分析15万份招聘数据，发现生成式AI正重塑职场技能需求。
Generative-AI and the transformation of workforce. A job postings-driven analysis
- 基于15万份职位招聘数据，追踪AI相关技能演变趋势。
- 2021年后提示工程等技能激增，数据录入等常规工作减少。
- 预测到2025年，人机协同型复合能力成就业新标准。
本文研究生成式人工智能如何重塑全球劳动力市场的岗位要求、技能结构与行业动态。基于12个公开数据集和1个公共API，构建了涵盖2018至2025年超过15万份英文职位招聘的多源语料库。采用词法提取、语义框架分析、主题建模（BERTopic、LDA、KMeans）及时间序列预测（ARIMA）等方法，将技能分为五大维度：AI_Data、Routine、Soft_Meta、Domain_Specific与Leadership。通过句向量嵌入与余弦相似度计算出‘框架指数’，区分增强型与自动化导向的表述。结果显示，2021年后AI相关技能提及显著上升，包括提示工程、微调与模型验证；而数据录入、手动编码等常规任务下降。预测表明，至2025年，AI_Data与Soft_Meta技能将持续增长，预示着人机协同型复合能力将成为新的就业基础。
原文摘要 · Abstract (English)
This paper investigates how generative-artificial intelligence AI is reshaping job requirements, skill compositions and sectoral dynamics across global labor markets. It examines the evolving frequency and framing of AI-related competencies in job postings, exploring whether generative-AI functions primarily as an augmentative or substitutive force in the workplace. A large-scale, multi-source corpus of over 150,000 English-language job postings 2018-2025 is compiled from twelve open-access datasets and one public API. The analytical framework integrates lexical skill extraction, semantic framing, topic modeling, BERTopic, LDA, KMeans, and time-series forecasting ARIMA. Skill mentions are categorized into five dimensions: AI_Data, Routine, Soft_Meta, Domain_Specific and Leadership, while cross sectoral analyses and correlation matrices quantify interdependencies between competencies. Sentence-transformer embeddings and cosine similarity are used to compute a Framing Index, distinguishing augmentation- versus automation-oriented discourse. Investigating job postings, our research contributes a replicable, data driven methodology for mapping the diffusion of AI related skills across industries and time. Results reveal a sharp post-2021 increase in AI-related skill mentions: prompt engineering, fine-tuning and model validation, accompanied by a decline in routine tasks: data entry and manual coding. Forecasts suggest sustained growth in AI_Data and Soft_Meta skills through 2025, signaling a structural convergence toward hybrid human-AI expertise as a new foundation of employability.
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