Artificial Intelligence and Change Management

Organizational Transformation, AI Challenges, and Management Consulting

Edited by:
Emmanuel Monod, EMSS and CPMC, Shanghai
Ingrid Qi, Shanghai SUIBE University, China
Anthony F. Buono, Bentley University

A volume in the series: Research in Management Consulting. Editor(s): David Brian Szabla, Western Michigan University.

Call for Chapters

Submission Deadline March 15, 2021
As artificial intelligence (AI) continues to grow on an exponential basis, questions linger about the benefits and risks that organizations may expect from AI applications. Many trends associated with AI adopt a technology-centered approach, assuming that selection of the “right” technology, such as voice recognition, machine learning or robotics, would lead to enhanced business performance. Yet, most of the time, organizational factors (e.g., the changing nature of work, hidden costs and hidden work) are neglected. Moreover, the unexpected consequences that may occur during the AI projects such as resistance to change, institutional logics and cultural context are also overlooked.

Although IS implementation approaches are often suggested to tackle these issues—from agile methods and distributed development, to Socio-Technical Systems (STS) and Business Process Innovation (BPI)—another perspective is to start from organizational transformation, in essence, independently from technology. These methods include, for instance, Organizational Development (OD), Socio-Economic Approaches to Management (SEAM), storytelling, appreciative inquiry and many others. Overall, whereas technology-centered approaches have been associated with numerous unintended consequences and failures with previous generations of technologies (e.g., ERP, KM and groupware), process-centered and human-centered approaches may represent a less risky approach to AI implementation. This call invites papers that focus on the management consulting possibilities and challenges from the perspective of companies and institutions, including workers and business processes. Emphasis is placed on evaluation of the potential performance improvements and risks of AI, and ways to examine how technology may support work and organizational goals

We seek for chapters that will help to advance theory, research and practice of the management of AI in organizations. The topics of chapters include, but are not limited to:

• Organizational dimensions associated with AI performance;
• Organizational dimensions associated with AI cost;
• Methods to evaluate AI implementation returns;
• Theories of change management related to solving the AI productivity paradox;
• Consulting methodology for AI implementation in organizations;
• Consulting practices that add value in facilitating AI implementation.

Among the wide range of possible chapters, which could focus on concepts, methods, processes, theory, research, or practices, we welcome:

• Theoretical or empirical chapters that provide insight into the theory and/or practice of AI in management;
• Critical analysis of AI in management consulting;
• Case studies or other field research, using quantitative or qualitative methods, which offer descriptive and reflective insights on successful or failed AI projects in organizations;
• Review papers that integrate what is known about AI in management or identify key unanswered questions;
• Thoughtful reflections on experiences that extract new insights into AI in management, especially by relating these topics to methods in organization transformation and change management.

Several of these topics were discussed during the Academy of Management annual meeting 2019 in Boston. A professional development workshop (PDW) was organized by the Management Consulting division and sponsored by five other divisions during the conferences organized at Harvard University by Management Institute and the Research Network "AI-IM" in partnership with MCD and OCIS (two divisions of the Academy of Management). Two other PDWs related to AI in management were accepted for AOM 2020 in Vancouver. As these initiatives underscore, there is much more to understand –in both theory and practice. What works and why? How can we improve AI in management? And beyond technology, how should AI in management be considered from a a stakeholder perspective? What is the role of management consulting related to these topics? Are the implications of AI on organizations of a different nature compared to those of other technologies?

In addition to this Call, the volume will contain invitational chapters. We welcome thoughtful, clarifying, provocative or creative proposals for chapters. If you’re interested, please start with a brief proposal including what you have in mind, any key questions you’re addressing and the ideas, concepts, case, data- or experience-base you will use.

Please Send you proposals to Emmanuel Monod (monod@suibe.edu.cn). If you want to explore further or have any questions, feel free to contact any of the editors (Ingrid Qi, qi@suibe.edu.cn; Anthony Buono (abuono@bentley.edu).