2026_AI就绪度_构建标准化就绪度框架分析报告V2.0_55页_1mb

报告摘要

AI Ready – Analysis Towards a Standardized Readiness Framework Summary

Core Content

The ITU AI Readiness project aims to develop a standardized framework for assessing the readiness of countries, enterprises, and organizations to integrate and benefit from AI technologies. The project, launched in 2024, uses a bottom-up approach to derive dimensions, metrics, and indices for AI readiness by analyzing real-world use cases and engaging with global experts.

Main Viewpoints

AI is reshaping society: It offers transformative potential in healthcare, climate resilience, education, and digital inclusion.
AI Readiness is multidimensional: It includes data readiness, digital infrastructure, digital skills, innovation ecosystem, and AI policy.
Collaboration is key: The project brings together stakeholders from industry, academia, government, and civil society to foster a shared understanding of AI readiness.
Regional customization is essential: The framework allows for tailored application through indices and metrics, enabling users to prioritize based on local needs.
Toolkits and challenges enhance engagement: The AI Readiness Enablement Toolkit (AI-RE Toolkit) and the AI Readiness Challenge are designed to support self-assessment and increase adoption.

Key Information

AI Readiness Framework Dimensions

Dimension	Indices & Metrics
Data	- Data Accessibility<br>- Data Service Capability (Quality, Labeling)<br>- Data Governance (Bias, Fairness)<br>- Data Interoperability
Digital Infrastructure	- Connectivity<br>- Computing Capacity<br>- Device<br>- Automation<br>- Access to AI
Digital Skills	- Education (STEM Graduates, AI Courses)<br>- Digital Literacy (ICT Skills, AI Skills)<br>- AI Application Development
Innovation Ecosystem	- Standards (Data, AI Pipeline, Benchmarking, Energy, Vertical Applications)<br>- Open Source<br>- R&D (Investment, Publications)<br>- Investment (Public, Private, VC)<br>- AI Technology Source (Export, Import)
AI Policy	- AI Policy and Regulation (National Strategies, Ethics Framework, Policy Tools)<br>- Regulatory Quality (Implementation, Flexibility, Sandbox)<br>- Implementation (Guidelines, Supervision, Content)

Insights from AI Readiness Study

ICT education and open-source ecosystems are vital for accelerating AI skills development.
Digital literacy correlates with national income, but middle-income countries show higher optimism toward AI.
Data readiness is critical for trustworthy and inclusive AI adoption. Quality, diversity, and governance of datasets influence AI performance and fairness.
Internet penetration remains uneven globally, with low-income economies lagging significantly.
Computing infrastructure and energy supply are key constraints for AI deployment.
Open-source engagement is a strong indicator of AI readiness, influencing R&D, innovation, and standardization.
Investment in AI (both public and private) supports the development of scalable and interoperable systems.
Regional performance varies based on the interplay between academia, industry, and governance in AI standardization and development.
Policy and regulation are essential to align AI adoption with ethical, legal, and technical standards.
Effective coordination between public and private investment is crucial for building competitive and innovative AI ecosystems.

Toolkit and Engagement

The AI-RE Toolkit is a dynamic and living tool that allows users to self-assess their AI readiness using a knowledge base built from ITU's AI Readiness studies.
The toolkit integrates regional customizations and is designed to evolve with new data and insights.
The ITU AI Readiness Challenge was launched in October 2025 to engage a broader audience and encourage the development of the knowledge base.

Future Work

The project will continue to expand the Plugfest initiatives.
The AI-RE Toolkit will be launched in 2026.
AI Readiness standards will be developed.
The ITU AI for Good Sandbox Network will be expanded to support more AI experiments and deployments.

Conclusion

The ITU AI Readiness project represents a comprehensive effort to build a global, standardized framework for assessing AI readiness. It emphasizes the importance of collaboration, data quality, digital infrastructure, skills development, and policy alignment in enabling effective AI adoption. The project also highlights the role of open-source technologies and investment strategies in fostering innovation and ensuring ethical, scalable, and inclusive AI deployment.

The AI-RE Toolkit and AI Readiness Challenge are key instruments for engaging stakeholders and supporting the practical application of the framework. The project is expected to evolve into ITU AI Readiness 3.0, further strengthening global AI governance and capacity building.

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