未来工作：人工智能对劳动力的范式转变

欢迎收听《市场观点》节目，今天我们继续探讨人工智能应用的第二部分。我是摩根士丹利全球研究主管凯蒂·胡伯蒂。再次与我共同参与讨论的是主题研究全球主管史蒂文·伯德，以及摩根士丹利全公司人工智能负责人杰夫·麦克米兰。今天我们将聚焦人文层面，探讨这一范式转变对个体工作者的意义。现在是纽约时间11月5日周三上午10点。

Welcome to thoughts in the market and to part two of our conversation on AI adoption. I'm Katie Huberty, Morgan Stanley's global head of research. Once again, I'm joined by Steven Bird, global head of thematic research, and Jeff McMillan, Morgan Stanley's head of firm wide AI. Today, let's focus on the human level, what this paradigm shift means for individual workers. It's Wednesday, November 5 at 10AM in New York.

史蒂文，大众对AI普及既充满担忧又满怀期待。显然人们担心AI可能导致大规模失业。但你似乎对这种范式转变持乐观态度，这是为什么？

Steven, there's a lot of simultaneous fear and excitement around widespread AI adoption. There's obviously concern that AI could lead to massive job losses. But you seem optimistic about this paradigm shift. Why is that?

正如我在第一部分提到的，这是我和孩子们最常讨论的话题。应该说年轻人对此相当忧虑。年轻一代普遍存在焦虑，他们担心未来的就业市场会是什么样子？必须承认，AI可能带来巨大冲击，我们不想粉饰这一点。许多工作岗位显然都会受到影响。

As I mentioned in part one, this is the most popular discussion topic with my children. I I would say younger folks are quite concerned about this. There's a lot of angst, among young folks thinking about what is that job market really going to look like for them? And, admittedly, AI could be quite disruptive, so we don't wanna sugarcoat that. There's clearly going to be impacts across many jobs.

我们的研究表明约90%的工作岗位将在某种程度上受到影响。长期来看，我猜测几乎所有工作都会受到某种程度的影响。我们持乐观态度的原因在于，我们看到的是AI作为能力增强工具的一系列应用场景，它能帮助你更出色地完成工作，拓展能力边界，并催生全新职业。对于任何新技术，我们都很难准确预测会产生哪些新职业。

Our work showed that around 90% of jobs will be impacted in some way. Or in the long term, I would guess nearly every job will be impacted in some way. The reason we are more optimistic is that what we see is a range of what we would think of as augmentation, where AI can essentially help you do something much better. It can help you expand your capabilities, and and it will result in entirely new jobs. Now with any new technology, it's always hard to predict exactly what those new jobs are.

以我所在的能源领域为例，智能电网分析、预测性维护、更高效地管理系统——这些系统复杂到超出人类有效管理能力的范畴，都让我感到振奋。在生命科学领域更令我激动的是，我们可能找到治疗某些困扰人类最严重疾病的全新方法。对于这些新就业领域我充满期待。关于失业问题，我们在未来工作报告中纳入了一项投资者高度关注的分析指标：岗位中能力增强与自动化替代的比例关系。

But examples that I see in my world of of energy would be smart grid analysis, predictive maintenance, managing systems in a much more efficient way, systems that are so complicated that they're really beyond the capability of humans to manage very effectively. So I'm quite excited there. I'm extremely excited in the life sciences where we could see entire new approaches to curing some of the worst diseases plaguing humankind. So I am really very excited in terms of those new areas of job creation. In terms of job losses, one interesting analysis that a lot of investors are really focused on that we included in our future of work report was the ratio within a job of augmentation to automation.

这个比例越低，失业风险就越高，这意味着AI更可能替代这类人力工作。比如专业服务领域，我之前从事的法律行业就是典型例子。本质上，那些不需要大量专有数据、创造性要求较低的工作任务更容易被自动化取代。

The lower the ratio, the higher the risk of job loss in the sense that that shows a sign that more of what AI is gonna do is gonna replace that type of human work. Examples of that would be in professional services, as I mentioned, you know, one of my former professions, law, would be an example of an area where you could see this. But, essentially, tasks that don't require a lot of proprietary data, require less creativity, those are the types of tasks that are more likely to be automated.

