This study examines how Artificial Intelligence (AI) is used in project management in small and medium-sized IT organizations. It focuses on the experiences of project managers. It aims to understand how AI tools are used, what factors affect these experiences, and how AI impacts project management practices using Second-Generation Activity Theory.

The research uses qualitative methods, including semi-structured interviews with nine project managers from various SMEs IT sectors. Thematic analysis groups AI applications into generative, predictive, and automation themes.

Activity Theory helps identify alignments and conflicts within project management systems. The findings show that project managers mainly use generative AI tools like ChatGPT and Microsoft Copilot to automate tasks, generate reports, and support decision-making. Predictive AI and automation tools are used less frequently. Factors influencing AI adoption include organizational support, personal initiatives, and engagement with professional communities.

Significant congruents and contradictions within the activity systems show AI's impact on traditional project management practices.

The study helps understand AI adoption in project management by applying Activity Theory to modern technological contexts. It provides practical analysis for project managers, organizations, and professional communities, stressing the need for AI knowledge and adaptation to new tools.

The research highlights the importance of integrating AI tools with existing processes to improve efficiency and decision-making.