In the evolving landscape of AI, companies must prioritize a robust data architecture, as emphasized by Irfan Khan, SAP Data & Analytics president. The unpredictability of AI’s future necessitates an “AI mindset” anchored in reliable data. With the rise of agentic AI, the quality of enterprise data governance is crucial for effective implementation, surpassing just advancements in models. Businesses should focus on modern data infrastructures that provide context along with data, moving beyond traditional perceptions that equate structured data with high value. The true risk for agentic AI lies not in data scarcity but in lack of context. High-value data is defined by its business relevance rather than its format. Companies must tackle “trust debt” by ensuring semantic consistency and reliable operational context to enhance AI readiness. Furthermore, the separation of compute and storage has led to data sprawl, making it imperative to establish a semantic, business-aware layer for an effective data strategy in AI-driven initiatives.
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