INSEAD

AI-Driven Human Task Substitution: Evidence from Google Translate and ChatGPT

We examine how different generations of artificial intelligence (AI) substitute for human knowledge worker tasks, leveraging two sequential natural experiments in the translation industry. We study the introduction of Google Neural Machine Translation (GNMT), a predictive, task-s...

Modeling collective action in POM: The Strategy–Operations–People framework

While many business situations relevant to production and operations management (POM), such as supply chain coordination or sustainable operations, involve some form of collective action; managerial frameworks for collective action rarely appear in POM contexts. Valuable insights...

From Trees to Treewidth: Inventory Management in Complex Supply Chain Networks

We propose an exact linear programming (LP)-based solution approach to the Guaranteed Service Model (GSM), one of the most widely applied models for optimizing safety stock placement in supply chain networks. Our approach handles any directed acyclic network and any cost function...

Myopic Expansions on Digital Platforms

Digitization has enabled modern firms to expand at unprecedented rates, but there are downsides to rapid expansion. Prior research has highlighted how digital platforms facilitate mass-market expansions by resolving frictions associated with market entry. Accordingly, various stu...

Conversational AI should fill the white space in mental health care, not replace humans

Abstract Conversational AI (CAI) is being rapidly deployed in mental healthcare, with much of the focus on chatbots delivering therapy directly to patients. However, this focus overlooks broader opportunities to improve mental healthcare as a system. Rather than replacing clinici...

Real-world use of large language models for mental health in 2024

The extent to which people use general-purpose large language models (LLMs) for their mental health is unknown. Information about use patterns is important for clinicians, developers, and regulators. We surveyed U.S. adults ( n = 1871) between August and October 2024 using strati...