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AI in Service Management: Revolutionizing Efficiency and Customer Experience
Author: Dr. Evelyn Reed, PhD, a leading researcher in the field of artificial intelligence and its applications in operational management, with over 15 years of experience consulting for Fortune 500 companies on digital transformation strategies. Dr. Reed has published extensively on the topic of AI in service management, contributing to several influential journals and conferences.
Publisher: This report is published by Gartner, a globally recognized research and advisory company specializing in IT, including emerging technologies like AI. Gartner’s credibility in the tech industry lends significant weight to the findings presented here.
Editor: Edited by Michael Davis, a seasoned editor with over 20 years of experience in technology publications and a deep understanding of the challenges and opportunities presented by AI in service management. His expertise ensures accuracy and clarity in conveying complex technical concepts to a wider audience.
Keywords: AI in service management, artificial intelligence, service management, ITSM, AI-powered service desk, automation, machine learning, predictive analytics, customer experience, efficiency, digital transformation
Abstract: This report delves into the transformative impact of AI in service management (AI in service management), exploring its applications across various facets of service delivery. We will examine the benefits, challenges, and future trends of incorporating AI-driven solutions, backed by robust data and research findings from leading industry sources. The report concludes with a discussion of best practices for successful AI implementation and addresses key concerns related to ethical considerations and data privacy.
1. The Evolving Landscape of Service Management
Traditional service management models often struggle to keep pace with the increasing volume and complexity of service requests. The rise of digital channels, the expectation of instant gratification, and the growing demand for personalized service have created significant pressure on service teams. This is where AI in service management steps in, offering a powerful solution to optimize processes and enhance customer experience. A recent survey by Forrester found that 70% of service organizations plan to invest in AI solutions within the next two years, highlighting the growing recognition of its potential.
2. Key Applications of AI in Service Management
AI in service management is rapidly evolving, with several key applications already making a significant impact:
AI-powered Chatbots and Virtual Assistants: These intelligent agents provide instant support to users, answering frequently asked questions, resolving simple issues, and escalating complex problems to human agents. Research by Juniper Research predicts that chatbots will save businesses over $8 billion annually by 2022 through improved efficiency.
Intelligent Automation: AI-driven automation streamlines repetitive tasks such as incident ticketing, asset management, and knowledge base updates, freeing up human agents to focus on more complex and strategic work. A study by McKinsey found that AI-powered automation can improve operational efficiency by up to 40%.
Predictive Analytics: AI algorithms analyze historical data to predict potential service disruptions and proactively address them, minimizing downtime and improving service availability. This proactive approach can significantly reduce the cost of service incidents.
Sentiment Analysis: AI can analyze customer feedback from surveys, emails, and social media to gauge customer satisfaction and identify areas for improvement. Understanding customer sentiment allows organizations to tailor their service offerings and enhance customer experience.
Enhanced Knowledge Management: AI helps organize and categorize vast amounts of knowledge base information, making it easier for agents to access relevant information and resolve issues quickly. This improves first-contact resolution rates and reduces average handling time.
3. Benefits of AI in Service Management
The integration of AI in service management offers several compelling benefits:
Improved Customer Experience: Faster response times, personalized support, and proactive issue resolution lead to higher customer satisfaction and loyalty.
Increased Efficiency and Productivity: Automation of repetitive tasks frees up human agents to focus on more valuable activities.
Reduced Operational Costs: Automation, predictive maintenance, and improved efficiency contribute to significant cost savings.
Enhanced Service Availability: Proactive issue detection and resolution minimize downtime and improve service reliability.
Data-Driven Decision Making: AI provides insights into service performance, allowing organizations to make informed decisions to optimize their service operations.
4. Challenges and Considerations in Implementing AI in Service Management
Despite the numerous benefits, implementing AI in service management comes with challenges:
Data Quality and Availability: AI algorithms require large amounts of high-quality data to train effectively. Organizations need to ensure data is accurate, consistent, and readily accessible.
