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Business Management The Transformative Power of Artificial Intelligence in Learning and Development
Editor: Dr. Aastha Tripathi
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CALL FOR BOOK CHAPTERS Pub Date: Hardback Price: Hard ISBN: Pages: Binding Type: |
CALL FOR BOOK CHAPTERS
Short description about the volume:
The book The Transformative Power of Artificial Intelligence in Learning and Development will present a systematic framework for the integration of artificial intelligence within learning and development (L&D) paradigms. This text will offer a comprehensive exploration of AI’s application, elucidating its capacity to facilitate personalized learning experiences, improve accessibility, augment learner engagement, automate procedural tasks, and establish robust evaluative metrics. By deconstructing the complexities of AI and contextualizing its relevance to L&D, the book will furnish practitioners, organizational leaders, and stakeholders with actionable insights and practical strategies. The narrative plans to encompass the strategic deployment of AI tools, the formulation of implementation strategies, and the quantitative assessment of impact, thereby enabling readers to effectively navigate the dynamic confluence of AI and L&D. This resource will serve as a guide for those seeking to leverage AI to optimize learning and development outcomes.
This book will elucidate the application of Artificial Intelligence in facilitating a systematic approach to human capital development. Specifically, it addresses the utilization of AI to execute thorough training needs analyses, diagnose granular competency deficits at the individual level, and formulate precise developmental interventions aligned with critical skill enhancement domains. This process enables employees to engage in sustained professional growth, thereby fostering a workforce equipped with the requisite competencies to navigate and succeed within evolving organizational contexts.
Coverage:
Prospective contributors are invited to submit scholarly manuscripts for inclusion in the forthcoming edited volume. The scope of the publication encompasses, but is not limited to, the following thematic areas:
INVITED CHAPTERS:
Chapter 1: Foundations of Employee Training and Development in the Age of Artificial Intelligence
This chapter establishes the conceptual framework for employee training and development, with a specific focus on the burgeoning integration of artificial intelligence (AI) to augment conventional methodologies. It examines the utilization of AI in the design of efficacious training curricula and the facilitation of individualized learning pathways. Furthermore, it analyzes the dynamic forces shaping contemporary learning paradigms in the context of AI implementation. An overview of global training initiatives employing AI is presented, thereby providing a foundational understanding of its prospective influence on the cultivation of a competent workforce.
Chapter 2: The Evolution of Learning Needs Assessment
This chapter delineates the integration of artificial intelligence (AI) into the process of organizational learning needs assessment (LNA), a critical function for strategic human capital development. Traditional LNA methodologies, while valuable, often suffer from limitations in scalability, objectivity, and the capacity to process complex, dynamic data. The incorporation of AI technologies offers a pathway to mitigate these constraints, facilitating a more precise and adaptive approach to identifying and addressing organizational learning gaps.
Chapter 3: Employing AI for the Strategic Analysis of Needs, Enabling Data-Driven Decision-Making
This chapter provides integration of artificial intelligence methodologies to allow for the sophisticated, algorithmic analysis of complex needs assessments. This process transforms raw data into structured, interpretable information, thereby empowering organizations to adopt data-driven decision-making frameworks that are informed by rigorous empirical evidence.
Chapter 4: The Effect of Leadership on Employee Innovation with AI
The integration of artificial intelligence (AI) into leadership roles represents a nascent yet rapidly evolving field of inquiry. This analysis aims to explore the potential impact of AI leadership, defined as the deployment of AI systems to perform managerial functions such as decision-making, task allocation, and performance evaluation, on employee innovation. Specifically, we will examine the theoretical frameworks and potential mechanisms through which AI leadership may influence the generation and implementation of novel ideas within organizations.
Chapter 5: AI-driven Innovation in the Development of Intercultural Competence
This section explains the importance of the integration of artificial intelligence (AI) into the development of intercultural competence represents a significant advancement in educational and professional training. This integration leverages AI’s capabilities to provide personalized, adaptive, and immersive learning experiences, thereby enhancing individuals’ ability to navigate and interact effectively across cultural boundaries.
Chapters 6: AI-Powered Performance Feedback and Coaching
This chapter explores how AI-powered performance feedback and coaching represent a paradigm shift in organizational talent development, leveraging artificial intelligence to enhance the efficacy and efficiency of traditional feedback and coaching processes. This technology integrates machine learning, natural language processing, and data analytics to provide personalized, data-driven insights that foster employee growth and optimize performance.
Chapter 7: AI-Driven Strategies for Workforce Development and Professional Advancement
This chapter presents an examination of the application of artificial intelligence to optimize employee development and career management. Specifically, it analyzes: (1) the utilization of AI for precise skills gap analysis, enabling the identification of individual development requirements through the synthesis of current competencies, projected job demands, and evolving industry trends; (2) the implementation of AI-enabled personalized career coaching and mentoring, facilitating tailored guidance and support for professional advancement, encompassing the curation of pertinent learning materials and developmental opportunities; and (3) the deployment of AI-driven talent management systems, designed to align employee skills and career aspirations with prospective organizational roles, thereby promoting talent retention and internal advancement.
Chapter 8: Ethical Dimensions of AI-Driven Learning and Development, encompassing Social Responsibility and Diversity
This chapter provides an analysis of the interplay between work-life equilibrium, organizational diversity and inclusion, and the integration of artificial intelligence in these domains. Furthermore, it examines the ethical dimensions of employing AI within learning and development, specifically addressing: (1) the mitigation of algorithmic bias and the promotion of equitable outcomes for diverse learner populations; (2) the provision of transparent and comprehensible AI-driven decision-making processes; and (3) the safeguarding of learner privacy and data integrity within AI-enhanced training ecosystems.
