你的数据很薄弱：为什么没有这个基础设施修复AI智能体就会失败
xebia首席技術官niels zeilemaker强调，代理ai的成功完全取决于数据的可用性。如果没有强大的摄取基础，ai智能体就无法有效地扩展以自动化业务流程。
xebia global cto niels zeilemaker outlined the prerequisite infrastructure required for organizations to successfully deploy and scale ai agents. he argues that while agents offer process acceleration, their success is contingent on making internal data accessible and consumable by ai systems. zeilemaker emphasized that agentic ai scales on data strength, implying that current data architectures are often insufficient for autonomous workflows. this perspective challenges the rush to deploy advanced models, suggesting that data engineering is the primary bottleneck for enterprise ai adoption. companies prioritizing agent capabilities over data readiness may face failed deployments as agents lack the necessary context to operate.