Besides this emerging topic, artificial intelligence (AI), large language models (LLMs), and knowledge management (KM) are understood by organizations in different ways. Consulting firms offer banks scalable solutions by going through checklists or question-and-answer sessions, which is not a sustainable solution. This research’s novel artifact aims to incorporate KM within AI readiness maturity assessment models and extend it with LLM best practices. The artifact consists of a novel dedicated maturity assessment model for adopting LLM-based KM within banks to allow banks to assess their readiness to start developing and using employee-augmenting LLMs.

The maturity assessment model proposed in this paper was developed during the design cycle using a procedure model for developing maturity models, as suggested by Becker et al. (2009). The novel artifact has been rigorously validated using Design Science Research. This approach involved validating and testing the model with AI experts and experts working in banks to ensure its practical applicability and effectiveness. Seven experts originating from banking institutions or consulting firms were interviewed, and their perspectives played a pivotal role in shaping this research.

In the awareness phase, the researcher discovered the need for such a maturity assessment model, which is significant based on seven experts’ knowledge and the literature. The experts underlined the different use cases in a bank, and the author chose employee-augmenting private LLM solutions, as this use case includes employee KM. The literature review emphasized improving banks' KM systems and practices, and over 200 best practices/indicators have been collected to create the novel artifact on Excel spreadsheets and transfer it to a user-friendly media called the ABILI Platform. Five evaluation concepts were conducted, and the profound results were documented. All the testers have confirmed the assessment’s content and the ABILI Platform’s usability. This thesis developed and evaluated a novel maturity assessment model tailored to assess the readiness of Swiss banks to adopt LLM-based KM engines. The model fills a significant research gap by addressing organizational readiness and employee mindset by integrating insights from systematic literature reviews, expert interviews, and iterative development strategies. It uniquely combines KM and LLM adoption elements previously unaddressed in existing models. The validation process, involving bank employees and consultants, demonstrated the model’s relevance, acceptance, and practical value.