Chapter 9: Integration of AI in Organizational Learning
This chapter presents how the integration of AI in organizational learning is transforming how companies develop their workforce. AI empowers personalized learning experiences by analyzing individual employee data, tailoring training paths, and providing adaptive content that adjusts to each learner’s pace and needs. AI also automates administrative tasks, freeing up learning and development professionals to focus on strategic initiatives. Furthermore, AI-driven analytics provide valuable insights into learning effectiveness, identifying skill gaps, and predicting future training requirements, enabling organizations to proactively address evolving business demands. Ultimately, AI fosters a more dynamic, efficient, and impactful learning environment, promoting continuous skill development and enhancing organizational agility.
Chapter 10: Collaborative AI Applications in the Advancement of Learning and Development
This concluding chapter synthesizes the preceding discourse by projecting the trajectory of Learning and Development (L&D) in the context of artificial intelligence (AI). It underscores the imperative of a synergistic human-AI paradigm. Specifically, the chapter elucidates two pivotal considerations: firstly, the necessity for sustained professional development and skill augmentation among L&D practitioners to facilitate efficacious AI utilization; and secondly, the strategic incorporation of AI technologies into L&D frameworks to augment and optimize extant methodologies.
Important Dates:
Initial Proposal/Extended Structured Abstract Submission (400 - 600 words) Deadline: March 31st, 2025
Notification of Acceptance: April 05th, 2025
Full Chapter (8,000 - 10,000 words) Submission Due: On or before April 30th, 2025
SUBMISSION PROCEDURE:
Prospective authors are requested to submit their Extended Structured Abstract/full-length chapters as an email attachment in a Word file to:
For Indian & International Authors:
Editor: Dr. Aastha Tripathi
Email: editors4ai@gmail.com
Please find a few quick points below to adhere:
1. For reference, please follow APA style (from the American Psychological Association) and be consistent throughout the book using recent references. For this purpose, refer to the Publication Manual of the American Psychological Association, 6th Edition. Information can also be found at https://www.library.cornell.edu/research/citation/apa and http://www.landmark.edu/m/uploads/APA-Citation-Guide 6th-ed.pdf.
2. Please use Times New Roman 11-point font with 1.5 spacing for preparing the manuscript.
3. All text, figures, equations, and images should be in open (editable) format, usually in Microsoft Word format, as we may need to perform enhancements on them. Please provide them in at least 300 dpi.
4. A concisely worded title should be provided.
5. Please provide the manuscript in American English with proper proofreading before submitting.
6. Please note that most of the illustrations and tables in the book should be original and have not published elsewhere (including online). If you wish to include figures/tables that have been published prior, proper permission is necessary. You MUST provide permission document of some sort (Copyright Clearance Center document, signed form, email, letter, etc.) that allows reuse at no charge. Open-source publications usually require a reference to the original publication, which is courtesy to the original author as well. You will frequently see how you should indicate source WITH the table or figure also. Please include that note in your manuscript with the figure/table caption or title.
7. The generation or reporting of chapter using a generative AI tool/Large scale generative models is not permissible, as per AAP’s authorship criteria, the author(s) must be responsible for the creation and interpretation of their work and accountable for its accuracy, integrity, and validity.
8. At AAP, we welcome submissions for consideration which are original and not under consideration for any other publication at the same time. All authors should be aware of the importance of presenting content that is based on their own research and expressed in their own words.
9. Please also provide Turnitin report along with your submitted chapter with us.
10. If chapter gets accepted to publish in this book, we will require signed Copyright Transmittal Forms (along with the figure/table chart) from each lead chapter author, which is already available here.
guidelines for chapter preparation: https://appleacademicpress.com/download/AAP_MS_INSTRUX.pdf
Note: There is no publication fee for manuscripts submitted to this book publication. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere.
About the Authors / Editors: Editor: Dr. Aastha TripathiAssistant Professor, Centre for Social and Organisational Leadership,
School of Management and Labour Studies, Tata Institute of Social Sciences (TISS), Mumbai, Maharashtra, India
Dr. Aastha Tripathi is an Assistant Professor at the School of Management and Labour Studies, Tata Institute of Social Sciences (TISS), Mumbai, Maharashtra, India, in the area of Human Resource Management/Organisational Behaviour. Before this, she worked as a post-doctoral researcher at the Indian Institute of Management, Ahmedabad (IIMA). She also worked as a senior research scientist with the Indian Institute of Technology, Delhi (IITD). She has recently been conferred with the prestigious Young Woman Researcher in Human Resource Management Award by the Venus International Foundation. Her areas of interest are leadership, learning agility, learning culture, employee attitudes, and behaviours. She serves as a reviewer in various A and A* category journals. She serves as an Associate Editor on the International Journal of Knowledge Management (ABDC-B). She also serves as an Editorial Advisory Member on the Business Process Management Journal (SSCI/Q1), Journal of Human Values (SSCI/Q1), International Journal of Technology & Human Interaction (ABDC), and International Journal of Organisational Analysis (ABDC-B), to name a few. She has published in top-notch journals (such as the American Business Review, International Journal of Organisational Analysis, Journal of Public Affairs, Innovation: Organization & Management, The Hindu, Economic Times, Ivey Publishing, to name a few.
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