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Informatica:2026年首席数据官(CDO)洞察报告:数据治理、数据信任悖论与 AI 素养成为核心焦点(中译版)(16页).pdf

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1、ReportCDO Insights 2026Data governance and the trust paradox of data and AI literacy take center CDO Insights 2026:Data governance and the trust paradox of data and AI literacy take center stage2ContentsExecutive Summary 3Key Findings 4Making Room for AI 5-Spotlight:Organizations Eye Customer Experi

2、ence Enhancements with AI 6Taking AI from Pilot to Production 7-Spotlight:Improvements to Data and Resources Are Aiding GenAI Success 8The Need to Temper Employee Trust 9Governing AI for Confidence in Responsible Use 10Data Management Investments 12Vendor Support 13Conclusion 14About Wakefield Resea

3、rch 15Methodology Notes 15About Informatica 16About Salesforce 16About Deloitte CDO Insights 2026:Data governance and the trust paradox of data and AI literacy take center stage3Executive SummaryThe moment has come:AI has transitioned from experimental technology to a strategic,transformational impe

4、rative.Now comes the hard part.With organizations exploring use cases and steering initiatives toward production,many are discovering that the growing,widespread use of AI at their companies is exposing infrastructure and governance gaps as well as shortfalls in employees data literacy and AI litera

5、cy.The enthusiasm around AI is being tempered by the realization that there are high-stakes challenges ahead that need to be addressed if ongoing and future AI initiatives are to continue finding success.Many are embracing the mindset that going all-in on AI is the only way to make it work.AI adopti

6、on has reached a tipping point at companies,with 69%having incorporated generative AI(GenAI)into their business practices and another 25%expecting to do so in the next 12 months,according to a survey of 600 data leaders(CDOs,CDAOs and CAOs)from companies with$500M+in revenue across the U.S.,UK/EU an

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1. **AI普及与挑战**:69%企业已采用生成式AI(GenAI),47%采用代理式AI(Agentic AI),但50%面临数据质量/检索问题,57%视数据可靠性为落地主要障碍。 2. **信任悖论**:65%员工信任AI数据,但75%需提升数据素养,74%需提升AI素养,76%认为AI治理未跟上员工使用速度。 3. **投资方向**:86%企业将增加数据管理投入,重点改善数据隐私安全(43%)、AI治理(41%)及员工技能(39%)。 4. **治理路径**:48%通过扩展现有数据治理工具管理AI,30%采用独立工具,但后者更易实现有效治理。 5. **未来展望**:AI项目将加速落地,但需以高质量数据和可靠治理为基础,以实现客户体验优化、决策智能化等价值。
AI信任危机? 数据治理难题? AI落地挑战?
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