Human-Centered AI Transformation: Exploring Behavioral Dynamics in Software Engineering
Theocharis Tavantzis, Robert Feldt

TL;DR
This study explores the social and behavioral dynamics of AI-driven organizational change in software engineering, emphasizing human factors, challenges, and ethical considerations during early AI transformation stages.
Contribution
It provides a qualitative analysis of behavioral aspects and challenges in AI transformation within software organizations, highlighting the importance of human-centric change management.
Findings
Emphasis on individual-level behavioral factors in early AI transformation stages
Identification of six key challenges related to behavioral and organizational aspects
Highlighting ethical considerations as critical in AI integration
Abstract
As Artificial Intelligence (AI) becomes integral to software development, understanding the social and cooperative dynamics that affect AI-driven organizational change is important. Yet, despite AI's rapid progress and influence, the human and cooperative facets of these shifts in software organizations remain relatively less explored. This study uses Behavioral Software Engineering (BSE) as a lens to examine these often-overlooked dimensions of AI transformation. Through a qualitative approach involving ten semi-structured interviews across four organizations that are undergoing AI transformations, we performed a thematic analysis that revealed numerous sub-themes linked to twelve BSE concepts across individual, group, and organizational levels. Since the organizations are at an early stage of transformation we found more emphasis on the individual level. Our findings further reveal…
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Taxonomy
TopicsBig Data and Business Intelligence
