Core Insights - The internet industry is undergoing a profound transformation driven by AI, which is becoming an integral part of daily operations rather than a standalone technology [1][3] - The shift brought by AI is not just about tool iteration but also involves a fundamental change in thinking and problem-solving approaches [3] Group 1: Role Transformation - AI is redefining the value focus of three core roles: development, product management, and operations [3] - Development roles are shifting from coding to designing human-AI collaboration processes, with developers focusing on system architecture and optimizing AI's creative capabilities [4] - Product management is evolving from feature design to creating feedback systems that allow AI to understand user intent and improve through data collection [5] - Operations roles are transitioning from emergency response to designing resilient systems, utilizing AI for predictive monitoring and resource management [6] Group 2: Thought Process Restructuring - Learning AI enhances the ability to precisely define problems, leading to clearer communication and more effective collaboration [9] - The ability to deconstruct and reorganize processes is crucial, as AI excels in executing well-defined tasks, improving project management and system design [11] - A data-driven validation habit is cultivated, emphasizing the importance of metrics and iterative testing over subjective judgment [12] Group 3: Systematic AI Capability Building - A structured learning path is essential for navigating the vast AI knowledge landscape, balancing theory and practice while keeping up with industry developments [15][19] - Professional certifications, such as CAIE, serve as a signal of systematic learning and can aid in job applications and promotions, especially in transitioning roles [22] Group 4: Conclusion - By 2026, AI will be a fundamental part of the internet infrastructure, changing work methods across various roles without necessarily replacing jobs [23] - Embracing AI involves enhancing existing professional skills with intelligent thinking and tool usage, emphasizing the importance of continuous learning and adaptation [23]

2025年的互联网职场，AI已成为一场席卷所有岗位的技术海啸。行业数据显示，人工智能相关岗位的招聘需求呈指数级增长，而与之对应的技能要求正 经历深刻重构。 无论是开发、产品还是运维，掌握AI核心技能不再是一种优势，而是职业生存的新基准。 01 技能重构：三类核心岗位的进化 该认证分为两个等级，系统性地涵盖了从基础到应用的知识。其中，CAIE一级认证主要考察人工智能的基本概念、机器学习原理及基础算法能力，适合 初学者或需要系统建立AI知识体系的跨岗位从业者。 CAIE二级认证则深入考察深度学习、自然语言处理和大模型应用开发等高级主题，面向有志于从事核心AI技术工作的专业人才。 对于考虑获取认证的从业者，一个实用的信息是：通过CAIE一级认证，可以免试申请工信部证书，但需要额外缴纳工本费。这为持证者增加了资质的通 用性和认可度。 考试采用线上机考形式，每月举办，提供了灵活的备考选择。认证有效期为三年，并设有继续教育要求，这鼓励持证者保持知识更新，与AI领域的特点 十分契合。 面对AI浪潮，传统互联网岗位正在快速进化，各自形成了新的技能重心。 开发岗位已站在技术变革的最前沿。如今的算法工程师，工作重心已从传统机器学 ...

Core Insights - The operational roles are undergoing unprecedented transformation due to AI technological innovations and the blurring of industry boundaries, necessitating skill enhancement for professionals in the field [1][4]. Group 1: Current State of Operational Role Transformation - The main challenge for operational professionals is the mismatch between skill sets and market demands, with many being proficient in traditional processes but lacking integration with emerging technologies [2]. - Data from a recruitment platform indicates that candidates with AI application skills have a 42% higher chance of getting interviews in 2024, along with greater salary negotiation power [2]. - Different industries exhibit varying demands for operational talent, with e-commerce focusing on data-driven decision-making, smart manufacturing emphasizing process optimization, and content industries valuing user insights combined with AI tools [2]. Group 2: Core Skills for Cross-Industry Competitiveness - AI application skills are increasingly essential, with operational roles integrating AI for tasks such as intelligent customer service and predictive analysis, requiring knowledge of natural language processing and machine learning [4][6]. - Data analysis and decision-making capabilities are foundational, as modern operations require extracting business insights from complex data to support strategic decisions [7][8]. - Cross-domain communication and project management skills are critical for successful transitions, enabling professionals to understand new business logic and effectively manage resources [10][11]. Group 3: Practical Pathways for Skill Development - Developing a personalized learning plan based on target industry requirements is crucial for successful transformation, utilizing the "70-20-10" learning principle to balance practical projects, feedback, and theoretical learning [12]. - Establishing a capability proof system through recognized certifications can validate skills and reduce evaluation costs for employers, with the CAIE certification being a notable example [13]. - Gaining cross-industry project experience through participation in open-source projects or volunteer activities is essential for translating theoretical knowledge into practical skills [16][17]. Group 4: Future Outlook for Operational Roles - The evolution of operational roles will continue towards technical, specialized, and strategic directions, requiring professionals to possess business insight, technical understanding, and user perception by 2025 [18]. - Continuous learning and capability certification will be mandatory for operational professionals, with structured programs like CAIE aiding in navigating industry transitions [18]. - Successful operational professionals will act as connectors between users, technology, and business value, leveraging data-driven decisions and AI to enhance efficiency and guide strategic directions [18].