Before You Deploy AI, Ask This: Is Your Data’s Bank Foundation Ready?
As banks race to deploy AI, they are failing to realize that the data foundation most are building on won’t support it.
Fragmented legacy systems, siloed reporting and inconsistent data don’t just slow transformation. They make AI unreliable in the one industry where unreliable decisions carry real consequences.
This report from Workday, Kainos, and The Financial Brand examines why finance transformation is the prerequisite for AI readiness — and how the “land and expand” methodology lets banks build that foundation in weeks, not years.
This report covers
- Why 63% of organizations don’t know if their data practices are suitable for AI deployment — and what that blind spot costs
- How fragmented finance infrastructure creates compounding risk as AI initiatives proliferate across business lines
- What the “land and expand” methodology looks like in practice, and how banks from $1B to $100B in assets are using it to modernize without disruption
- Why AI agents need the same governance rigor as human employees — and how to build the system of record to manage them
- How banks using unified finance platforms report 60% faster close times and 62% improved accounting capabilities
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