AndrewYNg发表了一篇twitter，讲述AI对工作的冲击，我感觉说的很不错。
文章分为如下部分
第一部分：我的总结
第二部分：更有兴趣的可以去看下原文
第三部分：更更有兴趣的可以去看下英文原文，也很简洁易懂
我的总结
核心结论：AI不会直接大规模取代工作，但会使用AI的人会取代不会使用AI的人。现在正是学习AI技能的最佳时机。
总结一、当前就业市场的真实情况
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裁员的真正原因
- 科技公司裁员主要是疫情期间过度招聘的纠正和常规重组
- 真正因AI自动化导致的裁员极少
- 大规模失业的担忧被过度炒作
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受AI影响较大的职业
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呼叫中心操作员、翻译、配音演员等高暴露职业面临压力
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但这只是少数特定领域，不是普遍现象
总结二、AI正在改变招聘标准
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技术岗位的转变
- 会用AI编码工具的开发人员需求激增
- AI提升了个人效率，团队规模随之缩小
- 例：过去8个工程师+1个PM的项目，现在可能只需2个工程师+1个PM
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非技术岗位的新要求
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市场营销、招聘、分析等传统非技术岗位也在转变
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懂得用AI编程的从业者生产力更高
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不适应AI的员工正被逐步替换
总结三、机遇大于挑战
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企业的实际需求
- 大多数企业工作量大、人手不足
- 掌握AI技能的人有更多承担重要工作的机会
- 许多积压的项目因AI提效而得以推进
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为什么现在是最佳时机
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绝大多数人（无论技术或非技术背景）都刚刚起步
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大家基本在同一起跑线上
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持续学习和实践的人将获得大量机会
对普通人的行动建议
现在就开始学习AI技能——无论你是技术人员还是非技术人员，掌握AI工具的使用将成为未来职场的核心竞争力。
文章原文
美国和许多其他国家的求职者正面临着严峻的就业环境。与此同时,人们对AI导致失业的担忧——到目前为止——被过度夸大了。然而,对AI技能的需求正开始引发就业市场的转变。我想分享一下我在实际工作中观察到的情况。
首先,许多科技公司在过去一年里裁减了员工。虽然一些CEO将AI作为裁员理由——认为AI正在完成工作,所以不再需要人——但现实是AI目前还没有那么好用。许多裁员实际上是对疫情期间过度招聘的纠正,或是即使在现代AI出现之前也偶尔会发生的常规成本削减和重组。除了少数几个岗位,很少有裁员是因为工作被AI自动化了。
诚然,这种情况未来可能会增加。目前在一些高度暴露于AI自动化风险的职业中工作的人,比如呼叫中心操作员、翻译人员和配音演员,可能会在求职时遇到困难,或者工资下降。但大规模失业的说法被过度炒作了。
相反,一个常见的说法更准确:AI不会取代工人,但会使用AI的工人会取代不会使用AI的工人。例如,由于AI编码工具使开发人员的效率大大提高,懂得如何使用这些工具的开发人员需求日益增长。(如果你想成为这样的人,请学习我们关于Claude Code、Gemini CLI和Agentic Skills的短期课程!)
所以AI确实在导致失业,但方式比较微妙。一些企业正在让那些不适应AI的员工离职,并用能够适应的人取而代之。这一趋势在软件开发领域已经很明显了。此外,在许多初创公司的招聘模式中,我看到了这种人员更替在传统上被认为是非技术岗位中的早期迹象。懂得如何用AI编程的市场营销人员、招聘人员和分析师比不懂的人更有生产力,因此一些企业正在慢慢与无法适应的员工分道扬镳。我预计这一趋势会加速。
同时,当企业建立AI原生的新团队时,有时新团队比它们取代的团队规模更小。AI使个人更有效率,这使得缩小团队规模成为可能。例如,随着AI使软件开发变得更容易,瓶颈正在转向决定构建什么——这就是产品管理(PM)瓶颈。一个过去需要分配给8名工程师和1名PM的项目,现在可能只需要2名工程师和1名PM,甚至可能只需要一个同时具备工程和产品技能的人。
对员工来说,好消息是大多数企业有很多工作要做,却没有足够的人手。拥有合适AI技能的人通常会获得机会去承担更多工作,也许还能处理那些在AI让工作进展更快之前无法执行的积压创意。我看到许多企业中的许多员工正在挺身而出,构建帮助其业务的新事物。机会比比皆是!
