Designing Delegation in Requirement Gathering: A Socio-technical Study of Product Practitioners and GenAI
(2026) INFM12 20261Department of Informatics
- Abstract
- As Generative AI becomes increasingly embedded in knowledge-intensive product work, product
practitioners are shifting from directly producing requirement artifacts toward configuring,
reviewing, and governing AI-assisted outputs. This thesis examines how product managers,
product owners, business analysts, and related practitioners design delegation and maintain
oversight when using GenAI in requirement-related tasks. While prior research has explored AI
augmentation, human–AI collaboration, and AI applications in requirements engineering, limited
attention has been given to how practitioners preserve contextual judgment, tacit knowledge, and
accountability when AI contributes to requirement documentation.
Adopting an interpretive... (More) - As Generative AI becomes increasingly embedded in knowledge-intensive product work, product
practitioners are shifting from directly producing requirement artifacts toward configuring,
reviewing, and governing AI-assisted outputs. This thesis examines how product managers,
product owners, business analysts, and related practitioners design delegation and maintain
oversight when using GenAI in requirement-related tasks. While prior research has explored AI
augmentation, human–AI collaboration, and AI applications in requirements engineering, limited
attention has been given to how practitioners preserve contextual judgment, tacit knowledge, and
accountability when AI contributes to requirement documentation.
Adopting an interpretive qualitative approach, the study draws on six semi-structured interviews
with product practitioners in Sweden. The findings show that AI-assisted requirement work is not
a process of simple automation, but an iterative socio-technical configuration. Practitioners
selectively delegate bounded and reviewable tasks, translate tacit and domain-specific knowledge
into prompts, examples, documents, and constraints, and maintain oversight through continuous
evaluation, correction, and accountability practices. The thesis contributes to Information Systems
research by conceptualizing GenAI-assisted requirement gathering as boundary design, where
requirement quality depends on the interaction between delegation, knowledge translation,
oversight, and calibrated trust. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/student-papers/record/9240119
- author
- Simarmata, Cindy Fransiska LU and Pham, Tuan Anh
- supervisor
- organization
- course
- INFM12 20261
- year
- 2026
- type
- H1 - Master's Degree (One Year)
- subject
- language
- English
- id
- 9240119
- date added to LUP
- 2026-06-17 07:07:45
- date last changed
- 2026-06-17 07:07:45
@misc{9240119,
abstract = {{As Generative AI becomes increasingly embedded in knowledge-intensive product work, product
practitioners are shifting from directly producing requirement artifacts toward configuring,
reviewing, and governing AI-assisted outputs. This thesis examines how product managers,
product owners, business analysts, and related practitioners design delegation and maintain
oversight when using GenAI in requirement-related tasks. While prior research has explored AI
augmentation, human–AI collaboration, and AI applications in requirements engineering, limited
attention has been given to how practitioners preserve contextual judgment, tacit knowledge, and
accountability when AI contributes to requirement documentation.
Adopting an interpretive qualitative approach, the study draws on six semi-structured interviews
with product practitioners in Sweden. The findings show that AI-assisted requirement work is not
a process of simple automation, but an iterative socio-technical configuration. Practitioners
selectively delegate bounded and reviewable tasks, translate tacit and domain-specific knowledge
into prompts, examples, documents, and constraints, and maintain oversight through continuous
evaluation, correction, and accountability practices. The thesis contributes to Information Systems
research by conceptualizing GenAI-assisted requirement gathering as boundary design, where
requirement quality depends on the interaction between delegation, knowledge translation,
oversight, and calibrated trust.}},
author = {{Simarmata, Cindy Fransiska and Pham, Tuan Anh}},
language = {{eng}},
note = {{Student Paper}},
title = {{Designing Delegation in Requirement Gathering: A Socio-technical Study of Product Practitioners and GenAI}},
year = {{2026}},
}