IBM: How Banks can Accelerate Enterprise-Wide AI Adoption
Jessica Ridella, Global Technology Managing Director at IBM, delves into the strategies enabling banks to move AI into enterprise-wide production
TL;DR
- The primary barrier to scaling AI in banking is not technology, but people and processes, often due to cultural resistance and the 'pilot trap'.
- Trust and governance are critical for AI adoption, ensuring AI operates safely, fairly, and transparently, allowing for innovation within regulatory frameworks.
- Successful banks are moving AI from pilots to production by building standardized 'AI factories' with common tools and processes, enabling faster, cheaper, and safer deployment.
- Overcoming data silos with a 'data fabric' allows banks to achieve hyper-personalization, creating a single customer view and transforming the customer relationship.
- A hybrid 'build and buy' model is the optimal strategy, leveraging foundational platforms from global partners while building proprietary solutions with unique data and industry knowledge.