2025年新兴技术趋势报告_人工智能与大数据发展4.0（英文版）-国际电信联盟_106页_5mb

Summary

Purpose

This report aims to assist developing countries in leveraging artificial intelligence (AI) and big data for sustainable development by addressing key challenges and offering policy recommendations. It emphasizes the need for strategies that focus on data infrastructure, skills development, and inclusive innovation.

Key Challenges

• Data issues: Limited data creation, poor accessibility, interoperability problems, and quality concerns.
• Infrastructure gaps: Inadequate electricity, connectivity, and digital infrastructure, especially in rural areas.
• Skills shortage: Lack of AI and data literacy among the workforce and policy implementation barriers.

Opportunities in Application

AI and big data can transform sectors like health, agriculture, and education:

• Healthcare: Improved diagnostics, disease surveillance, and pandemic response.
• Agriculture: Precision farming, crop monitoring, and climate-resilient strategies.
• Education: Personalized learning and equitable access through digital tools.

Policy Recommendations

• Invest in FAIR data infrastructure to ensure data findability, accessibility, interoperability, and reusability.
• Promote data sharing frameworks and open data policies to foster collaboration and innovation.
• Develop a national AI and data strategy with clear governance structures, ethical guidelines, and targeted stakeholder engagement.

Action Plan Template

A successful strategy includes:

• Stakeholder involvement across government, private sector, academia, and civil society.
• Milestones and tasks linked to budget allocations to track progress.
• Implementation mechanisms such as regulatory sandboxes and cross-functional teams.

Conclusion

Developing countries must prioritize data-driven initiatives with tailored policies to address systemic barriers and capitalize on global AI advancements for inclusive development.