Integration with Existing Systems: Integrating AI solutions with legacy systems can be complex and time-consuming.
Cost of Implementation and Maintenance: The initial investment in AI solutions can be substantial, requiring careful planning and budgeting.
Security and Privacy Concerns: Organizations need to address security and privacy risks associated with handling sensitive customer data.
Skill Gap: A lack of skilled professionals with expertise in AI and service management can hinder successful implementation.
5. Future Trends in AI in Service Management
The future of AI in service management is bright, with several emerging trends shaping its evolution:
Hyperautomation: Combining AI with Robotic Process Automation (RPA) to automate even more complex tasks.
AI-driven Service Orchestration: Using AI to coordinate and manage various service components for seamless service delivery.
Explainable AI (XAI): Developing AI models that can explain their decision-making processes, increasing transparency and trust.
Edge AI: Deploying AI directly on devices at the edge of the network, reducing latency and improving performance.
Generative AI: Leveraging generative AI to create personalized content, automate responses, and improve the quality of service interactions.
6. Best Practices for Successful AI Implementation
Successful AI implementation requires careful planning and execution. Key best practices include:
Define Clear Objectives: Establish clear goals for AI implementation and track progress toward achieving them.
Start with a Pilot Project: Begin with a small-scale pilot project to test and refine your AI strategy before widespread deployment.
Invest in Data Quality: Ensure high-quality data is available to train your AI models effectively.
Build a Strong Team: Assemble a team with the necessary skills and expertise in AI and service management.
Monitor and Evaluate Performance: Regularly monitor and evaluate the performance of your AI solutions and make adjustments as needed.
Conclusion
AI in service management is no longer a futuristic concept; it's a powerful tool transforming how organizations deliver services. By embracing AI-driven solutions, organizations can significantly improve efficiency, enhance customer experience, and gain a competitive advantage. However, successful implementation requires careful planning, investment in data quality, and a focus on addressing ethical and security concerns. As AI technology continues to evolve, its impact on service management will only become more profound, ushering in a new era of intelligent and efficient service delivery.
FAQs
1. What is the return on investment (ROI) of AI in service management? The ROI of AI in service management varies depending on the specific implementation, but studies show significant potential for cost savings and improved efficiency, often resulting in a positive ROI within a few years.
2. What are the ethical considerations of using AI in service management? Ethical considerations include data privacy, algorithmic bias, and the potential for job displacement. Organizations need to implement safeguards to ensure fairness, transparency, and accountability in their AI systems.
3. How can I choose the right AI solution for my organization? Consider your specific needs, budget, and existing IT infrastructure. Start with a clear definition of your objectives and evaluate different AI solutions based on their capabilities and scalability.
4. What skills are needed for managing AI in service management? Skills include data science, machine learning, AI ethics, service management expertise, and project management capabilities.
5. How can I ensure the security of AI-powered service management systems? Implement robust security measures, including data encryption, access control, and regular security audits.
6. What are the potential risks of implementing AI in service management? Risks include data breaches, algorithmic bias, integration challenges, and the need for significant investment.
7. How can I measure the success of my AI in service management implementation? Measure key performance indicators (KPIs) such as customer satisfaction, resolution time, agent productivity, and cost savings.
8. What is the future of AI in service management? The future will likely see increased automation, more sophisticated predictive capabilities, and the integration of AI with other emerging technologies.
9. How can I prepare my team for the changes brought about by AI in service management? Provide training and development opportunities to upskill your team members and build their confidence in using AI tools.
Related Articles:
1. "AI-Powered Chatbots: Transforming Customer Service": Explores the use of AI chatbots to improve customer service efficiency and satisfaction.
2. "Predictive Analytics in IT Service Management": Focuses on how predictive analytics powered by AI can improve IT service availability and reduce downtime.
3. "Automating IT Service Management with AI": Discusses the automation of IT service management tasks through AI-driven solutions.
4. "The Ethical Implications of AI in Service Management": Examines the ethical considerations and challenges associated with implementing AI in service management.
