
平庸的组织架构,很少被视为阻碍创新的罪魁祸首。但领英(LinkedIn)高管阿尼什·拉曼认为,随着企业纷纷推动员工应用AI,这些定义大多数职场关系的结构体系,恰恰成了创新的掣肘。
拉曼表示:“组织架构图诞生于工业时代,其目的是为快速扩张的组织带来秩序、可预测性和稳定性。企业需要摆脱这种模式,因为它将阻碍创新。”拉曼目前担任领英首席经济机会官,并与他人合著了一本探讨未来工作的书。
拉曼认为,高管们与其等待自上而下的转型项目,不如学会放权,让员工在实践中自行探索AI的使用方式,即便这些尝试会打破部门壁垒、跨越岗位职责也无妨。他表示:“真正能够释放AI价值的,不只是围绕AI重构流程,而是围绕人的能力,创造新的工作模式。”
拉曼曾任CNN战地记者,并担任奥巴马总统的演讲撰稿人。他与领英首席执行官瑞安·罗斯兰斯基合著了《开放工作:AI时代如何脱颖而出》(Open to Work: How to Get Ahead in the Age of AI)一书。该书基于领英数据和早期AI采用者案例,总结出一套他称为“人类如何与AI协作”的行动指南,旨在打破当前围绕AI对就业影响的“宿命论”论调。

他建议员工将自身工作以及与AI的关系分为三类。第一类涵盖AI已经能够胜任的任务,例如生成代码、进行快速分析,或撰写初稿以激发创作灵感。第二类是借助AI创造新事物的探索性尝试。第三类则是结合第一类节省下来的时间和第二类积累的经验,让AI在团队层面发挥作用。他问道:“关键在于,你正在与同事一起做什么?”
拉曼表示:“这将是一场由员工主导的转型,因此企业需要思考如何赋能个体,让他们在日常工作中平稳过渡到这一新时代。在重塑工作模式、追求卓越产出方面,我们拥有的自主权往往超乎想象。”
AI时代,哪些技能更胜一筹?
领英正推动招聘与用工模式向“以技能为先”转型。理论上,企业在招聘时更关注具体技能和能力,以及应聘者具备这些技能的证明,而非只看简历上的一串职位头衔。与此同时,领英也在将AI整合进自身产品,例如推出用于辅助招聘的新AI智能体。
不过,随着AI实现知识型工作自动化的能力不断提升,员工究竟需要具备哪些技能,仍存在不确定性。以编程为例,过去十多年间,高校与政策制定者一直告诉年轻人,“学会编程”是通往高薪职业的最稳妥途径。但在“氛围式编程”时代,这一判断开始动摇。Claude的开发公司Anthropic认为,在当前及未来可能被AI覆盖的职业中,计算机与数学相关职业首当其冲。
拉曼并不认为计算机科学已经过时。相反,企业需要重新审视计算机科学等学位所培养的更广泛技能。他指出,“计算机科学学位不仅仅教授编程,它还培养复杂思维、组织设计以及系统结构等能力。”
至少在美国,员工并不确信自己能从中受益。CBS News上周发布的一项调查显示,三分之二的美国人认为AI将减少就业岗位;比例相近的受访者也不相信科技公司会以妥当的方式使用AI。
相比之下,AI在亚洲或许更容易普及,当地人群对这一技术的接受度更高。皮尤研究中心(Pew Research Center)去年10月的一项调查显示,亚洲受访者的担忧程度整体低于西方。例如,在皮尤调查覆盖的25个国家中,仅有16%的韩国受访者表示对AI“担忧多于兴奋”,为最低水平;而美国占比最高,这一比例达到50%。
最近,中国消费者纷纷在设备上安装开源AI代理框架OpenClaw,各地政府也竞相支持“单人公司”——即借助AI开发新产品的创业项目。
拉曼表示:“在亚洲,无论是企业还是员工,都渴望学习并应用这些工具。许多亚洲国家本身就具备浓厚的创业文化。”
是时候顺势而为了
不过,拉曼也理解员工对自动化的担忧。他表示:“过去存在一条清晰的职业晋升阶梯,要登上每一级阶梯需要做什么,路径都极为清晰。”
但他仍然保持乐观。在他看来,随着AI逐步打破企业传统的组织方式与激励机制,员工最终反而会从中受益。他表示:“真正能够掌控自己职业路径的人少之又少。但在AI的推动下,未来的职场人,可能将比以往任何一代都拥有更强的掌控力。”
但如果有人并不想在工作中成为创新者呢?如果有人只想各司其职,获得一份稳定收入呢?
