Human-Centered AI Transformation: Exploring Behavioral Dynamics in Software Engineering

• URL: http://arxiv.org/abs/2411.08693v1
• Date: Wed, 13 Nov 2024 15:29:24 GMT
• Title: Human-Centered AI Transformation: Exploring Behavioral Dynamics in Software Engineering
• Authors: Theocharis Tavantzis, Robert Feldt,
• Abstract summary: This study uses Behavioral Software Engineering as a lens to examine these often-overlooked dimensions of AI transformation. Our findings reveal six key challenges tied to these BSE aspects that the organizations face during their AI transformation.
• Score: 6.126394204968227
• License:
• 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 six key challenges tied to these BSE aspects that the organizations face during their AI transformation. Aligned with change management literature, we emphasize that effective communication, proactive leadership, and resistance management are essential for successful AI integration. However, we also identify ethical considerations as critical in the AI context-an area largely overlooked in previous research. Furthermore, a narrative analysis illustrates how different roles within an organization experience the AI transition in unique ways. These insights underscore that AI transformation extends beyond technical solutions; it requires a thoughtful approach that balances technological and human factors.

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