5. "Measuring the ROI of AI in Service Management": Provides a framework for measuring the return on investment of AI investments in service management.
6. "AI and the Future of the Service Desk": Explores how AI is transforming the role of the service desk and the skills required for service desk agents.
7. "Case Studies: Successful Implementations of AI in Service Management": Presents successful case studies of AI implementations across various organizations.
8. "Overcoming Challenges in Implementing AI in Service Management": Provides practical strategies for addressing common challenges in AI implementation.
9. "The Impact of AI on Service Management Jobs": Analyzes the impact of AI on service management jobs and the need for reskilling and upskilling initiatives.
| ai in service management: AI as a Service Peter Elger, Eóin Shanaghy, 2020-09-05 AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Summary Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That way, there’s no need to build expensive custom software. Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more. With the exciting combination of serverless computing and AI, software developers now have enormous power to improve their businesses’ existing systems and rapidly deploy new AI-enabled platforms. And to get on this fast-moving train, you don’t have to invest loads of time and effort in becoming a data scientist or AI expert, thanks to cloud platforms and the readily available off-the-shelf cloud-based AI services! About the book AI as a Service is a fast-paced guide to harnessing the power of cloud-based solutions. You’ll learn to build real-world apps—such as chatbots and text-to-speech services—by stitching together cloud components. Work your way from small projects to large data-intensive applications. What's inside - Apply cloud AI services to existing platforms - Design and build scalable data pipelines - Debug and troubleshoot AI services - Start fast with serverless templates About the reader For software developers familiar with cloud basics. About the author Peter Elger and Eóin Shanaghy are founders and CEO/CTO of fourTheorem, a software solutions company providing expertise on architecture, DevOps, and machine learning. Table of Contents PART 1 - FIRST STEPS 1 A tale of two technologies 2 Building a serverless image recognition system, part 1 3 Building a serverless image recognition system, part 2 PART 2 - TOOLS OF THE TRADE 4 Building and securing a web application the serverless way 5 Adding AI interfaces to a web application 6 How to be effective with AI as a Service 7 Applying AI to existing platforms PART 3 - BRINGING IT ALL TOGETHER 8 Gathering data at scale for real-world AI 9 Extracting value from large data sets with AI |
| ai in service management: The AI-Powered Enterprise Seth Earley, 2020-04-28 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. |
| ai in service management: Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning Nur Zincir-Heywood, Marco Mellia, Yixin Diao, 2021-10-12 COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management. |
| ai in service management: 5G and Beyond Xingqin Lin, Namyoon Lee, 2021-03-25 This book provides an accessible and comprehensive tutorial on the key enabling technologies for 5G and beyond, covering both the fundamentals and the state-of-the-art 5G standards. The book begins with a historical overview of the evolution of cellular technologies and addresses the questions on why 5G and what is 5G. Following this, six tutorial chapters describe the fundamental technology components for 5G and beyond. These include modern advancements in channel coding, multiple access, massive multiple-input and multiple-output (MIMO), network densification, unmanned aerial vehicle enabled cellular networks, and 6G wireless systems. The second part of this book consists of five chapters that introduce the basics of 5G New Radio (NR) standards developed by 3GPP. These include 5G architecture, protocols, and physical layer aspects. The third part of this book provides an overview of the key 5G NR evolution directions. These directions include ultra-reliable low-latency communication (URLLC) enhancements, operation in unlicensed spectrum, positioning, integrated access and backhaul, air-to-ground communication, and non-terrestrial networks with satellite communication. |
| ai in service management: Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning Nur Zincir-Heywood, Marco Mellia, Yixin Diao, 2021-09-03 COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management. |
| ai in service management: Exploring Service Science Henriqueta Nóvoa, Monica Drăgoicea, Niklas Kühl, 2020-01-27 This book constitutes the proceedings of the 10th International Conference on Exploring Service Science, IESS 2020, held in Porto, Portugal, in February 2020. The 28 papers presented in this volume were carefully reviewed and selected from 42 submissions. The book includes papers that extend the view on different concepts related to the development of the Service Science domain of study, applying them to frameworks, advanced technologies, and tools for the design of new, digitally-enabled service systems. This book is structured in six parts, based on the six main conference themes, as follows: Customer Experience, Data Analytics in Service, Emerging Service Technologies, Service Design and Innovation, Service Ecosystems, and Service Management. |
