作为新一代数字技术集合体，生成式人工智能成为新一轮科技革命的重要驱动力。推进人工智能与教育 深度融合，是加快建设教育强国、办好人民满意教育的重要举措，也是抢占国际科技竞争主导权、加快 发展新质生产力的必然要求。生成式人工智能为高等教育注入了新活力，为破解教育教学难题提供了新 路径。 发展新质生产力，支撑在科技，关键在人才，基础在教育。加快生成式人工智能与教育深度融合，激活 教育新质生产力，开辟教育发展新赛道，塑造教育发展新优势，有助于坚定不移地走好拔尖创新人才自 主培养之路，为以中国式现代化全面推进中华民族伟大复兴提供强大支撑。 （作者为华中师范大学党委书记，本报记者田豆豆整理） 升级人才培养模式。从人际交互的"师—生"教学，到人机交互的"师—生—机"教学，再到人智协同 的"师—生—智"教学，生成式人工智能有助于重塑教育生态，缓解"标准化供给"与"个性化需求"之间的 矛盾。比如，生成跨学科的探究项目、实时案例与个性解释，渗入智能问答、智能备课、智能摘要、智 能批阅等"教、学、管、评、考"全链条，构建云端、终端、场景端无缝衔接的开放场域等，推进人智协 同，能够帮助师生自主学习、深度探究或即时答疑。 提高人才供给 ...

Core Insights - The report titled "2025 Generative Marketing Industry Research: From AIGC to AIGD" highlights the evolution of generative AI in marketing, transitioning from AIGC (AI-Generated Content) focused on content creation to AIGD (AI-Generated Decision) centered on decision support, indicating a shift from AI as an "efficiency tool" to a "strategic partner" in marketing [2][4]. AIGC: Marketing Supply Explosion - By 2025, generative AI has matured in creating marketing content, including copy, images, videos, and digital personas, significantly enhancing content supply [3]. - The emergence of new models and products like DeepSeek and Manus has lowered technical barriers, evolving AI from a "creative assistant" to an "execution agent" [3]. - However, the explosion of content supply raises challenges for businesses in selecting optimal solutions and ensuring the authenticity and reliability of AI-generated content, as AIGC addresses production issues but not effectiveness [3]. AIGD: Systematic Upgrade in Marketing Decisions - AIGD aims to resolve decision-making challenges from the AIGC era by integrating classic marketing theories with AI tools, creating a complete loop from "insight—generation—validation—decision" [4]. - On the consumer side, over 68% of consumers are influenced by AI recommendations in their purchasing decisions, indicating a shift in decision-making power towards AI [4]. - On the enterprise side, AI is utilized for core marketing tasks such as environmental analysis, brand positioning, and demand exploration, enhancing the scientific and efficient nature of marketing decisions [4]. AI Practices: Deepening Industry Applications - Generative AI has been implemented across various industries: - **Food and Beverage**: Companies like Mengniu and Yili use AI for health models and ad testing [5]. - **Beauty and Personal Care**: L'Oréal optimizes formula development with AI, while Proya builds ROI-driven decision systems [5]. - **Automotive**: AI enhances lead management and user profiling [5]. - **Alcohol Industry**: AI integrates into brewing processes and enhances cultural experiences through digital personas and the metaverse [5]. - **Dining and Retail**: Smart ordering and AI-driven site selection are core to digital transformation [5]. - **Apparel, Home Appliances, and Digital Products**: AI assists in design, sales forecasting, virtual fitting, and customer service [5]. Future Outlook: Human-AI Collaboration with Decision Priority - The future of generative marketing emphasizes human-AI collaboration rather than AI replacing humans, necessitating organizations to build "AI-ready" structures that deeply integrate AI into strategy, operations, and innovation processes [6]. - The transition from AIGC to AIGD represents a shift from "content-driven" to "decision-driven" approaches, where effective use of AI for decision-making will determine market success [6].

Core Insights - The 2025 World Digital Education Conference concluded with the release of the "Top Ten Global Hotspots in Digital Education Research" [1][4] - The report was based on nearly 60,000 digital education papers from 2019 to 2024, utilizing bibliometric analysis and insights from interdisciplinary experts [1] Group 1: Top Ten Hotspots - Generative AI accelerating interdisciplinary integration [2][3] - Metaverse technologies catalyzing smart learning paradigms [2][3] - Digital education transforming cognition of learning behaviors [2][3] - AI empowering personalized learning: the future is now [2][3] - Digital literacy supporting teachers' professional development [2][3] - Human-AI collaboration reshaping the digital education ecosystem [2][3] - Vocational education aligning with smart technology-driven innovation demands [2][3] - Global co-governance redefining ethical boundaries in digital education [2][3] - Digital education bridging regional gaps in balanced development [2][3] - Data driving intelligent decision-making across the entire teaching process [2][3]