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Advancements in intelligent process ...
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IGI Global.
Advancements in intelligent process automation
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Advancements in intelligent process automationDhanabalan Thangam, editor.
作者:
Thangam, Dhanabalan,
出版者:
Hershey, Pennsylvania :IGI Global,2025.
面頁冊數:
1 online resource (2 volumes (776 p.))
標題:
Production managementData processing.
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-5380-6
ISBN:
9798369353820$q(ebook)
Advancements in intelligent process automation
Thangam, Dhanabalan,1985-
Advancements in intelligent process automation
[electronic resource] /Dhanabalan Thangam, editor. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (2 volumes (776 p.)) - Advances in computational intelligence and robotics (ACIR) book series. - Advances in computational intelligence and robotics (ACIR) book series..
Includes bibliographical references and index.
Foreword -- Preface -- Acknowledgment -- Chapter 1. The Digital Transformation of Work: How Will Automation Alter Future Workplaces? -- Chapter 2. Integrating Intelligent Process Automation With Human Resource Management for Enhancing Efficiency and Strategic Decision-Making -- Chapter 3. Human Resource Management in the Epoch of Generative AI: Opportunities and Challenges -- Chapter 4. Human Resource Management Practices in the Age of Industrial Automation: Impact, Adoption, and Future Workforce -- Chapter 5. Navigating the Opportunities and Challenges of AI and Automation in Human Resource Development -- Chapter 6. Artificial Intelligence for Sustainable Futures: Navigating Social and Environmental Responsibility -- Chapter 7. Promoting Fairness and Ethical Practices in AI-Based Performance Management Systems: A Comprehensive Literature Review of Bias Mitigation and Transparency -- Chapter 8. Automating Athletic Excellence Through Intelligent Process Automation and Sports Analytics -- Chapter 9. Exploring the Intersection of Social Work and the Future of Technology -- Chapter 10. Indian Road Damage Detection Using Deep Learning -- Chapter 11. Cloud Computing Paradigms with the Internet of Things for Automating Business Processes -- Chapter 12. Enhancing Agriculture Through AI Vision and Machine Learning: The Evolution of Smart Farming -- Chapter 13. Emerging Trends of Graphene-Based Nanomaterials as DigitalMaterials for Data Generation in Industry 4.0 -- Chapter 14. Intelligent Machine Learning Solutions for Cybersecurity: Legal and Ethical Considerations in a Global Context -- Chapter 15. Intelligent Process Automation and Its Relevance to Various Industries -- Chapter 16. Intelligent Process Automation and Its Implications for the Marketing Industry -- Chapter 17. Leveraging Intelligent Process Automation for Customer Engagement in Sales and Marketing -- Chapter 18. Empowering Distributors by Leveraging Consumer Tenacity With Advanced Marketing Intelligence Systems and Intelligent Process Automation -- Chapter 19. Predictive Analytics: Facilitating the Process of Supply Chain Automation -- Chapter 20. Role of Intelligent Process Automation in the Banking and Financial Services Industry -- Chapter 21. Unleashing the Power of AI for Intelligent Investments: Revolutionizing Stock Market Trading -- Chapter 22. Human Evaluation in Large Language ModelTesting: Assessing the Quality of AI Model Output -- Chapter 23. Emerging Trends and Innovations of Artificial Intelligence in the Accounting and Financial Landscape -- Compilation of References -- About the Contributors -- Index.
"In the current fast-paced business environment, organizations face the challenge of improving operational efficiency and driving innovation while dealing with complex technological landscapes. Many organizations require assistance exploiting intelligent process automation's full potential (IPA). This is often due to a need for more comprehensive understanding or clear implementation strategies. As a result, they need to help their workflows, optimize resources, and adapt effectively to changing market demands. Advancements in Intelligent Process Automation bridges this gap by providing a holistic view of IPA, encompassing RPA, AI, and ML, among other key technologies. Through real-world case studies, strategic guidelines, and interdisciplinary perspectives, the book offers actionable insights that are not just theoretical, but practical and implementable. This ensures that organizations seeking to implement IPA can do so seamlessly, without feeling overwhelmed or unsure. Addressing ethical and regulatory considerations ensures responsible AI practices and compliance, fostering a sustainable approach to automation."--
Mode of access: World Wide Web.
