Call for Chapters: Addressing Faculty Anxiety Amid AI Transformation in Education

Editors

CEMİLE ŞEKER, Bahçeşehir University, Cyprus

Call for Chapters

Proposals Submission Deadline: June 14, 2026
Full Chapters Due: August 16, 2026
Submission Date: August 16, 2026

Introduction

The rapid advancement of artificial intelligence (AI) technologies has initiated a profound transformation across multiple sectors, with education emerging as one of the most significantly impacted domains. From intelligent tutoring systems to automated assessment tools and generative AI applications, these developments are reshaping teaching methodologies, learning environments, and institutional structures. While AI offers substantial opportunities to enhance educational quality, efficiency, and accessibility, it simultaneously introduces complex challenges—particularly for faculty members who are expected to adapt to these evolving technological landscapes. One of the most critical yet underexplored dimensions of this transformation is faculty anxiety related to AI integration. Faculty members often experience concerns regarding job security, role ambiguity, technological competence, ethical implications, and the potential erosion of traditional pedagogical values. These anxieties may hinder the effective adoption of AI tools, reduce teaching performance, and negatively influence organizational learning processes within educational institutions. Despite the growing body of literature on AI in education, there remains a limited focus on the psychological and behavioral responses of faculty members, especially within the context of rapid digital transformation. The primary aim of this study is to examine the nature, sources, and consequences of faculty anxiety in the context of AI-driven transformation in education, and to propose strategic approaches to manage and mitigate these concerns. Specifically, the study seeks to identify how AI-related anxiety influences faculty attitudes, teaching effectiveness, and adaptability, while also exploring institutional mechanisms that can foster resilience and acceptance. The rationale behind this research stems from the recognition that technological transformation is not solely a technical process but also a deeply human-centered one. Educational institutions cannot fully benefit from AI innovations without addressing the emotional and cognitive responses of their key stakeholders—faculty members. Ignoring faculty anxiety may lead to resistance to change, reduced innovation capacity, and a misalignment between institutional goals and individual readiness. Therefore, understanding and managing this anxiety is not only a psychological necessity but also a strategic imperative for sustainable educational development. In terms of its contribution to the literature, this study aims to fill a critical gap by integrating perspectives from organizational behavior, educational technology, and psychological adaptation. Unlike prior studies that predominantly focus on the technical capabilities of AI or student outcomes, this research places faculty members at the center of the transformation process. It contributes by conceptualizing AI-related faculty anxiety as a multidimensional construct, examining its antecedents and outcomes, and offering a framework that links anxiety with organizational learning, innovation readiness, and digital culture. Furthermore, the study provides practical insights for policymakers and institutional leaders on how to design supportive environments that facilitate effective AI integration while safeguarding faculty well-being. In conclusion, as AI continues to redefine the boundaries of education, addressing the human side of this transformation becomes increasingly critical. By focusing on faculty anxiety, this study not only advances theoretical understanding but also offers actionable pathways for creating more adaptive, inclusive, and resilient educational systems.

Objective

The main objective of this study is to examine faculty anxiety arising from the integration of artificial intelligence (AI) in education and to explore its implications for teaching effectiveness, adaptability, and organizational outcomes. In line with this overarching aim, the specific objectives of the study are as follows: • To identify the key sources and dimensions of faculty anxiety related to AI technologies in educational settings. • To analyze the impact of AI-related anxiety on faculty attitudes, teaching performance, and willingness to adopt new technologies. • To examine the relationship between faculty anxiety and organizational factors such as digital culture, institutional support, and organizational learning. • To explore how faculty anxiety influences innovation readiness and resistance to technological change within educational institutions. • To develop a conceptual framework that explains the role of faculty anxiety in the AI-driven transformation of education. • To propose practical strategies and recommendations for reducing faculty anxiety and supporting effective AI integration in educational environments.