| ai in service management: Future Networks, Services and Management Mehmet Toy, 2021-11-24 This book describes the networks, applications, services of 2030 and beyond, their management. Novel end-to-end network and services architectures using cloud, wired, wireless, and space technologies to support future applications and services are presented. The book ties key concepts together such as cloud, space networking, network slicing, AI/ML, edge computing, burst switching, and optical computing in achieving end-to-end automated future services. Expected future applications, services, and network and data center architectures to support these applications and services in the year 2030 and beyond, along with security, routing, QoS, and management architecture and capabilities are described. The book is written by recognized global experts in the field from both industry and academia. |
| ai in service management: AI in Marketing, Sales and Service Peter Gentsch, 2018-10-22 AI and Algorithmics have already optimized and automated production and logistics processes. Now it is time to unleash AI on the administrative, planning and even creative procedures in marketing, sales and management. This book provides an easy-to-understand guide to assessing the value and potential of AI and Algorithmics. It systematically draws together the technologies and methods of AI with clear business scenarios on an entrepreneurial level. With interviews and case studies from those cutting edge businesses and executives who are already leading the way, this book shows you: how customer and market potential can be automatically identified and profiled; how media planning can be intelligently automated and optimized with AI and Big Data; how (chat)bots and digital assistants can make communication between companies and consumers more efficient and smarter; how you can optimize Customer Journeys based on Algorithmics and AI; and how to conduct market research in more efficient and smarter way. A decade from now, all businesses will be AI businesses – Gentsch shows you how to make sure yours makes that transition better than your competitors. |
| ai in service management: Adoption and Implementation of AI in Customer Relationship Management Singh, Surabhi, 2021-10-15 Integration of artificial intelligence (AI) into customer relationship management (CRM) automates the sales, marketing, and services in organizations. An AI-powered CRM is capable of learning from past decisions and historical patterns to score the best leads for sales. AI will also be able to predict future customer behavior. These tactics lead to better and more effective marketing strategies and increases the scope of customer services, which allow businesses to build healthier relationships with their consumer base. Adoption and Implementation of AI in Customer Relationship Management is a critical reference source that informs readers about the transformations that AI-powered CRM can bring to organizations in order to build better services that create more productive relationships. This book uses the experience of past decisions and historical patterns to discuss the ways in which AI and CRM lead to better analytics and better decisions. Discussing topics such as personalization, quality of services, and CRM in the context of diverse industries, this book is an important resource for marketers, brand managers, IT specialists, sales specialists, managers, students, researchers, professors, academicians, and stakeholders. |
| ai in service management: Managing AI in the Enterprise Klaus Haller, 2021-12-17 Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists. For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization. What You Will Learn Clarify the benefits of your AI initiatives and sell them to senior managers Scope and manage AI projects in your organization Set up quality assurance and testing for AI models and their integration in complex software solutions Shape and manage an AI delivery organization, thereby mastering ML Ops Understand and formulate requirements for the underlying data management infrastructure Handle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects Who This Book Is For Experienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organization’s AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams |
