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Snowflake:2026年制造业数据趋势报告(中译版)(14页).pdf

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1、DATA TRENDS 2026 MANUFACTURINGHow agentic AI and unified data are transforming the industryTable of ContentsTransformative Change:Moving from Insight to Execution.3Trends That Matter in Manufacturing.5Trend 1:AI inside everything.6Trend 2:The unified manufacturing namespace.8Trend 3:Connected produc

2、ts become connected businesses.10The State of the AI Data Cloud for Manufacturing.11Building the Future of AI-Driven,Connected Manufacturing.13Table of Contents|2 DATA TRENDS 2026:MANUFACTURINGTransformative Change:Moving from Insight to ExecutionThis year,manufacturing is operating in a fundamental

3、ly different environment,marked by such stark changes that volatility is no longer an exception but the baseline condition.Outside factors now shape daily manufacturing decisions,from geopolitics to energy uncertainty and regulation.Simultaneously,manufacturers are facing cost pressures and margin c

4、ompression while trying to meet growing expectations for resilience,sustainability and responsiveness.This multifaceted set of challenges has exposed the limits of traditional planning cycles,siloed operations and retrospective analytics and the need to leave them in the past.Even modern processes a

5、re becoming more refined as manufacturers whove invested heavily in data,dashboards and analytics realize that while their insight improved,their execution did not.And in an era of constant industry disruption,insight alone is no longer enough.In 2026,leading manufacturers are moving beyond using da

6、ta to merely explain what happened to also understand why it happened.Theres a major shift toward AI-enabled execution as it becomes central to operations and optimization.And that optimization is no longer occurring in isolation,but throughout the organization with the aid of agentic AI.“Traditiona

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1. **AI驱动执行**:74%制造商预计3年内AI代理将独立管理11-15%的常规生产决策,75%认为AI将成为2026年运营利润前三贡献者。 2. **三大核心趋势**: - **AI嵌入全流程**:从分析转向执行,AI代理和Copilot融入供应链、车间决策,支持预测性维护。 - **统一制造命名空间**:整合ERP、MES等系统数据,实现跨域实时协同,提升供应链韧性。 - **连接产品变现**:产品数据反哺制造与供应链,通过AI挖掘使用模式,优化质量并创造新收入。 3. **数据基础关键**:现代数据平台需支持AI就绪数据(高质量、治理、跨结构化数据),避免40%的AI项目因成本或风险失控失败。
AI如何改变制造业? 统一数据有何价值? 连接产品如何创收?
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