While 94% of financial services firms pilot generative AI, most fail to transition from prototype to production due to execution bottlenecks—fragmented legacy infrastructure, poor data governance, and siloed systems rather than model limitations. Databricks identifies that successful firms treat data as a managed asset and adopt unified data-AI platforms with centralized governance. By end-2026, competitive differentiation will hinge on execution, separating firms with production-scale AI embedded in core operations from those still at pilot stage.
Infrastructure
8 AI and data trends shaping financial services in 2026
94% of financial services firms pilot generative AI but fail at production due to execution bottlenecks—legacy infrastructure and poor data governance, not model limitations, will separate competitive winners from laggards by end-2026.
Tuesday, April 14, 2026 12:00 PM UTC2 MIN READSOURCE: Databricks BlogBY sys://pipeline
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