If you want to scale your business using Artificial Intelligence tools and applications, then read below Artificial Intelligence is the tech of the future. But if you're not already working in the field or studying the depths of artificial intelligence, it can be difficult to find information in layman's terms. As a business owner, especially a small business owner, we are always looking at ways to improve the efficiency of our business; outsource, automate and scale. And Artificial Intelligence is the best tool to do use. Here's a few things you can learn from this book How current day businesses use Artificial Intelligence to move ahead4 Ways AI can help elevate your online marketing systemsUse AI to make your customers feel like they are in heaven3 Ways to Automate boring tasks with AIEnsure more efficient business compliance methods with AIHow Artificial Intelligence will Change the Nature of Business in the Future If you're ready to have a tool that breaks down this complex topic in simple language then this is your chance. Download your copy now so you can get started on what is promising to be a most amazing future.

During these uncertain and turbulent times, intelligent technologies including artificial neural networks (ANN) and machine learning (ML) have played an incredible role in being able to predict, analyze, and navigate unprecedented circumstances across a number of industries, ranging from healthcare to hospitality. Multi-factor prediction in particular has been especially helpful in dealing with the most current pressing issues such as COVID-19 prediction, pneumonia detection, cardiovascular diagnosis and disease management, automobile accident prediction, and vacation rental listing analysis. To date, there has not been much research content readily available in these areas, especially content written extensively from a user perspective. Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning is designed to cover a brief and focused range of essential topics in the field with perspectives, models, and first-hand experiences shared by prominent researchers, discussing applications of artificial neural networks (ANN) and machine learning (ML) for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence. It also presents summaries of currently available open source software that utilize neural networks and machine learning. The book is ideal for professionals, researchers, students, and practitioners who want to more fully understand in a brief and concise format the realm and technologies of artificial neural networks (ANN) and machine learning (ML) and how they have been used for prediction of multi-disciplinary research problems in a multitude of disciplines.

This new book provides a valuable overview of how artificial intelligence (AI) applications are transforming global businesses and financial organizations, looking at the newest artificial intelligence-based solutions for e-commerce, corporate management, finance, banking and trading, and more. Chapters look at using AI and machine learning techniques to forecast and assess financial risks such as liquidity risk, volatility risk, and credit risk. The book also describes the use of natural language processing and text mining paired with machine learning models to assist in guiding sophisticated investors and corporate managers in financial decision making. Other topics include cryptocurrency in emerging markets; the role of artificial intelligence in making a positive impact on sustainable development; the use of fintech for micro, small and medium enterprises; the role of AI i financial education; the application of artificial intelligence in cyber security; and more.

In modern business landscapes, leveraging Artificial Intelligence (AI), particularly Generative AI, has become imperative for enhancing daily productivity. Generative AI employs algorithms to autonomously generate content, automate routine tasks, and optimize workflows. This transformative technology empowers organizations to streamline operations across various domains, from content creation to customer service. By harnessing Generative AI tools, businesses can significantly reduce manual efforts, cut costs, and expedite processes while maintaining high-quality output. Whether it's generating reports, composing emails, or crafting marketing materials, Generative AI amplifies efficiency and effectiveness. This integration of AI into daily operations not only fosters innovation but also fosters a competitive edge in the market. In the realm of publishing, platforms like Amazon Kindle Direct Publishing (KDP) offer authors and publishers the opportunity to harness Generative AI for automating content creation and optimizing publishing workflows, thereby maximizing productivity and success.

Within the past year, generative AI has broken barriers and transformed how we think about what computers are truly capable of. But, with the marketing hype and generative AI washing of content, it’s increasingly difficult for business leaders and practitioners to go beyond the art of the possible and answer that critical question–how is generative AI actually being used in organizations? With over 70 real-world case studies and applications across 12 different industries and 11 departments, Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies fills a critical knowledge gap for business leaders and practitioners by providing examples of generative AI in action. Diving into the case studies, this TinyTechGuide discusses AI risks, implementation considerations, generative AI operations, AI ethics, and trustworthy AI. The world is transforming before our very eyes. Don’t get left behind—while understanding the powers and perils of generative AI. Full of use cases and real-world applications, this book is designed for business leaders, tech professionals, and IT teams. We provide practical, jargon-free explanations of generative AI's transformative power. Gain a competitive edge in today's marketplace with Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies. Remember, it's not the tech that's tiny, just the book!™

The present book on ‘Artificial Intelligence (AI) and Business’ presents the current trends of artificial intelligence. The book includes the research papers of various researchers from various disciplines. It has become necessary to understand the various trends of artificial intelligence to attain success in dynamic environment. Business people should analyze the favourable and unfavourable effects of these trends while framing the business strategy. I hope this book will be purposeful for the students, managers and researchers in the area of business management.

This book seeks to build a shared understanding of Artificial Intelligence (AI) within the global business scenario today and in the near future. Drawing on academic theory and real-world case studies, it examines AI’s development and application across a number of business contexts. Taking current scholarship forward in its engagement with AI theory and practice for enterprises and applied research and innovation, it outlines international practices for the promotion of reliable AI systems, trends, research and development, fostering a digital ecosystem for AI and preparing companies for job transformation and building skills. This book will be of great interest to academics studying Digital Business, Digital Strategy, Innovation Management, and Information Technology.

This book offers students an introduction to the concepts of big data and artificial intelligence (AI) and their applications in the business world. It answers questions such as what are the main concepts of artificial intelligence and big data? What applications for artificial intelligence and big data analytics are used in the business field? It offers application-oriented overviews and cases from different sectors and fields to help readers discover and gain useful insights. Each chapter features discussion questions and summaries. To assist professors in teaching, the book supplementary materials will include answers to questions, and presentation slides.

Neural networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice. Their use for risk assessment is also growing and they have been employed to visualise complex databases for marketing segmentation. This boom in applications covers a wide range of business interests -- from finance management, through forecasting, to production. The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise. This book reviews the state-of-the-art in current applications of neural-network methods in three important areas of business analysis. It includes a tutorial chapter to introduce new users to the potential and pitfalls of this new technology.

"This book deals with the computational intelligence field, particularly business applications adopting computational intelligence techniques"--Provided by publisher.