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印孚瑟斯(Infosys):2025技术导航:代理型AI的行业应用研究报告(中译版)(52页).pdf

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1、TECH NAVIGATOR:SECOND EDITION APPLYING AGENTIC AI TO INDUSTRIESKnowledge Institute2|Tech Navigator|Second Edition:Applying Agentic AI to IndustriesExternal Document 2025 Infosys Limited Tech Navigator|Second Edition:Applying Agentic AI to Industries|3External Document 2025 Infosys Limited Knowledge

2、InstituteExecutive summary 4Unified operational control in oil and gas 6Inventory discrepancy in the retail industry 12How to manage discretionary risk in financial services 20Agentic AI is redefining the manufacturing value chain 30How agentic AI is re-engineering telecom business sales 44CONTENTSK

3、nowledge Institute4|Tech Navigator|Second Edition:Applying Agentic AI to IndustriesExternal Document 2025 Infosys Limited Executive summaryIn our last edition of Tech Navigator,we explained the rise of agentic AI and how it amplifies business.AI agents are already enabling organizations to reimagine

4、 and re-engineer business processes when the ROI is justified and on a smaller scale,drive process automation and simplification.Beyond re-engineering,ongoing experiments pave the way for vibe coding and exploration for business users to continuously innovate.Many large enterprises have found that i

5、mplementing intelligence at scale is easier said than done.They need an architecture-first approach,and they need to treat AI as a transformative program.At the same time,it is important to set up the right hub and spoke operating model,backed by a value-and outcome-driven AI investment approach.On

6、the technology front,building AI runways that power platform and democratization capabilities across all layers of the architecture is proving key to effective AI scaling.Agentic AI is already proving its value in broad domains,such as IT,business operations,and information intensive business proces

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根据《Tech Navigator: Second Edition》报告,以下是全文关键点: 1. **Agentic AI 的兴起**:人工智能代理正在改变业务流程,提高效率,并推动自动化。 2. **行业应用**:报告重点介绍了Infosys如何利用Agentic AI解决五个不同行业的实际问题,包括: - 石油和天然气行业的统一运营控制 - 零售行业的库存差异管理 - 金融服务业的自主风险管理 - 制造业的飞机和车间维护 - 电信公司的业务销售流程 3. **技术挑战**:Agentic AI 需要与现有系统集成,特别是对于资产密集型行业。 4. **MCP 协议**:模型上下文协议(MCP)作为连接AI代理和现有系统的桥梁,实现统一运营控制。 5. **实施风险**:实施MCP时,应优先考虑安全、安全和可靠性。 6. **Agentic AI 的战略重要性**:Agentic AI 对于资产密集型行业是必要的,可以预防停机时间并优化生产。 7. **零售行业**:Agentic AI 可快速识别库存差异,并自动纠正,从而提高效率。 8. **金融服务业**:Agentic AI 在风险管理方面具有优势,例如合规性、贷款审批和交易。 9. **制造业**:Agentic AI 可在工程、生产和供应链流程中实现自主性,提高效率。
制造业新纪元" "零售业库存难题,AI如何破解?" "金融风控升级,AI助力决策"
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