Bridging the AI PoC – Production Gap – Keys to Deployment Success in Swiss Financial Industry
Background
Many Swiss financial institutions have experimented extensively with Artificial Intelligence (AI), primarily through proof-of-concept (PoC) projects and pilot implementations. Yet relatively few institutions have successfully transformed these initial explorations into fully operational and value-generating solutions. The previous SFTI-OST whitepaper, “A Scalable Framework for Implementing Artificial Intelligence in Swiss Financial Institutions,” highlighted a significant challenge: nearly half (43%) of surveyed AI initiatives remain stuck at the pilot stage, with only 29% having achieved full deployment and merely 19% advancing to a scaling phase.
This phenomenon of “pilot purgatory” is not unique to Switzerland. Global industry research consistently indicates that between 70% and 90% of AI pilots never successfully transition into production environments.
Objectives of the Project
This follow-up study aims specifically at identifying concrete, actionable pathways for Swiss banks and insurers to overcome the above barriers and challenges, enabling the effective transition of AI initiatives from pilot projects and PoCs into fully productive implementations.
By carefully investigating practical success factors, model management strategies, infrastructure and data governance considerations, and realistic approaches to expectation setting and business case validation, this research will equip SFTI member institutions with a clear and pragmatic roadmap for scaling AI beyond pilots. Ultimately, the study seeks to enable Swiss financial institutions to unlock the substantial business value promised by AI, while concurrently reinforcing SFTI’s strategic position and reputation as a leading authority and innovator in AI deployment within Switzerland’s financial industry.
The study will adopt a mixed-method research design that combines quantitative insights from a broad survey with qualitative depth from expert interviews. This structured approach is designed to produce both statistically grounded results and nuanced insights. It balances breadth and depth, yielding findings that are trustworthy and highly relevant to SFTI members’ strategic and operational needs.
Contact for Additional Details
The project co-leads are happy to provide additional details.
Eastern Switzerland University of Applied Sciences (OST), Institute for Finance & Law