In the digital landscape, where innovation knows no bounds, generative artificial intelligence (Gen AI) emerges as a true virtuoso, orchestrating a seamless symphony of creative wonders. Artificial intelligence that can generate fresh and plausible images, texts, and motion graphics rapidly is called Generative AI. It possesses the remarkable ability to effortlessly transform prompts into a rich tapestry of visual art, evocative prose, dynamic videos, and an array of captivating media. This chapter embarks on an exploratory journey, delving deep into the profound influence that Generative AI wields across a diverse spectrum of industries. Through an immersive exploration of these remarkable used cases, this chapter offers a glimpse into the boundless potential and the promises that Generative AI holds, positioning itself as a versatile catalyst for progress within the expansive industrial landscape.
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Artificial Intelligence (AI) embodies the artistry and engineering of creating intelligent machines, infusing them with the essence of intelligence and ingenuity (McCarthy et al., 1955). Whereas, Generative AI, a captivating offspring within the realm of Artificial Intelligence, transcends mere programming and becomes a digital art of novelty. Generative artificial intelligence, also known as GenAI, is a collection of codes and algorithms designed to develop the most plausible responses to a problem at hand. According to Morgan Stanley, this emerging technology has the potential to enable tech companies to access approximately $6 trillion in offline expenditure (Morgan Stanley, 2023). Generative AI harnesses the potency of a specific branch of deep learning, known as generative adversarial networks (GANs), to craft original content that springs forth from the interplay of creative forces. Among the array of generative AI platforms, notable examples encompass ChatGPT, Google Bard, DALL-E, and Musico, each a testament to the spectrum of AI-driven creativity. New forms of content such as text, images, music, audio, and videos can be created with the help of Generative AI. It can be used to generate more realistic images of people, music, and codes. Hence, Generative AI, including Large Language Models (LLMs), possesses the remarkable capability to fabricate highly realistic simulations of real-world data, extending its creative capability beyond traditional boundaries. Through the sophisticated algorithms and immense data-driven learning, Generative AI models like LLMs excel at understanding the underlying patterns and structures within diverse datasets, enabling them to recreate data that mirrors the intricacies of the world we experience. This capability finds application across numerous domains, from generating lifelike images for creative endeavors to crafting contextually rich textual content for natural language understanding tasks, fundamentally reshaping how we interact with and generate data in the digital age.
According to Tiago Bianchi (Generative AI Global Weekly Search Trends on Google 2023 | Statista, 2023), as of February 2022, global online searches related to “generative AI” had shown a consistent rise over the preceding six months. Notably, the search volume for terms associated with generative artificial intelligence surged to a popularity score of one hundred (100) index points during the week commencing February 12, 2023. This heightened interest in “Generative AI” closely correlated with the launch of ChatGPT, an AI chatbot model developed by the United States-based research company OpenAI in November 2022. Despite ChatGPT's significant global recognition since its debut, a substantial 55 percent of surveyed U.S. adults reported having no prior knowledge of this AI-powered chatbot. Another issues associated with the use of Gen AI are related with ethical, privacy, security concerns. Hackers can invade the individual privacy, security and may create harmful content with unethical use of AI. Further this technology can create serious impact of employment status, misinformation, plagiarism and copyright infringements (Lawton George, 2023). At present, knowledge about the utilization of Generative AI is confined to selective fields, resulting in a limited availability of comprehensive literature (Gozalo-Brizuela & Garrido-Merchán, 2023; Weisz et al., 2023). The primary objective of this chapter is to address the existing gap in literature concerning the applications of Generative AI. In-addition this chapter seeks to systematically explore the prominent authors and document the pertinent uses of Generative AI across various fields associated with its application. The overarching goal is to provide readers with a thorough understanding of how Generative AI is integrated into diverse domains. By elucidating the multifaceted applications of Generative AI, this chapter aims to contribute valuable insights that will not only fill the existing void in literature but also empower readers to gain a nuanced and precise comprehension of the role Generative AI plays in different fields. Through a comprehensive exploration of its relevant uses, the chapter endeavors to shed light on the intricate intersections between Generative AI and various industries, fostering a more informed and insightful perspective among readers.
Figure 1.
Global online searches over generative AI