Exploring the Role of Artificial Intelligence in Sustainability Initiatives in Public Sector Projects : A Comparative Case Study of Finnish Municipalities
Hossain, Maruf (2025)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025060721380
https://urn.fi/URN:NBN:fi:amk-2025060721380
Tiivistelmä
This thesis investigates the potential contribution of artificial intelligence (AI) to sustainability in the Finnish municipal context, comparing the cities of Vaasa and Seinäjoki. Cities with larger populations have been the focus of academic research, providing less insight into AI adoption and its effects in small and mid-sized cities. Focusing on this gap, this thesis examines how small municipalities perceive the usefulness of AI for sustainability work, as well as the main drivers and barriers to the adoption of AI in the public sector.
The study employs a qualitative case study approach formulated based on the Technology Acceptance Model (TAM). Interview data were supplemented with secondary sources, including municipal documents and project reports from two relatively small-sized municipalities in the western province of Finland.
Results demonstrate that AI is perceived to be particularly impactful in the energy sector, with applications such as digital twins, predictive maintenance, and real-time monitoring enhancing operational eco-sustainability. In transportation and waste, both cities are seeing more use cases emerge, including smart mobility and AI-powered waste sorting. Key enablers include institutional collaboration, the development of internal policies, and access to national or EU funds. Barriers are largely related to concerns about data governance, skill shortages, and regulatory ambiguity.
This work contributes to the discussion on smart cities by showing that even low-resource municipalities can take advantage of AI through strategic integration and ecosystem collaboration. This study presents that the adoption of AI will not only be based on technological readiness but also on organizational readiness, governance models, and cultural acceptance.
The study employs a qualitative case study approach formulated based on the Technology Acceptance Model (TAM). Interview data were supplemented with secondary sources, including municipal documents and project reports from two relatively small-sized municipalities in the western province of Finland.
Results demonstrate that AI is perceived to be particularly impactful in the energy sector, with applications such as digital twins, predictive maintenance, and real-time monitoring enhancing operational eco-sustainability. In transportation and waste, both cities are seeing more use cases emerge, including smart mobility and AI-powered waste sorting. Key enablers include institutional collaboration, the development of internal policies, and access to national or EU funds. Barriers are largely related to concerns about data governance, skill shortages, and regulatory ambiguity.
This work contributes to the discussion on smart cities by showing that even low-resource municipalities can take advantage of AI through strategic integration and ecosystem collaboration. This study presents that the adoption of AI will not only be based on technological readiness but also on organizational readiness, governance models, and cultural acceptance.