The Impact of Artificial Intelligence on Enterprise Software User Roles: An Empirical Case Study of Role Transformation on the SAP Business Technology Platform

This study investigates how the rapid adoption of Artificial Intelligence (AI) and agentic systems is transforming professional roles within the software development lifecycle. Focusing on the SAP Business Technology Platform (BTP), the researchers conducted a qualitative study involving 20 expert interviews and a participatory workshop with 24 participants. The goal was to understand how AI tools—ranging from coding assistants to autonomous agents—are altering daily tasks, collaboration patterns, and the overall structure of development teams.

The research identifies a clear transition in how software professionals interact with their tools. Developers are increasingly moving away from being mere "writers of code" toward becoming "controllers and reviewers" of AI-generated output. This shift is characterized by two primary modes of interaction: an acceleration mode, where AI acts as a high-speed autocomplete for routine microtasks, and an exploration mode, where AI serves as a sparring partner for complex problem-solving.

Furthermore, the study highlights that the existing "BTP User Type Matrix"—a framework used to categorize roles by task and interaction paradigm—is becoming outdated. As AI democratizes development through low-code and no-code interfaces, the boundaries between traditional roles (such as backend developers and UI designers) are blurring. The findings suggest that future enterprise software must prioritize new governance, oversight functions, and AI-native design approaches to accommodate these evolving professional responsibilities.

As organizations shift toward an agent-centric paradigm, the nature of software engineering is fundamentally changing. This research underscores that productivity gains from AI are not merely about speed; they represent a structural change in the workforce. By identifying the need for updated role taxonomies and governance, the study provides a roadmap for organizations to manage the transition to AI-augmented development without sacrificing software quality, security, or team cohesion.