Guest talk by Elaine Mosconi and Elisa Gagnon on "Managing the MLOps Chain for AI-enabled products"

Guest talk by Elaine Mosconi and Elisa Gagnon on "Managing the MLOps Chain for AI-enabled products"

Time and place:

• Date/Time: Thursday, 27.08.2026, 10:30-11:45

• Location: Meeting room D2.2.094 (D2 Entrance C, 2nd floor) or online via Teams (https://teams.microsoft.com/meet/367120062553350?p=vYjoQq32yYHF52cgbU)
   

Title:
Managing the MLOps Chain for AI-enabled products
 

Abstract:
Machine-learning operations (MLOps) encompass practices and tools that operationalize the development and subsequent deployment of machine-learning (ML) solutions in production environments. As organizations transition from isolated ML experiments to the continuous deployment and management of AI-enabled products, MLOps chains emerge. These chains require coordination across multiple pipelines, stakeholders, and sustained deployments, making their governance inherently complex. However, existing literature offers limited guidance on chain-level governance as AI-enabled products are scaled across an organization. Addressing this gap, this study adopts an in-depth case study of a large defense and aerospace organization scaling its MLOps chain. Our preliminary findings reveal four governance tensions: experimentation versus operational integration, standardization versus context-specific deployment, delivery versus sustained operations, and operational value versus external value articulation. The preliminary findings position MLOps governance as an evolving arrangement driven by the continuous balancing of competing tensions.

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LinkedIn:
Dr. Elaine Mosconi (LinkedIn)

Full Professor, University of Sherbrooke, Canada

Dr. Elisa Gagnon (LinkedIn)

Associate Professor, Bishop’s University, Canada