Data Infrastructure: Key to AI Agent Success in 2026

The article emphasizes the importance of a robust data infrastructure for the successful implementation and scaling of AI agents. While many companies are experimenting with AI agents, only a small fraction have managed to scale them effectively. A key reason for this is the lack of adequate data architectures that can provide the necessary business context to AI models. Irfan Khan from SAP Data & Analytics stresses that the capabilities of agentic AI are increasingly determined by the soundness of enterprise data architecture and governance, rather than solely by the evolution of the models themselves. The focus should be on delivering business context along with the data, rather than simply accumulating large volumes of data. Overcoming the lack of trust in data requires shared definitions, semantic consistency, and reliable operational context to align data with business meaning. By adopting a modern, business-aware data infrastructure, companies can unlock the full potential of AI agents and achieve better business outcomes.

_Context: This intelligence report was compiled by the DailyAIWire Strategy Engine. Verified for Art. 50 Compliance._