Revolutionizing Business Practices Through Artificial Intelligence And Data Rich Environments

Throughout the world, artificial intelligence is reshaping businesses, trade interfaces, economic activities, and society as a whole. In recent years, scholarly research on artificial intelligence has emerged from a variety of empirical and applied domains of knowledge. Computer scientists have developed advanced deep learning algorithms to leverage its utility in a variety of fields such as medicine, energy, travel, education, banking, and business management. Although a growing body of literature is shedding light on artificial intelligence-enabled difficulties, there is still much to be gained by applying fresh theory-driven techniques to this vital topic. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments provides a comprehensive understanding of the business systems, platforms, procedures, and mechanisms that underpin different stakeholders' experiences with reality-enhancing technologies and their transformative application in management. The book also identifies areas in various business processes where artificial intelligence intervention would not only transform the business but would also make the business more sustainable. Covering key topics such as blockchain, business automation, and manufacturing, this reference work is ideal for computer scientists, business owners, managers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Blockchain technology provided a buzz-seeking opportunity for all industries to implement improved corporate procedures and trust-building. Still, some industries, such as the banking sector, may view it as a disruptive technology that must be adopted. A transaction ledger’s contents can be verified, maintained, and synchronized by community members using blockchain technology. A transaction can never be changed or removed from the blockchain; updates may only be made by participants in the system. Its distributed database cannot be manipulated, disrupted, or hacked in the same manner as conventional, user-controlled access systems and centralized databases. Building Secure Business Models Through Blockchain Technology: Tactics, Methods, Limitations, and Performance studies and explores the status of blockchain technology and, through the latest technology, builds business models to secure the future direction in the field of business. This book discusses the tactics and methods, as well as their limitations and performance. Covering topics such as AI-based efficient models, digital technology and services, and financial trading, this premier reference source is a valuable resource for business leaders and managers, IT managers, students and educators of higher education, entrepreneurs, government officials, librarians, researchers, and academicians.

The relentless growth of data in financial markets has boosted the demand for more advanced analytical tools to facilitate and improve financial planning. The ability to constructively use this data is limited for managers and investors without the proper theoretical support. Within this context, there is an unmet demand for combining analytical finance methods with business analytics topics to inform better investment decisions. Advancement in Business Analytics Tools for Higher Financial Performance explores the financial applications of business analytics tools that can help financial managers and investors to better understand financial theory and improve institutional investment practices. This book explores the value extraction process using more accurate financial data via business analytical tools to help investors and portfolio managers develop more modern financial planning processes. Covering topics such as financial markets, investment analysis, and statistical tools, this book is ideal for accountants, data analysts, researchers, students, business professionals, academicians, and more.

In today's rapidly evolving landscape, AI has become an indispensable tool for organizations seeking to enhance their understanding of customers, boost productivity, and foster stronger connections with their target audience. The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics is a comprehensive and timely exploration of the integration of artificial intelligence (AI) into the field of digital marketing. Authored by experts in the field, this book delves into the profound and far-reaching changes that AI is bringing to the digital marketing arena. It provides a detailed examination of how organizations can leverage AI technologies to gain a competitive edge in the market. By mastering these new technologies, companies can effectively navigate the dynamic digital landscape, optimize their marketing strategies, and deliver highly personalized content to their customers. Ideal for a wide range of audiences, including researchers, teachers, students, and executives, this book serves as a vital resource for those seeking to stay ahead of the curve in the ever-evolving world of digital marketing. Through its comprehensive coverage of AI applications in the field, it equips readers with the knowledge and insights necessary to make informed decisions, develop effective marketing strategies, and drive business growth.

Digital evolution has become increasingly present in our lives, whether on cellphones, computers, watches, or other appliances. As a result of the wide access we have to the digital world, the amount of data generated daily is vast. This density of information generated at every moment can be the insight needed for the success of an organization. Much is said about data-based decision-making to generate the best results. The new capabilities of data intelligence unleashed by the emergence of cloud computing and artificial intelligence make it one of the most promising areas of digital transformation change management. Enhancing Business Communications and Collaboration Through Data Science Applications provides relevant theoretical frameworks and the latest empirical research findings in the area. It is written for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. Covering topics such as data science, online business communication, and user-centered design, this premier reference source is an ideal resource for business managers and leaders, entrepreneurs, data scientists, data analysts, sociologists, students and educators of higher education, librarians, researchers, and academicians.

In the modern data-driven era, artificial intelligence (AI) and machine learning (ML) technologies that allow a computer to mimic intelligent human behavior are essential for organizations to achieve business excellence and assist organizations in extracting useful information from raw data. AI and ML have existed for decades, but in the age of big data, this sort of analysis is in higher demand than ever, especially for customer support and analytics. The Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics investigates the applications of AI and ML and how they can be implemented to enhance customer support and analytics at various levels of organizations. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, deep learning, customer sentiment analysis, data mining, neural networks, and business analytics.

Artificial intelligence (AI) is becoming a reality for pioneering organizations while they are facing complex and multifaceted aspects of business sustainability with ambiguous and changing ethical norms and vague or nonexistent legislation. The first quarter of the 21st century was identified as the beginning of the continuous, ongoing, and accelerating wave of simultaneous general purpose technologies revolutions causing accelerated shrinkage of the half-life of knowledge. Cases on Enhancing Business Sustainability Through Knowledge Management Systems presents teaching case studies exploring the formulation and implementation of knowledge management systems (KMS) in organizations. Covering topics such as automation, machine learning, and socio-ecological innovation, this case book is an essential resource for business leaders and managers, IT managers, entrepreneurs, government officials, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Artificial Intelligence for Risk Mitigation in the Financial Industry This book extensively explores the implementation of AI in the risk mitigation process and provides information for auditing, banking, and financial sectors on how to reduce risk and enhance effective reliability. The applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to “transform inputs into output.” As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc. Audience This is an introductory book that provides insights into the advantages of risk mitigation by the adoption of AI in the financial industry. The subject is not only restricted to individuals like researchers, auditors, and management professionals, but also includes decision-making authorities like the government. This book is a valuable guide to the utilization of AI for risk mitigation and will serve as an important standalone reference for years to come.