Artificial intelligence and automation driving sustainability in banking
Perera, Vindya (2025)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025101526040
https://urn.fi/URN:NBN:fi:amk-2025101526040
Tiivistelmä
In the modern banking era, AI and automation are considered sustainability enablers. This thesis examines AI and automation’s contribution to sustainability in the banking sector. The primary objective of this thesis is to investigate the integration of AI and automation in banking and their impact on sustainability.
A mixed methods approach was employed to gather primary and secondary information on stakeholder perceptions on the sustainability impact of AI and automation. Descriptive and thematic analysis were used to analyse the data collected in quantitative and qualitative methods.
The study findings indicate that AI and automation result in significant improvement of cost efficiency, process optimization, and convenience. The research outcome highlighted that AI and automation have high potential to ensure economic, social, and environmental sustainability. Paper saving, reducing carbon emissions, and reducing fuel consumption are recognized as top contributors to sustainability, whereas perceptions on job displacement, new job opportunities, trust, and transparency are uncertain.
The study concludes with the identification of AI and automation’s potential for sustainability, and their success depends on customer-centric strategies of banks to ensure trust, ethical governance, and transparency. These insights provide valuable guidance for banks in digital transformation with AI and automation. Further studies are needed to study the longitudinal methods with larger samples to analyse the long-term sustainability of the banking industry through AI and automation.
A mixed methods approach was employed to gather primary and secondary information on stakeholder perceptions on the sustainability impact of AI and automation. Descriptive and thematic analysis were used to analyse the data collected in quantitative and qualitative methods.
The study findings indicate that AI and automation result in significant improvement of cost efficiency, process optimization, and convenience. The research outcome highlighted that AI and automation have high potential to ensure economic, social, and environmental sustainability. Paper saving, reducing carbon emissions, and reducing fuel consumption are recognized as top contributors to sustainability, whereas perceptions on job displacement, new job opportunities, trust, and transparency are uncertain.
The study concludes with the identification of AI and automation’s potential for sustainability, and their success depends on customer-centric strategies of banks to ensure trust, ethical governance, and transparency. These insights provide valuable guidance for banks in digital transformation with AI and automation. Further studies are needed to study the longitudinal methods with larger samples to analyse the long-term sustainability of the banking industry through AI and automation.