拉曼对这些人的回答很直接:“没有人会来拯救你,除了你自己。”
无论你喜欢与否,变革即将到来。他表示:“问题只在于,这种变革何时会降临到你身上,以及冲击会有多大。”(财富中文网)
译者:刘进龙
审校:汪皓
平庸的组织架构,很少被视为阻碍创新的罪魁祸首。但领英(LinkedIn)高管阿尼什·拉曼认为,随着企业纷纷推动员工应用AI,这些定义大多数职场关系的结构体系,恰恰成了创新的掣肘。
拉曼表示:“组织架构图诞生于工业时代,其目的是为快速扩张的组织带来秩序、可预测性和稳定性。企业需要摆脱这种模式,因为它将阻碍创新。”拉曼目前担任领英首席经济机会官,并与他人合著了一本探讨未来工作的书。
拉曼认为,高管们与其等待自上而下的转型项目,不如学会放权,让员工在实践中自行探索AI的使用方式,即便这些尝试会打破部门壁垒、跨越岗位职责也无妨。他表示:“真正能够释放AI价值的,不只是围绕AI重构流程,而是围绕人的能力,创造新的工作模式。”
拉曼曾任CNN战地记者,并担任奥巴马总统的演讲撰稿人。他与领英首席执行官瑞安·罗斯兰斯基合著了《开放工作:AI时代如何脱颖而出》(Open to Work: How to Get Ahead in the Age of AI)一书。该书基于领英数据和早期AI采用者案例,总结出一套他称为“人类如何与AI协作”的行动指南,旨在打破当前围绕AI对就业影响的“宿命论”论调。
他建议员工将自身工作以及与AI的关系分为三类。第一类涵盖AI已经能够胜任的任务,例如生成代码、进行快速分析,或撰写初稿以激发创作灵感。第二类是借助AI创造新事物的探索性尝试。第三类则是结合第一类节省下来的时间和第二类积累的经验,让AI在团队层面发挥作用。他问道:“关键在于,你正在与同事一起做什么?”
拉曼表示:“这将是一场由员工主导的转型,因此企业需要思考如何赋能个体,让他们在日常工作中平稳过渡到这一新时代。在重塑工作模式、追求卓越产出方面,我们拥有的自主权往往超乎想象。”
AI时代,哪些技能更胜一筹?
领英正推动招聘与用工模式向“以技能为先”转型。理论上,企业在招聘时更关注具体技能和能力,以及应聘者具备这些技能的证明,而非只看简历上的一串职位头衔。与此同时,领英也在将AI整合进自身产品,例如推出用于辅助招聘的新AI智能体。
不过,随着AI实现知识型工作自动化的能力不断提升,员工究竟需要具备哪些技能,仍存在不确定性。以编程为例,过去十多年间,高校与政策制定者一直告诉年轻人,“学会编程”是通往高薪职业的最稳妥途径。但在“氛围式编程”时代,这一判断开始动摇。Claude的开发公司Anthropic认为,在当前及未来可能被AI覆盖的职业中,计算机与数学相关职业首当其冲。
拉曼并不认为计算机科学已经过时。相反,企业需要重新审视计算机科学等学位所培养的更广泛技能。他指出,“计算机科学学位不仅仅教授编程,它还培养复杂思维、组织设计以及系统结构等能力。”
至少在美国,员工并不确信自己能从中受益。CBS News上周发布的一项调查显示,三分之二的美国人认为AI将减少就业岗位;比例相近的受访者也不相信科技公司会以妥当的方式使用AI。
相比之下,AI在亚洲或许更容易普及,当地人群对这一技术的接受度更高。皮尤研究中心(Pew Research Center)去年10月的一项调查显示,亚洲受访者的担忧程度整体低于西方。例如,在皮尤调查覆盖的25个国家中,仅有16%的韩国受访者表示对AI“担忧多于兴奋”,为最低水平;而美国占比最高,这一比例达到50%。
最近,中国消费者纷纷在设备上安装开源AI代理框架OpenClaw,各地政府也竞相支持“单人公司”——即借助AI开发新产品的创业项目。
拉曼表示:“在亚洲,无论是企业还是员工,都渴望学习并应用这些工具。许多亚洲国家本身就具备浓厚的创业文化。”
是时候顺势而为了
不过,拉曼也理解员工对自动化的担忧。他表示:“过去存在一条清晰的职业晋升阶梯,要登上每一级阶梯需要做什么,路径都极为清晰。”
但他仍然保持乐观。在他看来,随着AI逐步打破企业传统的组织方式与激励机制,员工最终反而会从中受益。他表示:“真正能够掌控自己职业路径的人少之又少。但在AI的推动下,未来的职场人,可能将比以往任何一代都拥有更强的掌控力。”
但如果有人并不想在工作中成为创新者呢?如果有人只想各司其职,获得一份稳定收入呢?
