Special Issue: Generative AI (GenAI) and Agentic AI at the Marketing–Operations Interface
in the
Production and Operations Management (POM)
Guest Editors
- Roland T. Rust, Distinguished University Professor and David Bruce Smith Chair in Marketing, Robert H. Smith School of Business, University of Maryland
- Ming-Hui Huang, Distinguished Professor and National Taiwan University Chair Professor, Department of Information Management, National Taiwan University
- Xin (Shane) Wang, Professor of Marketing, Pamplin College of Business, Virginia Tech
- Praveen K. Kopalle, Signal Companies’ Professor of Management & Professor of Marketing, Tuck School of Business, Dartmouth College
Recent breakthroughs in artificial intelligence are reshaping how firms integrate marketing and operations. Advances in generative AI (GenAI) (e.g., large language models, diffusion systems) and agentic AI (autonomous, goal-directed systems) are transforming both customer engagement and operational execution. GenAI enables large-scale personalization, demand simulation, and content creation, while agentic AI moves beyond passive recommendation tools to autonomously interact with customers, manage workflows, and coordinate resources in real time.
As these technologies converge, the traditional boundaries between marketing and operations are dissolving. Firms increasingly rely on intelligent systems to co-create value with customers, optimize resource allocation, and make cross-functional decisions. This shift raises urgent questions about theory, governance, and practice at the marketing-operations interface.
This special issue seeks to advance knowledge on how GenAI and agentic AI jointly influence demand generation, operational responsiveness, and firm performance. We welcome contributions from marketing, operations, information systems, and related fields, employing a wide range of methodologies, including analytical modeling, empirical studies, behavioral experiments, simulation, and system design.
Possible Topics
· Customer co-creation and adaptive operations: How GenAI enables real-time product customization and how agentic AI orchestrates fulfillment strategies.
· AI-driven service agents: The role of autonomous conversational agents in engagement, staffing, workflow design, and service recovery.
· Cross-functional decision automation: How Agentic AI leverages generative models to autonomously plan promotions, set prices, or manage inventory.
· Demand sensing and operational responsiveness: Synthesizing unstructured data (e.g., reviews, chat logs) with GenAI to improve operational decision-making.
· Trust, control, and governance: Managing risks of delegating decision rights to AI, including error, bias, or misalignment of marketing and operational objectives.
· AI-enabled coordination mechanisms: Designing new forms of human–AI collaboration that integrate marketing analytics with operations management.
Commitment to Timeliness
Given the rapid pace of research and practice in this domain, the editorial team is committed to quick turnaround and timely decisions. A paper submitted to the special issue will be processed right away. Authors are encouraged to submit as soon as they are ready. Our goal is to ensure that accepted papers are published swiftly, with the special issue scheduled for print publication in early 2027 to maximize its relevance and impact.
First-round submission deadline: June 30, 2026
First-round decisions: August 31, 2026
Revised submission deadline: November 15, 2026
Final decisions: December 31, 2026
Guidance for Authors
We encourage prospective authors to contact the Guest Editors to discuss fitness and receive guidance for this special issue. In addition to new submissions, we also welcome manuscripts that have been reviewed or under preparation at other leading journals such as Marketing Science, Management Science, Information Systems Research, etc. Authors may attach prior review reports when submitting; the Guest Editors will carefully assess the manuscript’s fitness for the special issue. Submissions should be prepared in accordance with the Production and Operations Management author guidelines and will undergo the journal’s standard peer-review process. We especially encourage interdisciplinary work that bridges Marketing, Operations, and Information Systems. By focusing on the marketing–operations interface in the era of intelligent systems, this special issue aims to generate timely insights for both scholars and practitioners navigating AI-driven value creation.