Target Audience

This study is designed for a diverse audience involved in the intersection of education, technology, and organizational development. Primarily, the target audience includes faculty members and educators who are directly affected by the integration of artificial intelligence (AI) in teaching and learning processes. The study aims to provide insights that can help them better understand and manage the anxieties associated with technological transformation. Secondly, the study addresses academic administrators, university leaders, and policymakers who are responsible for implementing AI-driven strategies in educational institutions. The findings offer guidance for developing supportive policies, fostering digital culture, and creating environments that reduce resistance to change. Additionally, the research is relevant to scholars and researchers in the fields of organizational behavior, educational technology, and higher education studies. By introducing faculty anxiety as a critical construct, the study contributes to ongoing academic discussions and opens new avenues for empirical research. The study also targets instructional designers, edtech professionals, and consultants who develop and implement AI-based tools in education. Understanding faculty concerns can help them design more user-friendly, inclusive, and effective technological solutions. Finally, this work may be beneficial for graduate students and future educators, who are preparing to enter a rapidly evolving academic environment shaped by digital transformation and AI technologies.

Recommended Topics

1. Artificial Intelligence in Education: Concepts, Tools, and Trends This chapter provides a theoretical foundation by examining the fundamental concepts of artificial intelligence in education, commonly used tools (e.g., generative AI, adaptive learning systems), and current trends. 2. The Digital Transformation of Higher Education This chapter explores the process of digital transformation in higher education, including the acceleration after the pandemic, emerging learning models, and institutional transformation strategies. 3. Understanding Faculty Anxiety in the Age of AI This chapter conceptually explains the types of anxiety experienced by faculty members in response to AI (e.g., technological, professional, ethical) and their underlying causes. 4. Psychological Responses to Technological Change This chapter examines individuals’ psychological responses to technological change (e.g., resistance, stress, adaptation, learned helplessness) from an organizational behavior perspective. 5. AI Anxiety and Its Impact on Teaching Effectiveness This chapter analyzes the effects of AI-related anxiety on teaching performance, classroom interaction, and pedagogical quality. 6. Faculty Readiness and Digital Competence This chapter investigates faculty members’ levels of digital competence, technology acceptance, and their ability to use AI tools effectively. 7. The Role of Organizational Support in Reducing Anxiety This chapter evaluates the role of leadership, training programs, technical support, and organizational culture in reducing faculty anxiety within universities. 8. Digital Culture and Organizational Learning in AI Adoption This chapter discusses the impact of digital culture and organizational learning on AI adoption and examines the concept of learning organizations in academic institutions. 9. Ethical Concerns and Academic Integrity in AI Use This chapter addresses the ethical dimensions of AI use, including academic integrity, plagiarism, data privacy, and accountability. 10. AI and the Changing Role of the Educator This chapter analyzes how the role of educators is evolving in the age of AI, particularly the shift from knowledge transmitters to facilitators. 11. Resistance to Change: Causes and Management Strategies This chapter explores the causes of faculty resistance to change and discusses strategic approaches for managing and overcoming this resistance. 12. AI, Innovation, and Academic Performance This chapter examines the impact of AI on academic innovation, research productivity, and institutional performance. 13. Best Practices for Integrating AI in Teaching This chapter presents successful examples, best practices, and case studies of effective AI integration in teaching. 14. Faculty Training and Development for AI Adaptation This chapter focuses on training programs, digital skill development strategies, and continuous learning approaches for faculty adaptation to AI. 15. Student Perspectives on AI and Faculty Competence This chapter analyzes students’ perceptions and expectations regarding faculty members who use AI in education. 16. Policy and Governance in AI-Driven Education This chapter evaluates educational policies, regulatory frameworks, and institutional AI strategies in higher education. 17. The Future of Education: Human–AI Collaboration This chapter presents future scenarios and predictions on how human–AI collaboration will shape education. 18. A Conceptual Model for Managing Faculty Anxiety in AI Transformation This chapter proposes a theoretical model that integrates the book’s themes (e.g., anxiety → resistance → adaptation → performance). 19. Case Studies from Different Countries and Institutions This chapter provides comparative analyses of AI applications and faculty experiences across universities in different countries. 20. Strategies for Sustainable and Human-Centered AI Integration This chapter offers an overall evaluation of the book and presents strategies for sustainable and human-centered AI integration in education.

Submission Procedure

Researchers and practitioners are invited to submit on or before June 14, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by June 28, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by August 16, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Addressing Faculty Anxiety Amid AI Transformation in Education. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

June 14, 2026: Proposal Submission Deadline
June 28, 2026: Notification of Acceptance
August 16, 2026: Full Chapter Submission
September 20, 2026: Review Results Returned
October 18, 2026: Final Acceptance Notification
October 25, 2026: Final Chapter Submission

Inquiries

CEMİLE ŞEKER
Bahçeşehir University
sekercemile@gmail.com

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