Exploring AI-Driven Change: Experimental Evidence on Managerial Practices in the Modern Workplace

Artificial intelligence (AI) is a radical innovation that is fundamentally transforming workplace structures, processes, and interactions. This thesis explores AI's organizational and managerial implications, focusing on its ability to redefine concepts such as collaboration, inclusion, and work ethics. Chapter 1 establishes the conceptual framework, highlighting the transformative potential of AI and the need for empirical research to understand its concrete effects in organizations. Chapter 2 presents a systematic literature review investigating experimental studies on AI’s impact in the workplace. Using the Scopus database and AI-powered tools for classification, the review identifies trends in experimental methodologies and managerial practices. It reveals a balanced use of field and laboratory experiments, and highlights human–machine interaction and training as dominant research topics. The analysis also identifies underexplored areas, such as diversity, ethics, and inclusion, signaling opportunities for future research. Chapter 3 examines the role of experimental methods in management studies, with a focus on laboratory and field experiments. Drawing from foundational literature, it discusses the strengths and limitations of these methodologies and introduces the experimental design developed for this thesis. In Chapter 4, this experimental framework is applied to an original study exploring a specific managerial practice impacted by AI. By integrating theoretical insights, systematic reviews, and original research, this thesis bridges the gap between abstract discussions and practical implications. It offers a structured understanding of AI’s transformative role in reshaping managerial practices and organizational behaviors.