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Artificial Intelligence for Customer Relationship Management: Solving Customer Problems (Human–Computer Interaction Series)
by Boris GalitskyThe second volume of this research monograph describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer. After we learn to detect fake content, deception and hypocrisy, we examine the domain of customer complaints. We simulate mental states, attitudes and emotions of a complainant and try to predict his behavior. Having suggested graph-based formal representations of complaint scenarios, we machine-learn them to identify the best action the customer support organization can chose to retain the complainant as a customer.
Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare (Chapman & Hall/CRC Biostatistics Series)
by Mark ChangArtificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science&’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.
Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare (Chapman & Hall/CRC Biostatistics Series)
by Mark ChangArtificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science&’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.
Artificial Intelligence for Fashion: How AI is Revolutionizing the Fashion Industry
by Leanne LuceLearn how Artificial Intelligence (AI) is being applied in the fashion industry. With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals. The book investigates the ways in which AI is impacting every part of the fashion value chain starting with product discovery and working backwards to manufacturing. Artificial Intelligence for Fashion walks you through concepts, such as connected retail, data mining, and artificially intelligent robotics. Each chapter contains an example of how AI is being applied in the fashion industry illustrated by one major technological theme. There are no equations, algorithms, or code. The technological explanations are cumulative so you'll discover more information about the inner workings of artificial intelligence in practical stages as the book progresses. What You’ll LearnGain a basic understanding of AI and how it is used in fashionUnderstand key terminology and concepts in AIReview the new competitive landscape of the fashion industryConceptualize and develop new ways to apply AI within the workplaceWho This Book Is ForFashion industry professionals from designers, managers, department heads, and executives can use this book to learn about how AI is impacting roles in every department and profession.
Artificial Intelligence for Fashion Industry in the Big Data Era (Springer Series in Fashion Business)
by Sébastien Thomassey Xianyi ZengThis book provides an overview of current issues and challenges in the fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges. Each chapter starts off with an example of a data-driven AI technique on a particular sector of the fashion industry (design, manufacturing, supply or retailing), before moving on to illustrate its implementation in a real-world application
Artificial Intelligence for HR: Use AI to Support and Develop a Successful Workforce
by Ben EubanksGetting to grips with artificial intelligence (AI) and the way it's changing the world of work is essential for HR professionals. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chat bots to enhance the employee experience, AI has created opportunities for the HR function. Artificial Intelligence for HR empowers HR professionals to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR. Covering everything from recruitment and retention to employee engagement and learning and development (L&D), Artificial Intelligence for HR outlines what value AI can add to the HR function and how to achieve this. It also includes essential discussion of the challenges that can arise from AI and how to deal with them including how to balance a human workforce with the rise of machine learning and robotics. Packed with practical advice and case studies from global organizations including Johnson & Johnson, this book equips HR professionals with the ability to use AI to recruit and develop a successful workforce and thrive in the future world of work.
Artificial Intelligence for HR: Use AI to Support and Develop a Successful Workforce
by Ben EubanksGetting to grips with artificial intelligence (AI) and the way it's changing the world of work is essential for HR professionals. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chat bots to enhance the employee experience, AI has created opportunities for the HR function. Artificial Intelligence for HR empowers HR professionals to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR. Covering everything from recruitment and retention to employee engagement and learning and development (L&D), Artificial Intelligence for HR outlines what value AI can add to the HR function and how to achieve this. It also includes essential discussion of the challenges that can arise from AI and how to deal with them including how to balance a human workforce with the rise of machine learning and robotics. Packed with practical advice and case studies from global organizations including Johnson & Johnson, this book equips HR professionals with the ability to use AI to recruit and develop a successful workforce and thrive in the future world of work.
Artificial Intelligence for HR: Use AI to Support and Develop a Successful Workforce
by Ben EubanksArtificial intelligence is changing the world of work. How can HR professionals understand the variety of opportunities AI has created for the HR function and how best to implement these in their organization? This book provides the answers.From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chatbots to enhance the employee experience, artificial intelligence can add value throughout the work of HR professionals. Artificial Intelligence for HR demonstrates how to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR in practice.Alongside coverage of employee engagement and recruitment, this second edition features new material on applications of AI for virtual work, reskilling and data integrity. Packed with practical advice, research and new and updated case studies from global organizations including Uber, IBM and Unilever, the second edition of Artificial Intelligence for HR will equip HR professionals with the knowledge they need to improve people operational efficiencies, and allow AI solutions to become enhancements for driving business success.
