这两年，AI走进办公室已经不算新鲜事，用AI辅助写作、查阅邮件或是总结信息等。也有一些公司用AI充当客服，提供协助咨询服务。但AI始终是一个辅 助性质的工具，一切都还要听使用者发号施令。假如角色反转，让AI检查真人的工作，会是怎样？ 日本电信公司KDDI启用的策略名为"AI上司/AI本部长"系统，这套大模型预先学习了真实本部长的说话方式、常用口头禅、决策习惯和审批逻辑，然后投入 到工作流。简单来说，就是KDDI给自己的员工配了个"AI老板"，你写完企划书、提案、内部申请后，直接交给AI，它会给出反馈。 当然，虽然KDDI给这个系统设计了相对高级的职位，但实际上却不是那么回事。"AI上司/AI本部长"系统真正参与到的工作，其实还是负责查阅、审批等简 单的事物，最核心解决的是大企业中繁杂的审批流程，以及应对上级领导缺勤时的工作检查的等问题。 如果有一天，你交上去的方案不是被老板看，而是被一个AI查阅、点评、修改，甚至直接决定能不能过，会是什么感觉？ 这听起来很荒谬，但一家公司已经开始这么干了。日本大型电信公司KDDI近期启用"AI老板"战略，通过大模型学习管理层的工作模式和点评语气，直接用 于处理员工提交的方案、 ...

Core Viewpoint - The company, Qichuang Data, has developed an AI management solution for chain store scenarios, utilizing a "camera + backend data" approach to enhance operational efficiency across various industries [2] Group 1: AI Management Solution - The solution is designed for multiple sectors including baking, catering, clothing, and retail, demonstrating its versatility [2] - It enables 24/7 monitoring and management for service scenarios such as bank counters, ensuring continuous oversight [2] - The solution allows for customizable detection models based on specific scene requirements, focusing on key dimensions like service response timeliness, staff dress code compliance, and operational adherence [2] Group 2: Performance Monitoring and Training - The solution can generate efficiency monitoring reports and alerts for key store issues, enhancing operational awareness [2] - An AI training component is included to help employees identify performance gaps and boost their sense of achievement, ultimately improving service quality and efficiency [2]

Core Insights - OpenAI has categorized AGI into five levels, with current AI Agents operating at the second or third stage, transitioning from tools to "digital labor" capable of completing specific tasks [1][2] - The management of AI Agents is becoming crucial as the industry shifts from "productivity competition" to "restructuring production relationships," necessitating effective collaboration among AI Agents [2][4] - Bika.ai aims to position itself as the "intelligent manager" of AI Agents, focusing on enhancing management capabilities and redefining collaboration between humans and AI [3][4] Group 1: AI Agent Management - The emergence of AI Agents as a mainstream workforce highlights the importance of effective management, which will be a key competitive advantage [3] - Bika.ai's product is designed to manage AI Agents, addressing issues of task division and scheduling, thereby creating a structured "company system" for AI labor [4][5] - The company has received significant investment to tackle challenges related to AI Agent management and aims to develop a framework for AI management studies [5] Group 2: Value Quantification and Compensation - The widespread adoption of AI labor will necessitate the integration of AI Agents into corporate payroll systems, raising questions about how to quantify their labor value [8][9] - Bika.ai proposes a subscription model based on "human seats + usage," which enhances transparency in measuring work outcomes and facilitates the development of AI Agent capabilities [8] - The future of wage distribution in companies is expected to shift from execution to AI management, creating a substantial market for those who master management capabilities [9] Group 3: Security and Compliance - As multiple AI Agents collaborate, data security and compliance become critical, with Bika.ai implementing sandbox isolation to prevent data leakage between Agents [10] - Bika.ai's partnership with Amazon Web Services provides the necessary infrastructure and compliance support to facilitate the global deployment of AI management solutions [11][12] Group 4: Future Outlook - The evolution of AI management systems is expected to transform AI from a competitor to a collaborator, enhancing human value and simplifying user interactions with AI [13] - Bika.ai plans to develop an "Agent Store" to centralize task completion, positioning itself as a proactive entity in the AI labor market [13]