当 Agent 真正进入企业流程，哪些工作可以交给 AI ？50 + 实战案例揭晓答案！
AI 正在从回答问题的辅助工具，走向理解目标、调用系统、完成任务的工作承担者。当 Agent 真正进入企业流程，问题不再是 “如何把 AI 做出来”，而是哪些工作可以交给 AI、结果如何验收、权限、成本与风险如何收住。随着大模型向推理、工具调用、多模态和长任务延伸，开发重心正从单次调用转向上下文、工具、执行环境与反馈回路的设计，Coding Agent 也从代码补全演进为能理解代码库、运行测试、完成复杂任务的工程协作者。OpenAI、Google Cloud、Anthropic 的最新实践共同指向一个结论：模型决定 Agent 能做什么，工程决定它能否真正进入生产、创造价值。
在这一背景下，2026 年 AICon 人工智能开发与应用大会 · 北京站正式启动。本次大会将于 12 月 18–19 日，在北京新云南皇冠假日酒店举办。本届大会以探索 A 应用边界为主题，设置 13 大技术专题，覆盖大模型后训练、推理优化、Agent 工程、知识工程、智能体评测与安全、自进化系统、AI 软件交付、原生架构及组织变革等核心方向，汇聚一线技术专家，深入分享 AI 技术突破与企业规模化落地的真实实践。
芯博士 SIMBOSS 联合创始人 &CTO 潘成宾已确认出席 “AI 时代的组织重构” 专题，并发表题为《从提效到扩能：AI 驱动小团队的能力突破与组织演进》的主题分享。AI 对小团队的影响，正在从提升既有工作的效率，延伸到扩展团队能力与成员责任。本次分享结合智能硬件连接业务，以 eSIM LPAd 与多平台 SDK 能力建设为技术背景，讨论团队如何借助 AI 承担过去难以覆盖的工作，并据此调整角色与协作方式。
本次分享将重点展开两个组织案例：一位测试工程师从质量把控走向客户需求与项目推进，以及产品、研发、运营共同参与售前和客户项目。通过这些实践，讨论技术负责人如何为成员提供机会与支持，明确责任边界，并将个人能力的扩展沉淀为团队解决客户问题的能力。演讲同时呈现仍在探索的难点，为小团队推进 AI 应用和组织调整提供参考。
潘成宾，芯博士（SIMBOSS）CTO，负责技术方向、产品研发与团队建设，围绕智能硬件连接、eSIM、端侧 SDK 及全球联网服务推进产品与客户项目。关注 AI 在研发、产品和运营等角色中的实际应用，探索小团队如何借助 AI 提高产出、建立多平台 SDK 等新能力，并推动专业人员更直接地参与客户需求与项目交付。实践重点包括技术与业务协同、角色发展、交付责任及可复用能力建设。
他在本次会议的详细演讲内容如下：
演讲提纲
1. 提效之后，我们观察到了什么？
- AI 在研发、产品和运营等角色中的应用
- 从工作产出增加，到可承担任务范围扩大
- 能力变化对原有岗位分工提出了哪些新问题
2. 能力突破：eSIM LPAd 与多平台 SDK 实践
- 客户需求与团队原有能力之间的缺口
- AI 参与方案探索、实现及交付准备的方式
- 工程师的专业判断、验证与能力沉淀
3. 角色变化：从测试工程师到客户项目经理
- 测试与质量经验如何延伸到需求理解和项目推进
- 从负责专业环节，到组织多方完成项目
- 管理者如何提供机会、授权、支持与反馈
- 新角色中仍需培养的能力和明确的边界
4. 协作变化：产品、研发、运营共同走向客户
- 各角色在售前和项目中的参与方式
- 如何共同判断需求、可行性、成本及运营条件
- 阶段牵头人、专业负责人和销售如何协作
- 将一次客户项目的经验转化为可复用能力
5. 方法提炼：从个人扩能到团队能力
- 从真实任务识别 AI 的应用机会
- 根据能力变化调整工作范围与协作方式
- 同步建立责任、验证和支持机制
- 用工作产出、能力复用及客户问题解决情况观察效果
听众收益
- 获得区分 AI 提效、能力扩展与组织变化的框架，能够从工作产出、能力复用及客户问题解决情况评价 AI 应用价值
- 获得将成员新增能力转化为更完整工作责任的思路，识别角色前移所需的授权、支持、验证与反馈机制
- 学习产品、研发、运营共同参与客户需求及项目推进的协作方法，明确阶段牵头、专业责任与商务配合，促进个人能力沉淀为团队能力
除此之外，本次大会还策划了Post-Training Engineering｜数据、奖励与模型能力塑造、大模型推理与算力调度实践、Knowledge Engineering｜让 Agent 理解企业、Multi-Agent Systems、智能体评测与生产可靠性探索、Agent Security｜身份、权限与行动安全、AgentOps｜企业 Agent 全生命周期管理、Self-Evolving Agents｜从经验学习到可控进化、Agentic Software Engineering｜从代码生成到软件交付、Personal Agent、AI 原生架构的演进与治理、AI 时代的组织重构、AI × Industries ｜产业智能化等 13 个专题论坛，届时将有来自不同行业、不同领域、不同企业的资深专家在现场带来前沿技术洞察和一线实践经验。
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When Agent actually enters the business process, which jobs can be given to AI?50 + the battle cases reveal the answer!