Artificial Intelligence for Industries of the Future: Beyond Facebook, Amazon, Microsoft and Google (Future of Business and Finance)
by Mayank KejriwalThis book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google. With this information, the author also makes some reasonable claims about the role of AI in future industries. The book draws on a broad range of material, including reports from consulting firms, published surveys, academic papers and books, and expert knowledge available to the author due to numerous collaborations in academia and industry on AI. It is rigorous rather than speculative, drawing on known findings and expert summaries, where available. This provides industry leaders and other interested stakeholders with an accessible review of contemporary perspectives on AI’s forward-looking role in industry as well as a clarifying guide on the major issues that companies are likely to face as they commence on this exciting path.Examines the likely role of AI in industries of the future, both known and unknownPresents use-cases of AI currently being explored across Big Tech, multi-national corporations and start-upsExplores the regulation of AI and its potential impacts on the workforce
Artificial Intelligence for Learning: How to use AI to Support Employee Development
by Donald ClarkArtificial intelligence is creating huge opportunities for workplace learning and employee development. However, it can be difficult for L&D professionals to assess what difference AI can make in their organization and where it is best implemented. Artificial Intelligence for Learning is the practical guide L&D practitioners need to understand what AI is and how to use it to improve all aspects of learning in the workplace. It includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, how it can be implemented to improve the efficiency of evaluation, assessment and reporting and how chatbots can provide learner support to a global workforce.Artificial Intelligence for Learning debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice.
Artificial Intelligence for Learning: Using AI and Generative AI to Support Learner Development
by Donald ClarkWith Artificial Intelligence (AI) creating huge opportunities for learning and employee development, how can learning professionals best implement the use of AI into their environment?Artificial Intelligence for Learning is the essential guide for learning professionals who want to understand how to use AI to improve all aspects of learning in organizations. This new edition debunks the myths and misconceptions around AI, discusses the learning theory behind generative AI and gives strategic and practical advice on how AI can be used.This book also includes specific guidance on how AI can provide learning support, chatbot functionality and content, as well as ideas on ethics and personalization. This book is necessary reading for all learning practitioners needing to understand AI and what it means in practice.
Artificial Intelligence for Marketing: Practical Applications (Wiley and SAS Business Series)
by Jim SterneA straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.
Artificial Intelligence for Marketing: Practical Applications (Wiley and SAS Business Series)
by Jim SterneA straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.
Artificial Intelligence for Marketing Management (Routledge Studies in Marketing)
by Park Thaichon Sara QuachArtificial intelligence (AI) has driven businesses to adopt new business practices rapidly, enhance product development and services, has helped to power AI-based market intelligence and customer insights, and improve customer relationship management. This timely book addresses the use of AI in marketing. This book also explores the dark side of AI in marketing management and discusses ethics and transparency of automated decision-making in AI applications, data privacy, cyber security issues, and biases in various facets of marketing. Emerging applications of AI such as DeepFakes which use deep learning technology could increase risks of manipulation and deception. Hence, apart from leveraging AI capabilities and advantages, the book cautions the need for prevention strategies to deal with potential issues that could arise from the adoption of AI in marketing management. This book will provide practical insights into the role of AI in marketing management. It will be a useful reference for those researching marketing and marketing professionals.
Artificial Intelligence for Marketing Management (Routledge Studies in Marketing)
by Park Thaichon Sara QuachArtificial intelligence (AI) has driven businesses to adopt new business practices rapidly, enhance product development and services, has helped to power AI-based market intelligence and customer insights, and improve customer relationship management. This timely book addresses the use of AI in marketing. This book also explores the dark side of AI in marketing management and discusses ethics and transparency of automated decision-making in AI applications, data privacy, cyber security issues, and biases in various facets of marketing. Emerging applications of AI such as DeepFakes which use deep learning technology could increase risks of manipulation and deception. Hence, apart from leveraging AI capabilities and advantages, the book cautions the need for prevention strategies to deal with potential issues that could arise from the adoption of AI in marketing management. This book will provide practical insights into the role of AI in marketing management. It will be a useful reference for those researching marketing and marketing professionals.
Artificial Intelligence for Sustainability: Innovations in Business and Financial Services
by Thomas Walker Stefan Wendt Sherif Goubran Tyler SchwartzIn light of the climate crisis, businesses are expected to embrace sustainability to reduce their negative impacts on the environment and society, while at the same time strengthening their organisations’ positive impacts. Managing this alongside the traditional requirements of business requires careful handling, and it is small wonder that some are heralding the advantages posed by artificial intelligence (AI) as the missing piece of the puzzle. This edited book aims to present a balanced discussion of the benefits and costs of using AI for the natural environment and society, including an analysis of its potential to help meet the UN’s Agenda 2030 and the Sustainable Development Goals. Researchers, practitioners, regulators, and entrepreneurs at the forefront of sustainable AI solutions share insights into the different sustainable applications of AI and highlight how these new developments may affect and contribute to our fight against climate change and address further environmental and social challenges. This volume will be of great interest to scholars and students of digital business and new technologies, sustainability, and strategy.