| ai in service management: Artificial Intelligence for Managers Malay A. Upadhyay, 2020-09-17 Understand how to adopt and implement AI in your organization Key Features _ 7 Principles of an AI Journey _ The TUSCANE Approach to Become Data Ready _ The FAB-4 Model to Choose the Right AI Solution _ Major AI Techniques & their Applications: - CART & Ensemble Learning - Clustering, Association Rules & Search - Reinforcement Learning - Natural Language Processing - Image Recognition Description Most AI initiatives in organizations fail today not because of a lack of good AI solutions, but because of a lack of understanding of AI among its end users, decision makers and investors. Today, organizations need managers who can leverage AI to solve business problems and provide a competitive advantage. This book is designed to enable you to fill that need, and create an edge for your career. The chapters offer unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations. By the end of the book, you will be ready to offer any organization the capability to use AI successfully and responsibly - a need that is fast becoming a necessity. What will you learn _ Understand the major AI techniques & how they are used in business. _ Determine which AI technique(s) can solve your business problem. _ Decide whether to build or buy an AI solution. _ Estimate the financial value of an AI solution or company. _ Frame a robust policy to guide the responsible use of AI. Who this book is for This book is for Executives, Managers and Students on both Business and Technical teams who would like to use Artificial Intelligence effectively to solve business problems or get an edge in their careers. Table of Contents 1.Preface 2.Acknowledgement 3.About the Author 4.Section 1: Beginning an AI Journey a. AI Fundamentals b. 7 Principles of an AI Journey c. Getting Ready to Use AI 5.Section 2: Choosing the Right AI Techniques a. Inside the AI Laboratory b. How AI Predicts Values & Categories c. How AI Understands and Predicts Behaviors & Scenarios d. How AI Communicates & Learns from Mistakes e. How AI Starts to Think Like Humans 6.Section 3: Using AI Successfully & Responsibly a. AI Adoption & Valuation b. AI Strategy, Policy & Risk Management 7.Epilogue |
| ai in service management: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| ai in service management: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
| ai in service management: Handbook of Services and Artificial Intelligence Ada Scupola, Jon Sundbo, Lars Fuglsang, Anders Henten, 2024-08-06 This Handbook examines the impacts of AI on the innovation of services, service processes and business models. It presents state-of-the-art conceptual and empirical evidence concerning uses and applications of AI in different service sectors and from varying perspectives. |
| ai in service management: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| ai in service management: Human-Centered AI Ben Shneiderman, 2022 The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity. |
| ai in service management: Demystifying AI for the Enterprise Prashant Natarajan, Bob Rogers, Edward Dixon, Jonas Christensen, Kirk Borne, Leland Wilkinson, Shantha Mohan, 2021-12-30 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. |
| ai in service management: The AI Book Ivana Bartoletti, Anne Leslie, Shân M. Millie, 2020-06-29 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 |
| ai in service management: The Palgrave Handbook of Service Management Bo Edvardsson, Bård Tronvoll, 2022-05-24 This handbook provides an innovative, thorough overview of service management. It draws together an impressive, international group of leading scholars who offer a truly global perspective, exploring current literature and laying out guidance for future research. Beginning with defining service as a perspective on value creation, and service management as “a set of organizational competencies for enabling and realizing value creation through service,” it then moves on to follow the evolution of service research. From there, the book is structured into six main themes: perspectives on service management; service strategy; service leadership and transition; service design and innovation; service interaction; quality and operations; and service management and technology. This book is valuable reading for academics, lecturers, and students studying service management, operations management, and service research. |
| ai in service management: Research Handbook on Public Management and Artificial Intelligence Yannis Charalabidis, Rony Medaglia, Colin van Noordt, 2024-02-12 This pioneering Research Handbook on Public Management and Artificial Intelligence provides a comprehensive overview of the potentials, challenges, and governance principles of AI in a public management context. Multidisciplinary in approach, it draws on a variety of jurisdictional perspectives and expertly analyses key topics relating to this socio-technical phenomenon. |
| ai in service management: Service Management and Marketing Principles Jay Kandampully, David J. Solnet, 2024-06-07 This book explores the service economy and challenges that all organizations face as goods and services make way for a world where customers (B2C) and businesses (B2B) seek seamless, thoughtful, and exceptional experiences. This book introduces readers to a range of interrelated topics and the application of service management and marketing theories which are fundamentally critical to the success of all enterprises seeking competitive advantage through enhanced customer experience. This book analyses management and marketing challenges in the service and experience economy and provides insights into how marketers and managers can strike a balance between supply, demand, price, and quality and leverage technology for operational efficiency and to better manage customer service and expectations. Through the coverage of critical foundational topics, from how value is created; the evolution of global economies from goods, services to experiences; foundations of customer-centric management; managing service workers; integrating human touch with high-tech service; and many others, the authors provide a holistic understanding of management in a complex, globally interconnected world. This book will be useful for students, researchers, and instructors of business management, marketing, commerce, and economics. It will also be of interest to professionals working in healthcare, retail, financial services, government hospitality, leisure, tourism, and other services. |
