The AI enabled enterprise uses technology to continuously learn by monitoring its behavior and the environment as well as external knowledge sources in order to automate the decision-making and decision-implementation processes leading to continuous improvement over time. This book discusses the key challenges that organizations need to overcome in achieving an AI enabled enterprise: the role of digital twins in evidence-backed design, enterprise cartography that goes far beyond process mining, decision-making in the face of uncertainty, software architecture for continuous adaptation, democratized knowledge-guided software development enabling coordinated design, low code versus no code, and coherent design. For each challenge, the book proposes a line of attack along with the associated enabling technology and illustrates the same through a near real world use case.

We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities Empower better, smarter decision making by implementing AI-enabled analytics decision support tools Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation.

Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.

Enterprise Artificial Intelligence Transformation AI is everywhere. From doctor's offices to cars and even refrigerators, AI technology is quickly infiltrating our daily lives. AI has the ability to transform simple tasks into technological feats at a human level. This will change the world, plain and simple. That's why AI mastery is such a sought-after skill for tech professionals. Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for over 10 years. He shares that expertise in the new book, Enterprise Artificial Intelligence Transformation. The first of its kind, this book grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology. As AI continues to grow into a necessary feature for many businesses, more and more leaders are interested in harnessing the technology within their own organizations. In this new book, leaders will learn to master AI fundamentals, grow their career opportunities, and gain confidence in machine learning. Enterprise Artificial Intelligence Transformation covers a wide range of topics, including: Real-world AI use cases and examples Machine learning, deep learning, and slimantic modeling Risk management of AI models AI strategies for development and expansion AI Center of Excellence creating and management If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in Enterprise Artificial Intelligence Transformation.

As the use of AI becomes more and more ubiquitous in companies around the world, managers charged with taking key decisions require resources to enable them to evaluate new projects effectively. The business case for AI projects is not necessarily clear cut and part of the reason for this is the lack of understanding on key decision criteria. AI touches on many ethical concepts - data privacy, validity and more importantly, its potential misuse. AI is often being used to replace human decision-making and there is often no real understanding of the implications of this. This book provides a detailed primer for practitioners without a deep technological background. It guides the reader through the basic issues and offers advice on ‘how to take decisions’. There is a dearth of such books currently available and this book aspires to fill a growing niche. ENDORSEMENTS: "This book is sure to offer value to business users, students and the general public." — K. Ananth Krishnan, Tata Consultancy Services "I highly recommend this book for the leader seeking an up-to-date review of AI to make strategic investments." — Kes Sampanthar, Innovation, BCG Brighthouse "The specificity of application in case studies and easy to understand definitions and recommendations make this a must read in the ever-growing field of literature around AI." — John C. Havens "The AI Enabled Organization is the perfect tool to embark on a thorough assessment of what AI means for your business." — Arno Fehler, Schmidt Kranz Group, Germany

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

While enterprise information systems are increasingly featuring capabilities based on Artificial Intelligence with the aim to support human users in decision-making, user trust in such AI-enabled enterprise information systems is often still low, which constitutes one of the main acceptance barriers regarding these systems. Besides clearly defining this new class of information systems by developing a taxonomy, this thesis examines which factors are affecting user trust in AI-enabled enterprise information systems. A model of relevant user trust antecedents is developed by conducting a structured literature review of previously examined trust antecedents and by interviewing expert practitioners. The resulting model subdivides these relevant user trust antecedents into the main areas of user characteristics, system characteristics, user experience and interpretability, contributing valuable insights for both AI practitioners and scholars.