Springer Artificial Intelligence-Augmented Digital Twins: Transforming Industrial Operations for Innovation and Sustainability: 503 (Studies in Systems, Decision and Control, 503)

Presently, we stand on the threshold of a technological revolution that will drastically change the way we live, work, and communicate with each other. By the current rate, scope, and complexity, this transformation will be as fundamental for society as any other technological paradigm change from the past. The industries which are more susceptible to change are technologically oriented industries including banking, finance, accounting, and auditing. One of the technological concepts of the technological revolution is the concept of the digital twin. The application of digital twins and AI as paired with Internet of Things technologies makes it possible to solve ESG problems on a completely different level (Li, 2019) for accounting firms and financial institutions. These include recycling on demand, rational energy consumption, smart surveillance cameras for crime tracking, and smart branch parking solutions, monitoring the wear and tear and conditions of financial technology infrastructures. Moreover, numerous researchers and practitioners emphasize the significance of innovating sustainable business models and operations (Geissdoerfer et al., 2018). The digital twin will allow businesses and financial institutions to minimize costs, boost customer service, and find new ways to generate revenue. DTW is accessible now more than ever, and many reputable and innovative companies such as Tesla, Ericsson, and Siemens have adopted it with varying success. Therefore, this book examines the opportunities, challenges, and risks of artificial intelligence-augmented digital twins for financial operations, innovation, and sustainable development. It focuses on AI and digital twin technologies to furnish solutions for the current industrial revolution including the Metaverse. Henceforth, this book aims to encourage authors to submit multi-disciplinary chapters indicating the current scholarly challenges about the applications and potential of artificial intelligence and digital twins in accounting, finance, and banking.