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AI-ready data architecture
This paper explores architecture and leading practices to build resilient, intelligent and future‑ready data foundations for enterprise AI.
Organizations face persistent challenges in scaling AI due to fragmented data estates, inconsistent governance, and limited ability to manage real-time, high-volume structured and unstructured data. Traditional architecture often fails to support the performance, trust and interoperability required for AI and GenAI workloads.
This whitepaper explores how organizations can overcome data and governance challenges to support enterprise AI. It outlines key capabilities, governance models and data supply chain patterns needed to enable trusted, scalable AI adoption, while supporting advanced analytics, machine learning and emerging AI agent workloads.