Exploring employee experiences with AI-driven workflow automation

: a qualitative study using inductive thematic analysis

Abstract

This thesis explores how AI-driven workflow automation influences employees' experiences in the workplace, focusing on three core areas: autonomy, communication and both current and future expectations for AI integration. As tools such as generative AI become increasingly integrated into organizational settings, it is essential to understand their broader impact on everyday work dynamics, both individually and collaboratively. The study adopts a qualitative research approach, drawing on 15 structured interviews with employees from various industries who actively use AI tools in their daily tasks. Braun and Clarke's (2006) inductive thematic analysis was used to identify recurring patterns in their experiences. Findings reveal mixed effects of AI on workplace dynamics. AI was seen as improving operational efficiency and enhancing employee autonomy, particularly among junior staff, by reducing repetitive tasks and enabling more independent work. It also reshaped communication patterns, reducing informal exchanges and promoting more asynchronous, AI-mediated interactions. Trust and transparency emerged as critical factors shaping employees' experience with AI tools. The results suggest that AI should be introduced in ways that support teamwork and communication, rather than replace it. Future research should explore AI's long-term impact on relationships and how organizations can better support its use across cultures and industries.

Date of Award	25 Jun 2025
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Cristina Soares Pacheco Mendonça (Supervisor)