Why AI pilots in banking are struggling to move beyond the surface
By Devipad Tripathy, SVP & Global Head, Digital Engineering & Enterprise Transformations, Xebia
A Chief Technology Officer at a leading private bank once admitted his most polished AI dashboard was an illusion: an elegant front-end underwritten by a team of junior analysts manually reconciling mainframe databases behind the scenes.
That disconnect illustrates the current state of financial services.
Almost every bank has embraced generative AI prototypes, deploying conversational copilots and auto-summarizing loan dossiers. Yet across the global banking, financial services, and insurance (BFSI) sector, these high-profile deployments are hitting fundamental architectural limits. The issue is not model intelligence; it is core readiness.
BCG research reveals that while many organizations claim to capture value from AI, only a fraction qualify as genuinely mature. The vast majority remain stuck in an ‘emergence’ phase, piloting isolated point solutions while grappling with fragile data infrastructure and governance bottlenecks.
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