For an organization to responsibly advance AI innovations within its business operating models, significant upfront and ongoing investments are required to establish operational security frameworks, tools, and processes that support trustworthy multi-hop AI model hand-offs at scale. The costs pale in comparison to the alternative risks of distorted, vulnerable, or compliance-defying decisions that erode customer and employee trust in AI-generated results.
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