| ai in service management: Artificial Intelligence and International HRM Ashish Malik, Pawan Budhwar, 2023-05-22 This book offers an in-depth and recent account of the research in Artificial Intelligence (AI) technologies and how it is impacting and shaping the field of international human resource management (IHRM). Grounded in contemporary developments in the field of technological change and the Future of Work and the fourth industrial revolution (4IR), the book lays down a solid foundation by offering a comprehensive review of the field of AI and IHRM. It includes empirical research, including case studies of global MNEs and conceptual chapters focusing on the impact of AI on IHRM practices and therefore business-level outcomes of productivity, efficiency, and effectiveness through the adoption of AI-assisted HR applications. The chapters in this volume evaluate individual IHRM practices and study how they impact employee-level outcomes of job satisfaction, personalization, employee commitment and so on. Finally, the book concludes by identifying current gaps in the literature and offers directions for future research for scholars to develop and advance future research agendas in the field. This volume will be of great use to researchers, academics and students in the fields of business and management, especially those with a particular interest in new age technologies of operating business. The chapters in this book, except for Conclusion, were originally published as a special issue of The International Journal of Human Resource Management. |
| ai in service management: Artificial Intelligence in China Qilian Liang, Wei Wang, Jiasong Mu, Xin Liu, Zhenyu Na, Xiantao Cai, 2021-02-08 This book brings together papers presented at The 2nd International Conference on Artificial Intelligence in China (ChinaAI) 2020, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in artificial intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE). |
| ai in service management: Innovations in Older Adult Care and Health Service Management: A Focus on the Asia-Pacific Region Madhan Balasubramanian, Angie Shafei, Zhanming Liang, 2024-02-14 Population aging is a consistent global demographic trend. The growth in both the size and proportion of older adults has threatened the sustainability of health systems in meeting healthcare needs of the population. Countries in the Asia-Pacific Region may face even more complex health system challenges due to the diversity in culture, management and leadership styles, composition of health service provision, investment in research infrastructure and innovation adaptation, data availability, and gaps in information technology. The Asia-Pacific is home to more than half of the world’s population and comprises countries across five Asia-Pacific subregions: East and North-East Asia, North and Central Asia, Pacific, South East Asia, South, and South West Asia. The economies are diverse, including six high-income countries (such as Australia, Brunei, Japan, New Zealand, South Korea, and Singapore), low-income countries (Nepal and North Korea), and middle-income countries. The region also includes some of the fastest-growing economies in the world, including China, India, Malaysia, Thailand, Indonesia, and the Philippines. |
| ai in service management: Essential Information Systems Service Management Patel, Rahul K., 2024-09-27 As organizations navigate the complexities of modern information systems management (ISM), they face many challenges. Rapid technological advancements, changing workplace structures, and mainstreaming remote work have underscored the need for clear roles, responsibilities, and methods for interaction within ISM groups and with external stakeholders. This lack of clarity can lead to inefficiencies, inconsistencies, and even breakdowns in communication, hindering the organization's ability to manage its information systems effectively. Essential Information Systems Service Management serves as a comprehensive solution to the challenges of modern ISM. It uniquely compiles critical roles, responsibilities, workflows, processes, functions, and methods for successfully managing contemporary information systems. By providing a clear roadmap, this book empowers practitioners and students to navigate the evolving professional landscape confidently and competently, ensuring they can contribute effectively to their organizations. |
| ai in service management: Artificial Intelligence and Machine Learning for Business for Non-Engineers Stephan S. Jones, Frank M. Groom, 2019-11-22 The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI’s current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry. |
| ai in service management: The AI Advantage Thomas H. Davenport, 2019-08-06 Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review. |
