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The article focuses on how fragmented data limits AI reliability in regulated environments, proposing connected data as a necessary foundation for trustworthy agents rather than discussing new models or algorithms. This discussion centers on the infrastructure and data governance required to make enterprise AI defensible against auditors, which is central to the operational viability of current AI systems.
Connected data emerges as the foundation for trusted AI: theCUBE’s keynote analysis from Amplify
Connected data gives artificial intelligence agents the context required to handle critical business work. Enterprises are beginning to assign AI more consequential tasks, but fragmented records and undocumented human knowledge limit what those systems can do reliably. Enterprise software company Workiva Inc. is positioning its platform as a connective layer across business systems while expanding […] The post Connected data emerges as the foundation for trusted AI: theCUBE’s keynote analysis from Amplify appeared first on SiliconANGLE.
Connected data gives artificial intelligence agents the context required to handle critical business work. Enterprises are beginning to assign AI more consequential tasks, but fragmented records and undocumented human knowledge limit what those systems can do reliably. Enterprise software company Workiva Inc. is positioning its platform as a connective layer across business systems while expanding beyond financial reporting into risk, compliance and sustainability. That opportunity depends on giving AI enough context to produce defensible results, according to Krista Case (pictured, left), principle…
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