting its capabilities in data management, facilitating collaborative discussions, and enhancing accessibility to complex research. In addition to the aforementioned positive characteristics, we will also delve into the limitations and ethical considerations associated with this innovative device. The functionality of the system is constrained by the limitations imposed by its pre-established algorithms and training data. In addition, there are significant concerns regarding data privacy, potential biases in its responses stemming from its training data, and the wider societal implications associated with a heavy reliance on machine-generated content. Ensuring responsible and ethical utilization of Bard necessitates Google's provision of transparent communication regarding its development process. In light of the prominent functionalities demonstrated by Google Bard, it is imperative for researchers to engage in a rigorous examination of the information it presents, thereby safeguarding against the inadvertent propagation of misinformation or biased viewpoints. This will lay the groundwork for its effective integration into the academic research methodology.

Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

The production of news through artificial intelligence (AI) is a reality in many countries, including the United States, where two leading companies in this area are based. The purpose of this explanatory bibliographic research is to discuss who or what should bear the ethical responsibility for automated writing in a newsroom, considering that codes of ethics address only the conduct of people. This chapter compares the Code of Ethics of the National Federation of Brazilian Journalists with the code used in the United States and highlights examples of news released with incorrect information, produced by algorithms, and published by US news organizations. Facing the current informational scenario, the ethical responsibility of the automated news must be attributed to the media, represented in the figure of the editor. Such a conclusion is motivated by the fact that neither the algorithm nor the person who developed it takes part in the decision-making process of publishing an article or not.