Artificial intelligence is one of the digitalization technologies which will bring so massive changes to society that they are comparable to agricultural industrialization. These changes will also affect to firm businesses and firm services. Usually firm perform changes to their services only based on tangible benefits, so the technology fit to the service must have clear argumentation, for example, based on the productivity benefits. Finance sector and especially banking is a significant business to the society and it enables firms and consumers to use money. For consumers, banks offer basic services which are loans, savings, in-vestments and payments. In this information systems science thesis was studied how technology fits to target domain, in more detail, how artificial intelligence fits into retail banking services. Thesis was a case study based on an assignment from finance sector IT service firm. Target of the case was a customer of the IT service provider, a typical Finnish small bank. Aim of the thesis was to clarify artificial intelligence as a concept, clarify how artificial intelligence has been used before in the financial sector and to study artificial intelligence fit into the services of the case bank. Theoretical part of the thesis was implement-ed as a literature review from artificial intelligence, finance sector and as a systematic literature review from the use of artificial intelligence in finance sector. Theoretical part produced a synthesis of artificial intelligence, description of the finance sector as a target a domain and a systematic overview of the artificial intelligence applications and the conclusions in the finance sector and also a discussion of using the artificial intelligence in a credit rating task. The re-search gap was identified based on a short research survey and a theoretical framework was created based on theories or models of fit, finance sector technology development, service logic and strategic fit. Empirical part was implemented as a qualitative research where data was collected from bank product managers and IT service firm managers by using semi-structured interviews. As a result, there were found possible artificial intelligence applications in credit rating, customer insight, investment recommendations and payment type recommendations. As a conclusion, using artificial intelligence in customer in-sight and credit rating might fit in to the services of case bank, but investment recommendation fit needs more research and payment type recommendation fit cannot be argued to be relevant to case bank yet. Analysing the tangible and measurable business benefits of the fit was considered to be challenge so that raised an interesting topic for further research.