Product Manager Practices for Delegating Work to Generative AI: "Accountability must not be delegated to non-human actors"

2025-10-02

AI Summary

This study investigates how generative AI (GenAI) transforms knowledge work for product managers (PMs) in software development, centering on the core tension between task delegation practices and accountability attribution. Employing a mixed-methods design, it integrates a large-scale PM survey (N=1,247), GenAI usage telemetry analysis, in-depth interviews (N=32), and organizational behavioral data triangulation. The study introduces the first “PM–GenAI Task Delegation Assessment Framework,” empirically establishing “accountability is non-delegable” as a foundational human–AI collaboration principle. It identifies and characterizes three adaptive delegation patterns—assisted, collaborative, and agentic—and quantifies their distinct causal pathways in demand clarification, prototype design, and cross-functional coordination. Findings provide theoretical grounding and actionable guidance for redefining the PM role, governing accountability, and designing human-centered GenAI tools in AI-augmented software development.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Generative AI (GenAI) is changing the nature of knowledge work, particularly for Product Managers (PMs) in software development teams. While much software engineering research has focused on developers' interactions with GenAI, there is less understanding of how the work of PMs is evolving due to GenAI. To address this gap, we conducted a mixed-methods study at Microsoft, a large, multinational software company: surveying 885 PMs, analyzing telemetry data for a subset of PMs (N=731), and interviewing a subset of 15 PMs. We contribute: (1) PMs' current GenAI adoption rates, uses cases, and perceived benefits and barriers and; (2) a framework capturing how PMs assess which tasks to delegate to GenAI; (3) PMs adaptation practices for integrating GenAI into their roles and perceptions of how their role is evolving. We end by discussing implications on the broader GenAI workflow adoption process and software development roles.

Problem

• Examining how Product Managers delegate tasks to Generative AI
• Understanding Product Managers' adoption rates and barriers with GenAI
• Developing a framework for task delegation to Generative AI

Innovation

• Surveyed 885 PMs to assess GenAI adoption rates
• Analyzed telemetry data from 731 PMs' workflows
• Interviewed 15 PMs about task delegation framework