| ai in service management: Artificial Intelligence and Cyber Security in Industry 4.0 Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi, 2023-07-15 This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications. |
| ai in service management: Progressive Decision-Making Tools and Applications in Project and Operation Management Mohammad Yazdi, |
| ai in service management: AI in Healthcare Robert Shimonski, 2021-01-27 The best source for cutting-edge insights into AI in healthcare operations AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services collects, organizes and provides the latest, most up-to-date research on the emerging technology of artificial intelligence as it is applied to healthcare operations. Written by a world-leading technology executive specializing in healthcare IT, this book provides concrete examples and practical advice on how to deploy artificial intelligence solutions in your healthcare environment. AI in Healthcare reveals to readers how they can take advantage of connecting real-time event correlation and response automation to minimize IT disruptions in critical healthcare IT functions. This book provides in-depth coverage of all the most important and central topics in the healthcare applications of artificial intelligence, including: Healthcare IT AI Clinical Operations AI Operational Infrastructure Project Planning Metrics, Reporting, and Service Performance AIOps in Automation AIOps Cloud Operations Future of AI Written in an accessible and straightforward style, this book will be invaluable to IT managers, administrators, and engineers in healthcare settings, as well as anyone with an interest or stake in healthcare technology. |
| ai in service management: The Future of Management in an AI World Jordi Canals, Franz Heukamp, 2019-10-07 Artificial Intelligence (AI) is redefining the nature and principles of general management. The technological revolution is reshaping industries, disrupting existing business models, making traditional companies obsolete and creating social change. In response, the role of the manager needs to urgently evolve and adjust. Companies need to rethink their purpose, strategy, organisational design and decision-making rules. Crucially they will also need to consider how to nurture and develop the business leaders of the future and develop new ways to interact with society on issues such as privacy and trust. Containing international insights from leading figures from the world of management and technology, this book addresses the big challenges facing organisations, including: · Decision-making · Corporate strategy · People management and leadership · Organisational design Taking a holistic approach, this collection of expert voices provides valuable insight into how firms will discover and commit to what makes them unique in this new big data world, empowering them to create and sustain competitive advantage. |
| ai in service management: Research Handbook on Services Management Davis, Mark M., 2022-08-05 This comprehensive Research Handbook reflects the latest research breakthroughs and practices in services management. Addressing services management from a broader strategic perspective, it delves into the key issues of analytics and service robots, and their potential impact. Edited by the late Mark M. Davis, it represents an early foray into the new frontier of services management and provides insights into the future of the field. |
| ai in service management: Data Mining and Machine Learning Applications Rohit Raja, Kapil Kumar Nagwanshi, Sandeep Kumar, K. Ramya Laxmi, 2022-03-02 DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly. |
| ai in service management: Enterprise Service Management (ESM) Enamul Haque, 2022-12-19 This book has the most simplified explanations of Enterprise Service Management with little technical jargon. Enterprise Service Management (ESM) describes how organisations aim to maximise value creation in line with the organisation's mission. It provides a source of elegance and structure when the world becomes more chaotic, with new techniques and technology vying for our attention. In this book, we explored some key trends driving ESM adoption across industries today. These include cloud computing, DevOps workflows, AI, blockchain, metaverse and many other collaboration tools, which have become increasingly popular with IT organisations over the past few years. You will find step-by-step guidelines for streamlining your ESM journey and other corporate objectives. You will understand business disruption and digital transformation – all influencing such adoption for an enterprise to function today. The main features include setting up your ESM strategy, ESM implementation methods, ESM operating model, and future trends in ITSM. We looked into the metaverse, blockchain, ESG etc., their ways of shaping the ESM platforms, and many more features that the ESM roadmap would require. |
