Integrating artificial intelligence (AI) tools, including Robotic Process Automation (RPA) and advanced analytics, reshapes the financial industry by streamlining operations and improving fraud detection capabilities. Nevertheless, financial institutions encounter notable obstacles in adopting and implementing these technologies. Key challenges include employee resistance, the need to integrate with legacy systems, issues with data quality, and a shortage of skilled workers. This study investigates these obstacles through the lens of actor-network theory (ANT), analyzing the dynamics between human and non-human entities in two financial institutions in South Africa. By applying ANT concepts like translation, inscription, and obligatory passage points (OPP), the research uncovers strategies to mitigate resistance, align stakeholders' interests, and promote the successful integration of AI tools. The findings highlight the critical roles of cultural practices, policy implementation, and focused training in tackling these challenges. The study concludes by suggesting practical strategies for financial organizations to effectively utilize AI tools, boosting operational efficiency and enhancing decision-making capabilities.