Legacy financial systems often trap organizations in "data swamps" where AI is mistakenly treated as a magic fix for fundamentally broken manual architectures. In this episode, Juan Orlandini, CTO of North America at Insight, outlines why senior executives must distinguish between statistical AI outputs and the mathematical precision required for financial compliance to avoid significant reporting risks. The conversation provides a roadmap for building a scalable operating layer by prioritizing data engineering and leveraging established vendor knowledge to protect long-term investment. This episode is sponsored by K1x. Learn how brands work with Emerj and other Emerj Media options at https://go.emerj.com/partner

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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