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Gartner:2025年领导力前瞻:首席数据与分析官的三大战略重点(中译版)(11页).pdf

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1、Leadership Vision for 2025Top 3 Priorities for Chief Data and Analytics Officers2Gartner for CDAOs Follow Us on LinkedIn Become a Client Leadership Vision for 2025About 75%of chief executives identify AI as the technology poised to impact their industry most significantly over the next three years,a

2、nd AI investment is supported by executive leadership.Despite the rivalry for“who owns AI”among C-Level leaders,the chief data and analytics officer(CDAO)and the data and analytics(D&A)function are central,as organizations with an AI-ready D&A foundation see a 20%improvement in AI-related business o

3、utcomes.To establish themselves as key partners and AI influencers in the business,CDAOs should:Create value by aligning D&A and AI initiatives to strategic business priorities Build and scale data,analytics and AI foundations to realize value Elevate leadership influenceUse this research to underst

4、and the major trends and opportunities affecting the D&A function in 2025,and the actions CDAOs should prioritize.IntroductionWhat are the major trends affecting CDAOs?What are the top challenges and priorities for CDAOs in the year ahead?What actions do CDAOs and their teams need to take to succeed

5、?Key questions addressed3Leadership Vision for 2025Gartner for CDAOs Follow Us on LinkedIn Become a Client 3 Trends Defining the Data Analytics Landscape in 2025Pressure to demonstrate value has never been more acute,but a critical gap remains in terms of how CDAOs are able to communicate the busine

6、ss value of their investments and performance.CDAOs are pivotal to AI success.Ballooning investment in AI represents a significant opportunity for CDAOs.Organizations with AI-ready data report a 20%improvement in business outcomes.New organizational and leadership complexities present real challenge

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根据报告的内容,全文主要讨论了2025年数据和分析领导层(CDAOs)的愿景、挑战和优先事项。研究表明,约75%的首席执行官认为人工智能(AI)是未来三年内对其行业影响最大的技术,而AI的投资得到了高层领导的支持。CDAOs在AI的成功中起着关键作用,组织需要建立一个AI准备好的数据和分析(D&A)基础,以实现20%的AI相关业务成果改进。CDAOs应致力于将D&A和AI倡议与战略业务重点对齐,建立和扩展数据、分析和AI基础,以实现价值,并提升领导影响力。面临的主要挑战包括CDAOs在沟通业务价值方面遇到困难,以及组织内不同部门之间的协作问题。到2027年,70%的通用AI项目将在概念验证阶段后因数据质量差、风险控制不足、成本上升或业务价值不明确而废弃。因此,CDAOs及其团队需要采取一系列行动,包括建立预算和资金案例、理解数据、分析和AI基础、消除业务和IT团队之间的功能壁垒等,以实现成功。
"如何通过数据和分析实现业务增长?" "CDAO如何在组织中建立自己的战略合作伙伴地位?" "如何打造具备AI能力的数据和分析基础设施?"
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