Synopsis
As organizations grapple with the challenges of a dynamic market, the integration of Artificial Intelligence (AI) emerges not only as a technological progression but a strategic necessity. The transformative potential of AI, particularly through OpenAI, holds the promise of redefining operational paradigms, accelerating innovation, and unlocking unprecedented growth opportunities. However, lurking beneath this promise are challenges that demand urgent attention - from tailoring relevance for specific business units to ethical and safe integration practices. The specifics of how OpenAI can amplify labor productivity and enhance decision-making processes remain elusive. Generative AI and Multifactor Productivity in Business offers a guide surrounding the complexities of OpenAI's role in business operations. It contends that understanding OpenAI is not just beneficial; it is essential for organizations seeking to navigate economic uncertainties and unlock high levels of efficiency and growth. The book delves into the effects of OpenAI on business, with a primary objective of illuminating the scholarly and practitioner-based contributions that push the boundaries of OpenAI in business research. This exploration encompasses applications of advanced generative AI tools, language models, and innovative technologies specific to diverse businesses across sectors, scales, and regions. It emphasizes that as AI becomes more seamlessly integrated into business processes, the potential for multifactor productivity to fuel economic growth, new industries, and job opportunities is unparalleled. The book caters to businesses, industry leaders, academics, researchers, and policymakers. It beckons readers into a world where empirical and theoretical research converge to shape the future of OpenAI and multifactor productivity. With a wide variety of recommended topics, spanning from international business and global economic dynamics to labor market adaptation, ethical implications, and environmental sustainability, the book establishes itself as a resource for anyone seeking to understand, navigate, and capitalize on the intersection of OpenAI and multifactor productivity in the ever-evolving landscape of business.
About the Authors
Festus Fatai Adedoyin is a Fellow of the Higher Education Academy, a Chartered Management and Business Educator, and a lecturer at the Department of Computing and Informatics, Bournemouth University, U.K. Festus leads the Economics of Information Security, Integrated Digital Healthcare Projects, and the Individual Masters Project Units at the department. His current research interest is in the application of Machine and Deep Learning, and Econometrics tools to research stories in Energy and Tourism Economics as well as Finance and Digital Health.
Bryan Christiansen is the Chief Executive Officer of Global Research Society, LLC in Michigan, USA. A former business lecturer at universities in Russia, Turkey, and the USA, he has traveled to 41 countries where he has conducted international business since 1985 in multiple languages and various industries with Global 500 firms and smaller. Christiansen received his Bachelor of Science degree in Marketing at the University of the State of New York in 1996 and his MBA degree at Capella University in 2003. The author of 22 Scopus-indexed Reference books on business, cultural studies, economics, and psychology, he is fluent in Chinese, Japanese, Spanish, and Turkish. Christiansen is currently working with a Russian theoretical mathematician on a new economic model for developing nations.
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