Intelligent automation solutions for social security
Liukkonen, Elisa (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202505079606
https://urn.fi/URN:NBN:fi:amk-202505079606
Tiivistelmä
This thesis investigates how intelligent automation could enhance the operational capabilities of Kela (The Social Insurance Institution of Finland) through a qualitative analysis of employee perspectives and an examination of relevant market solutions. Against the backdrop of Kela's ongoing digital transformation the research examines how intelligent automation technologies combining artificial intelligence, machine learning, and robotic process automation could enhance service delivery and operational efficiency, with a primary focus on the views and experiences of Kela employees.
The research employed a qualitative methodology, conducting semi-structured interviews with 14 Kela employees from various departments and hierarchical levels. These interviews provided insights into current automation practices, challenges, and opportunities within Kela's operational environment. The data was analyzed thematically to identify patterns and key areas where intelligent automation could create value.
The results revealed that Kela could benefit from several intelligent automation solutions available in the market, particularly in document processing, customer service, and benefits application processing. The study identified specific market offerings in robotic process automation (RPA) and AI-enhanced systems that align with Kela's operational requirements and could streamline workflow processes. The findings suggest that intelligent automation could significantly reduce manual workloads, minimize errors, and allow staff to focus on more complex, customer-centric tasks.
The research concludes that Kela would benefit from establishing strategic partnerships with technology providers and developing a comprehensive automation roadmap. As development recommendations, the thesis emphasizes the importance of process optimization before automation implementation, continuous skills development for staff, and regular evaluation of technological innovations to ensure alignment with Kela's strategic objectives.
The research employed a qualitative methodology, conducting semi-structured interviews with 14 Kela employees from various departments and hierarchical levels. These interviews provided insights into current automation practices, challenges, and opportunities within Kela's operational environment. The data was analyzed thematically to identify patterns and key areas where intelligent automation could create value.
The results revealed that Kela could benefit from several intelligent automation solutions available in the market, particularly in document processing, customer service, and benefits application processing. The study identified specific market offerings in robotic process automation (RPA) and AI-enhanced systems that align with Kela's operational requirements and could streamline workflow processes. The findings suggest that intelligent automation could significantly reduce manual workloads, minimize errors, and allow staff to focus on more complex, customer-centric tasks.
The research concludes that Kela would benefit from establishing strategic partnerships with technology providers and developing a comprehensive automation roadmap. As development recommendations, the thesis emphasizes the importance of process optimization before automation implementation, continuous skills development for staff, and regular evaluation of technological innovations to ensure alignment with Kela's strategic objectives.