我知道这些变化令人焦虑。我的心与每一个受到裁员影响的家庭同在,与每一个努力寻找理想职位的求职者同在,也与更多担心未来就业前景的人同在。幸运的是,现在还有时间学习并为就业市场的发展方向做好准备。在AI方面,绝大多数人,无论是技术人员还是非技术人员,都还在起跑线上,或者说他们最近才起步。所以现在仍然是持续学习和持续构建的绝佳时机,对于那些这样做的人来说,机会是无数的!
原帖子地址：x.com/andrewyng/s…
英文原文
Job seekers in the U.S. and many other nations face a tough environment. At the same time, fears of AI-caused job loss have — so far — been overblown. However, the demand for AI skills is starting to cause shifts in the job market. I’d like to share what I’m seeing on the ground.
First, many tech companies have laid off workers over the past year. While some CEOs cited AI as the reason — that AI is doing the work, so people are no longer needed — the reality is AI just doesn’t work that well yet. Many of the layoffs have been corrections for overhiring during the pandemic or general cost-cutting and reorganization that occasionally happened even before modern AI. Outside of a handful of roles, few layoffs have resulted from jobs being automated by AI.
Granted, this may grow in the future. People who are currently in some professions that are highly exposed to AI automation, such as call-center operators, translators, and voice actors, are likely to struggle to find jobs and/or see declining salaries. But widespread job losses have been overhyped.
Instead, a common refrain applies: AI won’t replace workers, but workers who use AI will replace workers who don’t. For instance, because AI coding tools make developers much more efficient, developers who know how to use them are increasingly in-demand. (If you want to be one of these people, please take our short courses on Claude Code, Gemini CLI, and Agentic Skills!)
So AI is leading to job losses, but in a subtle way. Some businesses are letting go of employees who are not adapting to AI and replacing them with people who are. This trend is already obvious in software development. Further, in many startups’ hiring patterns, I am seeing early signs of this type of personnel replacement in roles that traditionally are considered non-technical. Marketers, recruiters, and analysts who know how to code with AI are more productive than those who don’t, so some businesses are slowly parting ways with employees that aren’t able to adapt. I expect this will accelerate.
At the same time, when companies build new teams that are AI native, sometimes the new teams are smaller than the ones they replace. AI makes individuals more effective, and this makes it possible to shrink team sizes. For example, as AI has made building software easier, the bottleneck is shifting to deciding what to build — this is the Product Management (PM) bottleneck. A project that used to be assigned to 8 engineers and 1 PM might now be assigned to 2 engineers and 1 PM, or perhaps even to a single person with a mix of engineering and product skills.
The good news for employees is that most businesses have a lot of work to do and not enough people to do it. People with the right AI skills are often given opportunities to step up and do more, and maybe tackle the long backlog of ideas that couldn’t be executed before AI made the work go more quickly. I’m seeing many employees in many businesses step up to build new things that help their business. Opportunities abound!
I know these changes are stressful. My heart goes out to every family that has been affected by a layoff, to every job seeker struggling to find the role they want, and to the far larger number of people who are worried about their future job prospects. Fortunately, there’s still time to learn and position yourself well for where the job market is going. When it comes to AI, the vast majority of people, technical or nontechnical, are at the starting line, or they were recently. So this remains a great time to keep learning and keep building, and the opportunities for those who do are numerous!
