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Editor’s note: This post was co-authored by Diana Rothfuss. For the past few years, banks have focused on proving that AI can deliver business value. Across financial services, organizations have launched pilots, explored generative AI use cases and tested how AI can improve everything from customer engagement and fraud detection
Organizations have spent years investing in data, analytics and AI. Many now have dashboards, predictive models and generative AI tools. Yet one challenge continues to surface: turning those insights into timely, consistent decisions. That’s one reason decision intelligence is getting more attention. As AI becomes part of everyday business, organizations
Many AI initiatives don’t stall because of the models – they stall because of the data behind them. Teams can build promising prototypes, but moving those models into production is where progress slows down. Data is spread across systems, pipelines are difficult to maintain and governance often lags behind how