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GSMA:2026中小企业 AI 规模化落地:南非 AI 数据治理环境洞察报告(英文版)(60页).pdf

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1、Scaling AI for SMEsInsights Into South Africas AI Data Governance EnvironmentThe GSMA is a global organisation unifying the mobile ecosystem to discover,develop and deliver innovation foundational to positive business environments and societal change.Our vision is to unlock the full power of connect

2、ivity so that people,industry,and society thrive.Representing mobile operators and organisations across the mobile ecosystem and adjacent industries challenges,the GSMA delivers for its members across three broad pillars:Connectivity for Good,Industry Services and Solutions,and Outreach.This activit

3、y includes advancing policy,tackling todays biggest societal issues,underpinning the technology and interoperability that make mobile work,and providing the worlds largest platform to convene the mobile ecosystem at the MWC and M360 series of events.We invite you to find out more at GSMA Central Ins

4、ights UnitThe Central Insights Unit(CIU)sits at the core of GSMA Mobile for Development(M4D)and produces in-depth research on the role and impact of mobile and digital technologies in advancing sustainable and inclusive development.The CIU engages with public and private sector practitioners to gene

5、rate unique insights and analysis on emerging innovations in technology for development.Through our insights,we support international donors to build expertise and capacity as they seek to implement digitisation initiatives in low-and middle-income countries through partnerships within the digital e

6、cosystem.Contact us by email: This material is funded by the UK governments Foreign,Commonwealth&Development Office(FCDO)through its Global Research and Technology Development portfolio.The views expressed in this report are those of the authors and do not necessarily reflect the official policy or

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1. **南非AI数据治理现状**:南非拥有非洲最全面的数据治理环境,受《个人信息保护法》(POPIA)保护,但缺乏AI专项指导,中小企业(SMEs)合规能力不足,仅51%全面实施POPIA措施。 2. **SMEs AI采用瓶颈**:72%的SMEs AI影响指数为中等,主要障碍包括高成本(39%认为前三)、数据碎片化(31%)及资本约束,仅22%定期评估AI风险。 3. **数据治理挑战**:44%的SMEs通过正式协议共享数据,但多数未覆盖AI用途;32%依赖国际云服务,面临跨境数据合规风险。 4. **案例与建议**:医疗与金融领域案例显示,缺乏行业特定标准及模型漂移监管。建议包括建立监管沙盒、提供SMEs专项工具包及数据共享激励机制。
AI治理困境? 数据合规难题? 中小企业AI路在何方?
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