拉曼对这些人的回答很直接:“没有人会来拯救你,除了你自己。”
无论你喜欢与否,变革即将到来。他表示:“问题只在于,这种变革何时会降临到你身上,以及冲击会有多大。”(财富中文网)
译者:刘进龙
审校:汪皓
The humble org chart isn’t usually blamed for holding back innovation. But as companies push their employees to adopt AI, LinkedIn executive Aneesh Raman thinks the relationships that structure most workplaces are what’s holding things back.
“The org chart was built in the industrial age to bring order, predictability, and stability to rapidly growing organizations,” says Raman, LinkedIn’s chief economic opportunity officer and coauthor of a new book on the future of work. “Companies need to let that go, as it’s going to hold back innovation.”
Instead of waiting for top-down transformation programs, Raman argues, executives will need to get comfortable with workers figuring out AI on their own, even if those experiments cut across departments and job descriptions. “Where you’re going to see the real returns on AI isn’t just a new workflow around AI, but rather new work around human capability,” he says.
Raman, a former CNN war correspondent and Obama speechwriter, is the coauthor of Open to Work: How to Get Ahead in the Age of AI, alongside LinkedIn CEO Ryan Roslansky. The book draws on LinkedIn data and case studies of early adopters to offer what he calls a “how-to-human-with-AI” playbook that tries to counter the “fatalism” dominating most conversations about AI’s effect on employment.
He urges workers to think about their work, and how AI relates to it, in three categories. The first bucket covers activities AI already does today, like generating code, running quick analyses, or writing a first draft to inspire someone else’s writing. The second bucket are experiments to create something new with AI. The final bucket involves using the time saved from the first bucket, and the lessons learned from the second bucket, to start using AI as a group. “What are you doing with other people?” he asks.
“It’s going to be a worker-led transition, and so companies are going to have to figure out how to let individuals start to move into this new era in their day-to-day work,” Raman says. “We have more autonomy than we often think in terms of pushing for what we want to do that might push our work to the next level.”
What skills will matter in the AI workforce?
LinkedIn is in the middle of a pivot to what it calls a “skills-first approach” to hiring and employment. In theory, employers are looking for specific skills and capabilities—and proof that potential hires have those skills—instead of just looking at a list of job titles on a résumé. LinkedIn is also integrating AI into its own product, such as a new AI agent to help with hiring.
But as AI’s capacity to automate knowledge work grows, there’s still confusion over what skills employees will need. Take coding: For more than a decade, universities and policymakers told young people that learning to code was the surest path to a high-paying job. That advice looks less certain in the age of “vibe coding”: Claude developer Anthropic now sees computer and math careers as leading the way in terms of current and possible coverage by AI.
Raman, for his part, thinks computer science isn’t obsolete. Instead, employers need to look at the broader skills a degree like computer science provides. “A computer science degree doesn’t just teach coding alone. It teaches complex thinking, organizational design, and structures of systems,” he points out.
Workers, at least in the U.S., aren’t convinced they will come out ahead. A CBS News poll released last week reported that two-thirds of Americans believe AI will decrease the number of jobs; around the same share don’t believe that tech companies will use AI in appropriate ways.
AI could get more traction in Asia, where populations are more comfortable with the technology. A Pew Research Center survey from October found lower rates of concern among Asia-based respondents than Western ones. For example, just 16% of South Koreans reported being “more concerned than excited” about AI, the lowest share among the 25 countries Pew surveyed; the U.S., in contrast, had the highest share, with 50% reporting concern.
More recently, Chinese consumers have flocked to install OpenClaw, the open-source AI agent framework, on their devices, and local governments are rushing to support “one-person companies,” or AI startups trying to build new products.
“There’s a hunger in Asia, not just among companies but also among workers, to learn about these tools and put them to use,” Raman says. “There’s an entrepreneurial culture in a lot of countries in Asia.”
Time to adapt
Still, Raman is sympathetic to workers concerned about automation. “There was a career ladder, and there was extreme clarity about what you had to do to get on each rung of that ladder,” he says.
But he’s optimistic that, ultimately, employees will be better off as AI starts to dismantle the ways companies traditionally organize and reward their talent. “Very few people have ever had real control over their career,” he says. “Because of AI, I think we’re about to have the first generations at work that have more control over their career than any who’ve come before.”
But what if someone doesn’t want to be an innovator at their job? What if someone wants to maintain their responsibilities and earn a stable wage?
Raman’s answer to those people is direct: “Nobody is coming to save any individual but themselves.”
Change is coming, like it or not. “It’s just a question of when this change hits you, and how hard it hits you,” he says.