Ai Oriented Competency Framework For Talent Management In The Digital Economy

In the digital-driven economy era, an AI-oriented competency framework (AIoCF) is a collection to identify AI-oriented knowledge, attributes, efforts, skills, and experiences (AKASE) that directly and positively affect the success of employees and the organization. The application of skills-based competency analytics and AI-equipped systems is gradually becoming accepted by business and production organizations as an effective tool for automating several managerial activities consistently and efficiently in developing and moving the capacity of a company up to a world-class level. AI-Oriented Competency Framework for Talent Management in the Digital Economy: Models, Technologies, Applications, and Implementation discusses all the points of an AIoCF, which includes predictive analytics, advisory services, predictive maintenance, and automated processes, which help to make the operations of project management, personnel management, or administration more efficient, profitable, and safe. The book includes the functionality of emerging career pathways, hybrid learning models, and learning paths related to the learning and development of employees in the production or delivery fields. It also presents the relationship between skills taxonomy and competency framework with interactive methods using datasets, processing workflow diagrams, and architectural diagrams for easy understanding of the application of intelligent functions in role-based competency systems. By also covering upcoming areas of AI and data science in many government and private organizations, the book not only focuses on managing big data and cloud resources of the talent management system but also provides cybersecurity techniques to ensure that systems and employee competency data are secure. This book targets a mixed audience of students, engineers, scholars, researchers, academics, and professionals who are learning, researching, and working in the field of workforce training, human resources, talent management systems, requirement, headhunting, outsourcing, and manpower consultant services from different cultures and industries in the era of digital economy.

This book investigates the growing influence of artificial intelligence in the marketing sphere, providing insights into how AI can be harnessed for developing more effective and efficient marketing strategies. In addition, the book will also offer a comprehensive overview of the various digital marketing tools available to entrepreneurs, discussing their features, benefits, and potential drawbacks. This will help entrepreneurs make well-informed decisions when selecting the tools most suited to their needs and objectives. It is designed to help entrepreneurs develop and implement successful strategies, leveraging the latest tools and technologies to achieve their business goals. As the digital landscape continues to evolve rapidly, this book aims to serve as a valuable resource for entrepreneurs looking to stay ahead of the curve and capitalize on new opportunities. The book's scope encompasses a wide range of topics, including customer experience, content marketing, AI strategy, and digital marketing tools.

The application of internet of things (IoT) technologies and artificial intelligence (AI)-enabled IoT solutions has gradually become accepted by business and production organizations as an effective tool for automating several activities effectively and efficiently and developing and distributing products to the global market. Within this book, the reader will learn how to implement IoT devices, IoT-equipped machines, and AI-equipped IoT applications using models and methodologies along with an array of case studies. Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy covers the basics of IoT-equipped machines in developing and managing various activities in many industries. It discusses all of the key points of an AI-enabled IoT solution, which includes predictive analytics, robotic process automation, predictive maintenance, automated processes, IoT technologies and IoT-equipped sensors related to machines and processes, production testing systems, and product assessment processes in the production environment. The book presents the concepts and interactive methods using datasets, processing workflow charts, and architectural diagrams along with additional real-time systems for easy and fast understanding of the application of IoT-equipped machines and AI-enabled solutions in organizations and includes many case studies throughout the book to enforce reader comprehension. This book is an ideal read for industry specialists, practitioners, researchers, scientists, and engineers working or involved in the fields of Robotics, IT, Computer Science, Soft Computing, IoT, AL/ML/DL, Data Science, the Semantic Web, Knowledge Engineering, and other related fields.

Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.

This book brings insight to the HR management system and offers data-centric approaches and AI-enabled applications for the design and implementation strategies used for workforce development and management. Designing Workforce Management Systems for Industry 4.0: Data-Centric and AI-Enabled Approaches focuses on the mechanisms of proposing solutions along with architectural concepts, design principles, smart solutions, and intelligent predictions with visualization simulation. Data visualization for the metrics of management systems and robotic process automation applications and tools are also offered. This book is also useful as a reference for those involved in AI-enabled applications, data analytics, data visualization, as well as systems engineering and systems designing.

This book covers the need for Internet of Things (IoT) technologies and artificial intelligence (AI)–aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. AI-Aided IoT Technologies and Applications for Smart Business and Production shows how a variety of IoT technologies can be used toward integrating data fabric solutions and how intelligent applications can be used to greater effect in business and production operations. The book also covers the integration of IoT data-driven financial technology (fintech) applications to fulfill the goals of trusted AI-aided IoT solutions. Next, the authors show how IoT-based technology uses algorithms and AI models to bring out the desired results across various industries including smart cities, buildings, hospitals, hotels, homes, factories, agriculture, transportation, and more. The last part focuses on AI-aided IoT techniques, data analytics, and visualization tools. This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, and professionals. It will be useful to engineering officers, IoT and AI engineers, engineering and industrial management students, and research scholars looking for new ideas, methodologies, technologies, models, frameworks, theories, and practices to resolve the challenging issues associated with leveraging IoT technologies, data-driven analytics, AI-aided models, IoT cybersecurity, 5G, sensors, and augmented and virtual reality techniques for developing smart systems in the era of Industrial Revolution 4.0.

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0. AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries. This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields.

This book examines computer vision and IoT-integrated technologies used by medical professionals in decision-making, for sustainable development in a healthcare ecosystem, and to better serve patients and stakeholders. It looks at the methodologies, technologies, models, frameworks, and practices necessary to resolve the challenging issues associated with leveraging the emerging technologies driving the medical field. The chapters discuss machine vision, AI-driven computer vision, machine learning, deep learning, AI-integrated IoT technology, data science, blockchain, AR/VR technology, cloud data, and cybersecurity techniques in designing and implementing a smart healthcare infrastructure in the era of the Industrial Revolution 4.0. Techniques are applied to the detection, diagnosis, and monitoring of a wide range of health issues. Computer Vision and AI-Integrated IoT Technologies in the Medical Ecosystem targets a mixed audience of students, engineers, researchers, academics, and professionals who are researching and working in the field of medical and healthcare industries from different environments and countries.