ISBN: 9798369353820$q(ebook)Subjects--Topical Terms:
189489
Production management
--Data processing.Subjects--Index Terms:
AI-Driven Customer Analytics.Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: TS155.6 / .T43 2025eb
Dewey Class. No.: 658.500285
Advancements in intelligent process automation
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Foreword -- Preface -- Acknowledgment -- Chapter 1. The Digital Transformation of Work: How Will Automation Alter Future Workplaces? -- Chapter 2. Integrating Intelligent Process Automation With Human Resource Management for Enhancing Efficiency and Strategic Decision-Making -- Chapter 3. Human Resource Management in the Epoch of Generative AI: Opportunities and Challenges -- Chapter 4. Human Resource Management Practices in the Age of Industrial Automation: Impact, Adoption, and Future Workforce -- Chapter 5. Navigating the Opportunities and Challenges of AI and Automation in Human Resource Development -- Chapter 6. Artificial Intelligence for Sustainable Futures: Navigating Social and Environmental Responsibility -- Chapter 7. Promoting Fairness and Ethical Practices in AI-Based Performance Management Systems: A Comprehensive Literature Review of Bias Mitigation and Transparency -- Chapter 8. Automating Athletic Excellence Through Intelligent Process Automation and Sports Analytics -- Chapter 9. Exploring the Intersection of Social Work and the Future of Technology -- Chapter 10. Indian Road Damage Detection Using Deep Learning -- Chapter 11. Cloud Computing Paradigms with the Internet of Things for Automating Business Processes -- Chapter 12. Enhancing Agriculture Through AI Vision and Machine Learning: The Evolution of Smart Farming -- Chapter 13. Emerging Trends of Graphene-Based Nanomaterials as DigitalMaterials for Data Generation in Industry 4.0 -- Chapter 14. Intelligent Machine Learning Solutions for Cybersecurity: Legal and Ethical Considerations in a Global Context -- Chapter 15. Intelligent Process Automation and Its Relevance to Various Industries -- Chapter 16. Intelligent Process Automation and Its Implications for the Marketing Industry -- Chapter 17. Leveraging Intelligent Process Automation for Customer Engagement in Sales and Marketing -- Chapter 18. Empowering Distributors by Leveraging Consumer Tenacity With Advanced Marketing Intelligence Systems and Intelligent Process Automation -- Chapter 19. Predictive Analytics: Facilitating the Process of Supply Chain Automation -- Chapter 20. Role of Intelligent Process Automation in the Banking and Financial Services Industry -- Chapter 21. Unleashing the Power of AI for Intelligent Investments: Revolutionizing Stock Market Trading -- Chapter 22. Human Evaluation in Large Language ModelTesting: Assessing the Quality of AI Model Output -- Chapter 23. Emerging Trends and Innovations of Artificial Intelligence in the Accounting and Financial Landscape -- Compilation of References -- About the Contributors -- Index.
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"In the current fast-paced business environment, organizations face the challenge of improving operational efficiency and driving innovation while dealing with complex technological landscapes. Many organizations require assistance exploiting intelligent process automation's full potential (IPA). This is often due to a need for more comprehensive understanding or clear implementation strategies. As a result, they need to help their workflows, optimize resources, and adapt effectively to changing market demands. Advancements in Intelligent Process Automation bridges this gap by providing a holistic view of IPA, encompassing RPA, AI, and ML, among other key technologies. Through real-world case studies, strategic guidelines, and interdisciplinary perspectives, the book offers actionable insights that are not just theoretical, but practical and implementable. This ensures that organizations seeking to implement IPA can do so seamlessly, without feeling overwhelmed or unsure. Addressing ethical and regulatory considerations ensures responsible AI practices and compliance, fostering a sustainable approach to automation."--
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AI-Driven Customer Analytics.
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Automation in Supply Chain and Logistics.
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Business Process Modeling and Automation.
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Competitive Advantage Through Automation.
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Compliance Monitoring Using Automation.
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Control Theory in Automation Systems.
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Cyber-Physical Systems for Monitoring.
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Deep Learning for Process Optimization.
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