Artificial Intelligence in Business Management is a review of artificial intelligence (AI) applications in businesses. This book adopts a cross-disciplinary strategy toward AI adoption. Book chapters explore many projects that go beyond simple data management and accessibility to showcase the growing role of artificial intelligence and machine learning in the enterprise data space. AI methods for tackling marketing and commercial strategies, as well as the use of AI and machine learning in tourism, insurance and healthcare systems, are discussed. A study on the significance of cultural assets in evaluating risks and protection is also presented. The content gives valuable insights on the application and implications of artificial intelligence and machine learning from this book to readers aiming for corporate roles, such as directors, executives, senior software developers, and digital transformation managers. The book is an essential resource for researchers and professionals in business, economics, and allied disciplines.

This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.

Integrating Artificial Intelligence (AI) presents immense opportunities and daunting challenges in the rapidly evolving finance landscape as AI-driven algorithms and models revolutionize decision-making and enhance efficiency, concerns about bias, ethics, and security loom. Financial institutions must navigate these complexities responsibly while leveraging AI's potential to innovate and thrive. Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security guides this dynamic environment. Written for professionals, researchers, policymakers, and students, this book comprehensively explores AI's impact on finance. It delves into the intricacies of bias in algorithms, ethical frameworks, cybersecurity, and regulatory compliance, offering actionable insights to address these critical issues.

In the realm of Islamic finance, a pivotal challenge looms—the escalating complexity of investment decisions, macroeconomic analyses, and credit evaluations. In response, we present a groundbreaking solution that resonates with the rapidly evolving fintech era. Fintech Applications in Islamic Finance: AI, Machine Learning, and Blockchain Techniques offers a compelling repository of knowledge, meticulously curated by renowned editors Mohammad Irfan, Seifedine Kadry, Muhammad Sharif, and Habib Ullah Khan. Fintech Applications in Islamic Finance: AI, Machine Learning, and Blockchain Techniques is a call to action, an exploration of innovation, and a guide for both academia and industry. In an era where AI, ML, and blockchain reshape finance, this book stands as a beacon of knowledge, ushering Islamic finance into a realm of unprecedented efficiency and insight. As we invite readers to embark on this transformative journey, we illuminate the path to a future where technology and tradition converge harmoniously.

This comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

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!™