Artificial Intelligence in Data Analytics

Sammanfattning

The bachelor’s thesis explores the utilization of Artificial Intelligence (AI) in data analytics, aiming to understand data analysts' perceptions and experiences with AI-based tools and technologies. Through qualitative research involving semi-structured interviews with six data analysts from Sweden and the United States, thematic analysis identified five key themes.These findings were discussed in light of a theoretical framework encompassing data analytics concepts, AI in data analytics, accountability in decision-making AI tools, and the sensemaking theory. The findings show that data analysts recognize AI's benefits, particularly in error reduction, time efficiency and bias mitigation, yet acknowledge its inability to fully replace human analysts. They predominantly rely on specialized software to mitigate risks associated with multi-purpose AI tools and utilize self-developed AI solutions to enhance machine learning benefits. Concerns persist regarding limitations, data integrity, and the need for ongoing education, emphasizing the importance of accountability and effective communication among stakeholders. While AI adoption in data analytics is growing, manual workflows remain prevalent, reflecting cautious optimism and ongoing evaluation of AI's capabilities and challenges. Theoretical contributions include insights into the dynamics surrounding AI integration, while practical implications underscore the effective utilization and integration of AI-based technologies in data analytics workflows.