AI is moving from a question-and-answer support tool to an understanding of the goal, to a system, and to a duty bearer. When Agent actually enters the business process, the question is no longer “how to make AI”, but what work can be given to AI, how results are acceptance check, permission, how costs and risks are collected. With the extension of LLM to reasoning, tool call, multimodular and long missions, the development of the design of a shift in focus from a single call to context, tools, implementation environment and feedback loops, Coding Agent also evolved from a code completion to an engineering collaborator who understands the code library, runs tests, and completes complex tasks. Open AI, Google Cloud, Anthropic ' s latest practice points to one conclusion: the model determines what Agent can do, and the project determines whether it can actually enter production and create value.
In this context, the AICon Congress on Artificial Intelligence Development and Application, Beijing Station, was officially launched in 2026. The Congress will be held at the New Yunnan Crown Holiday Hotel in Beijing from 18 to 19 December. The Congress, which focused on exploring the A application boundary, set up 13 major technical topics covering the core directions of LLM post-training, reasoning optimization, Agent engineering, intellectual engineering, AI agent assessment and security, self-evolution systems, AI software delivery, native architecture and organizational change, bringing together first-line technical experts to share in depth the real practices of AI technological breakthroughs and enterprise size.
Dr. Kure, co-founder of SIMBOSS & CTO Pan Chengbin, has confirmed his participation in the theme “Organization Reconstruction of the AI Age” and has published a theme-sharing entitled “From Effectiveness to Empowerment: AI Capability Breaking and Organizational Evolution”. The impact of AI on small teams is extending from increasing the efficiency of existing jobs to expanding team competencies and member responsibilities. This sharing, combined with intelligent hardware connection operations, with eSIM LPAd and multi-platform SDK capacity-building as the technical context, discusses how teams can use AI to take on tasks that were hard to cover in the past and adjust roles and collaborative approaches accordingly.
This sharing will focus on two organizational cases: a test engineer who moves from quality control to client demand and project advancement, as well as products, research and development, and joint operations for pre-sales and client projects. Through these practices, discussions were held on how technical directors could provide members with the opportunity and support to clarify the boundaries of responsibility and to position the expansion of individual capabilities as a team ' s ability to solve client problems. At the same time, the presentation presents the difficult points that are still being explored to inform small teams in advancing AI applications and organizational adjustments.
Dr. Pan (SIMBOSS) CTO, responsible for technology direction, product development and team-building, promotes product and client projects around smart hardware connections, eSIM, endside SDK and global networking services. Focus on the practical application of AI in its role of R & D, products and operations, exploring how small teams can leverage AI to enhance outputs, build new capabilities such as multi-platform SDK and promote more direct involvement of professionals in client needs and project delivery. The practice focus includes technical and operational synergies, role development, delivery responsibility and reusable capacity-building.
His detailed presentation at this meeting reads as follows:
Outline of the presentation
1. What have we observed after the effect?
- AI Applications in R & D, products and operations
- From increased output to expanded scope of deliverables
- What new issues have been raised by changes in capacity regarding the division of former posts
2. Capacity breakthrough: eSIM LPAd and multi-platform SDK practice
- Gap between client needs and the original ability of the team
- AI Modalities for participation in programme exploration, realization and delivery preparation
- Professional judgement, certification and capacity of engineers
3. Role change: from testing engineer to client project manager
- How testing and quality experiences extend to demand understanding and project advancement
- From responsibility for professional aspects to the organization of multi-party projects
- How managers provide opportunities, mandates, support and feedback
- Capacity still to be developed in the new role and clear boundaries
4. Collaborative changes: products, R & D, operations towards clients
- The manner in which actors participate in pre-sales and projects
- How to collectively determine needs, feasibility, costs and operating conditions
- How phase leaders, professional leaders and sales collaborate
- Translating the experience of a client project into reusable capacity
5. Methodology refining: from individual to team capacity
- Identification of AI applications from real task
- Adapt the scope of work and modalities of collaboration to changes in capacity
- Synchronization of mechanisms for responsibility, validation and support
- Observation of the effects of using work outputs, re-use of capacity and client issues
Audience benefits
- To obtain a framework for distinguishing between AI effectiveness, competency expansion and organizational change that can address work outputs, competencies and client issues
- Obtaining ideas for translating the additional competencies of members into more complete work responsibilities, identifying the delegation of authority, support, validation and feedback mechanisms needed to move the role forward
- A collaborative approach to learning products, research and development, operational engagement with clients ' needs and project advancement, with clear phases of leadership, professional responsibility and business collaboration to promote personal capacity as a team capacity
In addition to this, the Congress planned Post-Training Engineering data, awards and modelling capability development, LLM reasoning and arithmetical scheduling practices, Knowridge Engineering to Agent to understand enterprises, Multi-Agent Systems, AI agent to assess and explore the reliability of production, Agent Security, permission and operational security, AgentOps| Enterprise Agent management, Self-Evolving Agents| From experience learning to manageable evolution, Agenic Software Engineering from code generation to software delivery, Personal Agent, the evolution and governance of the AI original architecture, the organization of the AI era, AI x Industries, industrial intelligence, etc., 13 thematic forums will bring forward technological insights and first-line practical experience from different industries, fields and firms.
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