Abstract: The new-round scientific and technological revolution and industrial transformation are reshaping the global landscape at an unprecedented pace. As a strategic technology driving this transformation, artificial intelligence has become a core focus of global technological competition. Against the backdrop of advancing the “AI+” initiative and fostering new-quality productive forces, artificial intelligence in China has pervaded science and technology, industry, people’s livelihood, governance and other fields. While unlocking socio-economic momentum, it has also given rise to multiple security-related challenges including supply-chain risks, algorithmic ethics, employment polarization. Balancing development and security has gradually become the central thread of artificial intelligence governance. At present, domestic practices of AI integration tend to prioritize industrial scale expansion with insufficient consideration of potential risk costs. Some applications remain at the shallow implementation stage, and in-depth integration needs further improvement. Evaluation tools that take both development benefits and security risks into account are still inadequate. This paper sorts out the multi-dimensional impacts of AI-integrated development on economy, industry, employment and global competition, and analyzes the practical bottlenecks in evaluating its effectiveness. Drawing on differentiated evaluation approaches from the United States, the European Union, Japan and South Korea, it puts forward suggestions on evaluation pathways, so as to provide references for judging the effectiveness of AI-integrated development and coordinating innovative development with whole?chain risk prevention and control.

Key words: AI+, integrated development effects, evaluation system, coordination of development and security

摘要： 新一轮科技革命与产业变革正以前所未有的速度重塑全球格局，人工智能作为引领这一变革的战略性技术，已成为全球科技竞争的核心焦点。在全面推进“人工智能+”行动、加快培育新质生产力的时代背景下，我国人工智能全面渗透科技、产业、民生、治理等各领域。在释放经济社会发展动能的同时，衍生出供应链风险、算法伦理、就业分化等多重安全挑战，统筹发展与安全逐步成为人工智能治理的核心主线。当前国内对人工智能融合实践更多关注产业规模扩张，对潜在风险成本考量相对不足，部分应用停留在浅层落地层面，深度融合程度有待提升，兼顾发展效益与安全风险的评估工具仍较为欠缺。本文通过梳理人工智能融合发展对经济、产业、就业、全球竞争等的多维影响，剖析人工智能融合发展成效评估的现实瓶颈；借鉴欧美等发达国家的差异化评估实践，提出适配我国的评估路径，为研判人工智能融合发展成效、统筹创新发展与全链条风险防控提供有益参考。

关键词: 人工智能+, 融合成效, 评估体系, 发展与安全