Artificial Intelligence for Sustainable Finance and Sustainable Technology: Proceedings of ICGER 2021 (Lecture Notes in Networks and Systems #423)
by Abdalmuttaleb M. A. Musleh Al-SartawiThis book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.
Artificial Intelligence for Sustainable Value Creation
Artificial Intelligence for Sustainable Value Creation provides a detailed and insightful exploration of both the possibilities and the challenges that accompany widespread Artificial Intelligence.Providing a cutting edge analysis of the impact of AI in business and society, the editors offer an opportunity to assess what is known about managing other forms of information systems, strategy, and marketing, and to re-examine this knowledge in situations involving AI. This comprehensive book explores how human- centric AI systems create value inside organizations, distinguishing three main components: ethical value, societal value, and business value.Using a multidisciplinary perspective, this discerning book addresses the interests of a wide spectrum of practitioners, students, and researchers alike who are interested in identifying the value generated by AI systems in management.
The Artificial Intelligence Imperative: A Practical Roadmap for Business
by Anastassia Lauterbach Andrea Bonime-BlancThis practical guide to artificial intelligence and its impact on industry dispels common myths and calls for cross-sector, collaborative leadership for the responsible design and embedding of AI in the daily work of businesses and oversight by boards.Artificial intelligence has arrived, and it's coming to a business near you. The disruptive impact of AI on the global economy—from health care to energy, financial services to agriculture, and defense to media—is enormous. Technology literacy is a must for traditional businesses, their boards, policy makers, and governance professionals. This is the first book to explain where AI comes from, why it has emerged as one of the most powerful forces in mergers and acquisitions and research and development, and what companies need to do to implement it successfully. It equips business leaders with a practical roadmap for competing and even thriving in the face of the coming AI revolution. The authors analyze competitive trends, provide industry and governance examples, and explain interactions between AI and other digital technologies, such as blockchain, cybersecurity, and the Internet of Things. At the same time, AI experts will learn how their research and products can increase the competitiveness of their businesses, and corporate boards will come away with a thorough knowledge of the AI governance, ethics, and risk questions to ask.
The Artificial Intelligence Imperative: A Practical Roadmap for Business
by Anastassia Lauterbach Andrea Bonime-BlancThis practical guide to artificial intelligence and its impact on industry dispels common myths and calls for cross-sector, collaborative leadership for the responsible design and embedding of AI in the daily work of businesses and oversight by boards.Artificial intelligence has arrived, and it's coming to a business near you. The disruptive impact of AI on the global economy—from health care to energy, financial services to agriculture, and defense to media—is enormous. Technology literacy is a must for traditional businesses, their boards, policy makers, and governance professionals. This is the first book to explain where AI comes from, why it has emerged as one of the most powerful forces in mergers and acquisitions and research and development, and what companies need to do to implement it successfully. It equips business leaders with a practical roadmap for competing and even thriving in the face of the coming AI revolution. The authors analyze competitive trends, provide industry and governance examples, and explain interactions between AI and other digital technologies, such as blockchain, cybersecurity, and the Internet of Things. At the same time, AI experts will learn how their research and products can increase the competitiveness of their businesses, and corporate boards will come away with a thorough knowledge of the AI governance, ethics, and risk questions to ask.
Artificial Intelligence in Accounting: Organisational and Ethical Implications (Routledge Studies in Accounting)
by Othmar M. Lehner Carina KnollArtificial intelligence (AI) and Big Data based applications in accounting and auditing have become pervasive in recent years. However, research on the societal implications of the widespread and partly unregulated use of AI and Big Data in several industries remains scarce despite salient and competing utopian and dystopian narratives. This book focuses on the transformation of accounting and auditing based on AI and Big Data. It not only provides a thorough and critical overview of the status-quo and the reports surrounding these technologies, but it also presents a future outlook on the ethical and normative implications concerning opportunities, risks, and limits. The book discusses topics such as future, human-machine collaboration, cybernetic approaches to decision-making, and ethical guidelines for good corporate governance of AI-based algorithms and Big Data in accounting and auditing. It clarifies the issues surrounding the digital transformation in this arena, delineates its boundaries, and highlights the essential issues and debates within and concerning this rapidly developing field. The authors develop a range of analytic approaches to the subject, both appreciative and sceptical, and synthesise new theoretical constructs that make better sense of human-machine collaborations in accounting and auditing. This book offers academics a variety of new research and theory building on digital accounting and auditing from and for accounting and auditing scholars, economists, organisations, and management academics and political and philosophical thinkers. Also, as a landmark work in a new area of current policy interest, it will engage regulators and policy makers, reflective practitioners, and media commentators through its authoritative contributions, editorial framing and discussion, and sector studies and cases.