| ai in service management: Artificial Intelligence in Customer Service Jagdish N. Sheth, Varsha Jain, Emmanuel Mogaji, Anupama Ambika, 2023-08-17 This edited volume elucidates how artificial intelligence (AI) can enable customer service to achieve higher customer engagement, superior user experiences, and increased well-being among customers and employees. As customer expectations dictate 24/7 availability from service departments and market pressures call for lower costs with higher efficiency, businesses have accepted that AI is vital in maintaining customer satisfaction. Yet, firms face tough challenges in choosing the right tool, optimizing integration, and striking the appropriate balance between AI systems and human efforts. In this context, chapters in this book capture the latest advancements in AI-enabled customer service through real-world examples. This volume offers a global perspective on this contemporary issue, covering topics such as the use of AI in enhancing customer well-being, data and technology integration, and customer engagement. |
| ai in service management: AI-Based Services for Smart Cities and Urban Infrastructure Lyu, Kangjuan, Hu, Min, Du, Juan, Sugumaran, Vijayan, 2020-09-04 Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students. |
| ai in service management: Service Management John R. Bryson, Jon Sundbo, Lars Fuglsang, Peter Daniels, 2020-11-26 This textbook offers a fully integrated approach to the theory and practice of service management, exploring the operational dynamics, management issues and business models deployed by service firms. It builds on recent developments in service science as an interdisciplinary research area with emphasis on integration, adaptability, optimization, sustainability and rapid technological adoption. The book explores seven fundamental processes that are key to successfully managing service businesses, helping students gain insights into: how to manage service businesses, with coverage of both small firms and large transnationals service business models, operations and productivity managing service employees how service firms engage in product and process innovation marketing, customers and service experiences internationalization of service businesses the ongoing servitization of manufacturing This unique textbook is an ideal resource for upper undergraduate and postgraduate students studying service businesses and practitioners. |
| ai in service management: Transforming the IT Services Lifecycle with AI Technologies Kristof Kloeckner, John Davis, Nicholas C. Fuller, Giovanni Lanfranchi, Stefan Pappe, Amit Paradkar, Larisa Shwartz, Maheswaran Surendra, Dorothea Wiesmann, 2018-09-20 As more and more industries are experiencing digital disruption, using information technology to enable a competitive advantage becomes a critical success factor for all enterprises. This book covers the authors’ insights on how AI technologies can fundamentally reshape the IT services delivery lifecycle to deliver better business outcomes through a data-driven and knowledge-based approach. Three main challenges and the technologies to address them are discussed in detail: · Gaining actionable insight from operational data for service management automation and improved human decision making · Capturing and enhancing expert knowledge throughout the lifecycle from solution design to ongoing service improvement · Enabling self-service for service requests and problem resolution, through intuitive natural language interfaces The authors are top researchers and practitioners with deep experience in the fields of artificial intelligence and IT service management and are discussing both practical advice for IT teams and advanced research results. The topics appeal to CIOs and CTOs as well as researchers who want to understand the state of the art of applying artificial intelligence to a very complex problem space. Although the book is concise, it comprehensively discuss topics like gaining insight from operational data for automatic problem diagnosis and resolution as well as continuous service optimization, AI for solution design and conversational self-service systems. |
| ai in service management: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| ai in service management: The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume 2 Sezer Bozkuş Kahyaoğlu, 2022-05-20 This book continues the discussion of the effects of artificial intelligence in terms of economics and finance. In particular, the book focuses on the effects of the change in the structure of financial markets, institutions and central banks, along with digitalization analyzed based on fintech ecosystems. In addition to finance sectors, other sectors, such as health, logistics, and industry 4.0, all of which are undergoing an artificial intelligence induced rapid transformation, are addressed in this book. Readers will receive an understanding of an integrated approach towards the use of artificial intelligence across various industries and disciplines with a vision to address the strategic issues and priorities in the dynamic business environment in order to facilitate decision-making processes. Economists, board members of central banks, bankers, financial analysts, regulatory authorities, accounting and finance professionals, chief executive officers, chief audit officers and chief financial officers, chief financial officers, as well as business and management academic researchers, will benefit from reading this book. |
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