Browsing by Author "Tuomela, Anni"

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  • ChatGPT:n turvallisuuden parantaminen: Käytetyt menetelmät ja vastausten kehittyminen
    (2023-05-26) Tuomela, Anni
     Sähkötekniikan korkeakoulu | Bachelor's thesis
  • The Integration of Conversational AI System into Enterprise Architecture
    (2025-04-25) Tuomela, Anni
     School of Science | Master's thesis
    As digital transformation reshapes the business environment, enterprises must adopt emerging technologies to maintain competitiveness. One of the most recent innovations in this transformation is Conversational AI (CAI). It has the potential to revolutionise customer service operations by enhancing enterprises’ efficiency and scalability while also improving customer experience. Adopting CAI systems into Enterprise Architecture (EA) presents a complex challenge, requiring enter-prises to address technical, operational, and strategic aspects. While the potential of CAI technology is widely recognised, its systematic adoption as part of EA remains underexplored. This thesis examines how enterprises can effectively adopt a CAI system into EA to advance customer service operations in the energy sector. The study adopts a qualitative research approach, comprising a literature review to ana-lyse existing theoretical frameworks and a case study conducted within the Finnish energy company Helen Ltd. The empirical investigation explores key factors influ-encing CAI system adoption, drawing on semi-structured interviews with IT archi-tects, product owners, AI specialists, and cybersecurity experts of the case company. The primary outcome of this research is a CAI-EA Adoption Framework for Cus-tomer Service. This framework builds on the known EA layers and their role in the phased AI adoption process. In addition, the thesis focuses more on the technology layer, highlighting its central role in CAI system’s secure and trustworthy operation. Findings indicate that CAI system integrations should be built around business log-ic, ensuring decision-making accuracy and consistency. Additionally, risk manage-ment was identified as a cross-cutting process, extending across all identified EA layers. The study underscores the importance of developing a comprehensive risk management strategy to anticipate and prepare for potential risks.