Artificial Intelligence in Accounting: Organisational and Ethical Implications (Routledge Studies in Accounting)
by Othmar M. Lehner Carina KnollArtificial intelligence (AI) and Big Data based applications in accounting and auditing have become pervasive in recent years. However, research on the societal implications of the widespread and partly unregulated use of AI and Big Data in several industries remains scarce despite salient and competing utopian and dystopian narratives. This book focuses on the transformation of accounting and auditing based on AI and Big Data. It not only provides a thorough and critical overview of the status-quo and the reports surrounding these technologies, but it also presents a future outlook on the ethical and normative implications concerning opportunities, risks, and limits. The book discusses topics such as future, human-machine collaboration, cybernetic approaches to decision-making, and ethical guidelines for good corporate governance of AI-based algorithms and Big Data in accounting and auditing. It clarifies the issues surrounding the digital transformation in this arena, delineates its boundaries, and highlights the essential issues and debates within and concerning this rapidly developing field. The authors develop a range of analytic approaches to the subject, both appreciative and sceptical, and synthesise new theoretical constructs that make better sense of human-machine collaborations in accounting and auditing. This book offers academics a variety of new research and theory building on digital accounting and auditing from and for accounting and auditing scholars, economists, organisations, and management academics and political and philosophical thinkers. Also, as a landmark work in a new area of current policy interest, it will engage regulators and policy makers, reflective practitioners, and media commentators through its authoritative contributions, editorial framing and discussion, and sector studies and cases.
Artificial Intelligence in Accounting: Practical Applications (ISSN)
by Cory Ng John AlarconArtificial Intelligence in Accounting: Practical Applications was written with a simple goal: to provide accountants with a foundational understanding of AI and its many business and accounting applications. It is meant to serve as a guide for identifying opportunities to implement AI initiatives to increase productivity and profitability. This book will help you answer questions about what AI is and how it is used in the accounting profession today. Offering practical guidance that you can leverage for your organization, this book provides an overview of essential AI concepts and technologies that accountants should know, such as machine learning, deep learning, and natural language processing. It also describes accounting-specific applications of robotic process automation and text mining. Illustrated with case studies and interviews with representatives from global professional services firms, this concise volume makes a significant contribution to examining the intersection of AI and the accounting profession. This innovative book also explores the challenges and ethical considerations of AI. It will be of great interest to accounting practitioners, researchers, educators, and students.
Artificial Intelligence in Accounting: Practical Applications (ISSN)
by Cory Ng John AlarconArtificial Intelligence in Accounting: Practical Applications was written with a simple goal: to provide accountants with a foundational understanding of AI and its many business and accounting applications. It is meant to serve as a guide for identifying opportunities to implement AI initiatives to increase productivity and profitability. This book will help you answer questions about what AI is and how it is used in the accounting profession today. Offering practical guidance that you can leverage for your organization, this book provides an overview of essential AI concepts and technologies that accountants should know, such as machine learning, deep learning, and natural language processing. It also describes accounting-specific applications of robotic process automation and text mining. Illustrated with case studies and interviews with representatives from global professional services firms, this concise volume makes a significant contribution to examining the intersection of AI and the accounting profession. This innovative book also explores the challenges and ethical considerations of AI. It will be of great interest to accounting practitioners, researchers, educators, and students.
Artificial Intelligence in Commercial Aviation: Use Cases and Emerging Strategies
by Ricardo V. PilonThis book is a must read for aviation managers and all stakeholders that are interested in improving the business performance of airlines. In this book, the first of its kind on AI in Commercial Aviation, the author outlines how Machine Learning and AI are accelerating and improving the performance of airlines. Moreover, the author shares insights into many new use cases that emerging technology can deliver. He tackles all crucial functions from air navigation, flight operations, to sales, distribution, cargo, retailing, and commercial optimization. He then looks forward to blockchain and the metaverse and its opportunities. With connected devices and the Internet of Everything (IoE), airlines can become retailers, sell, deliver, and service holistic experiences tailored to individuals in real time. This requires airlines to modernize processes and practices supported by decision intelligence (AI) that ingests sophisticated insights and executes service automation in real time. Transforming airlines from a production to a services-based execution also requires departments to be aligned along overriding customer experience and profitability goals. The book demonstrates how AI can be deployed to redesign airline organization as well. The author also describes the next wave of business transformation around the integration of commercial functions using Composite AI at enterprise level. With his holistic understanding and experience in the airline industry, the author provides valuable insights and helps managers understand how to embrace ML and AI and contribute to future commercial aviation and cargo success.