我在硅谷和金融行业都听到一个共识观点：领域专长的价值正在提升。比如在法庭表现出色或能处理复杂案件的资深律师，他们的劳动价值和专业才能会愈发珍贵。所以当朋友问我该让孩子在学校选择什么专业、从事什么职业时，我的建议是：与其纠结具体职业，不如选择热爱领域并快速成为该领域的专家。

One theme I hear both in Silicon Valley and in our industry is the value of domain expertise goes up. So the lawyer that's very good in the courtroom or handling a really complicated situation because they have decades of experience, the value of that labor and talent goes up. And so when my friends ask me what their kids should pursue in school and as a career, I tell them it's less about what job they pursue, pick a passion, and become a domain expert really quickly.

我认为这是极好的建议。

I think that's excellent advice.

杰夫，你认为人工智能将如何改变摩根士丹利所需技能以及人们规划职业生涯的方式？

Jeff, how do you see AI changing the skills we'll need at Morgan Stanley and the way that people should think about their careers?

我认为需要从三个方面来分析，史蒂文刚才也略有提及。第一，必须关注那些可能消失的岗位；第二，必须关注那些即将发生变化的岗位；最后，必须关注这一现象中即将诞生的新岗位。你们现在就应该思考如何通过学习提示工程等技能，为转型到那些不会被淘汰的岗位做好准备。

I think you have to break this down into three pieces, and and Steven sort of alluded to it. One, you have to look at the jobs that are likely to disappear. Two, you have to look at the jobs that are going to change. And then finally, you have to look at the new jobs that are going to actually emerge from this phenomena. You should be thinking right now about how you are going to prepare yourself with the right skills around learning how to prompt and learning how to move into those functions that are not gonna be eliminated.

关于正在变化的岗位，它们将需要更强的协作能力和创造力。而提示工程正是其中的核心技能，我强烈建议每位听众都努力成为所在团队、朋友圈或组织中最优秀的提示工程师。至于新创造的岗位，我其实相当乐观。随着智能代理的发展，我们甚至可能因为创造出过于复杂的环境而需要更多人力来管理。

In terms of jobs that are changing, they're gonna require a far, far greater sense of collaboration, creativity. And, again, prompting, prompt engineering is sort of the center of that, and I would highly encourage every single person who's listening to this to become the single best prompt engineer in their group, in their friend, in their in their organization. And then in terms of the jobs that are getting created, I'm actually pretty optimistic here. As we build agents. There's actually a bull case that we're gonna create so much complexity in our environment that we're gonna need more people to help manage that.

但这些技能绝非重复性的线性技能，它们将需要实时决策能力、领导力和协作能力。不过我还是想重申：每个人都应该学会与机器对话，培养创造力，并每天练习与这项技术互动。

But the skills are not gonna be repetitive linear skills. They're gonna require real time decision making, leadership skills, collaboration skills. But, again, I would go back to every single person. Learn how to talk to the machine. Learn how to be creative and practice every day your engagement with this technology.

那么企业该如何平衡技能重塑与任何新范式都不可避免带来的文化转变呢？

So then how are companies balancing the reskilling with the inevitable culture shifts that come with any new paradigm?

首先，如果你只把这视为工具，那已经偏离重点了。第一要务是明确自身战略——无论什么战略，AI都只是战略的赋能工具。第二点是从高层开始传递明确信息：变革已至，它至关重要且必须被接纳。

So so first of all, I think if you think about this as a tool, you've already lost the plot. I I think that, number one, you have to remind yourself what your strategy is. Whatever that strategy is, this is an enabler of your strategy. The second point I'd make is that you have to go from both the top down in terms of leadership messaging that this change is here. It's important, and it needs to be embraced.

这是一种自下而上的过程，因为你需要用正确的工具和技术赋能员工，让他们自主革新工作方式。如果只是强硬地告诉人们必须遵循某条路径，就无法获得真正的认同。我们真正要做的是让人们能充分利用这些工具。最让我兴奋的是当员工走进办公室说：‘嘿杰夫，给你看看我今天做的东西。’

And then it's a bottoms up because you have to empower people with the right tools and the technology to transform their own work. Because if you're trying to tell people that this is the path that they have to follow, you don't get the buy in that you need. You really want to empower people to leverage these tools. And what excites me most is when people walk into my office and say, hey, Jeff. Let me show you what I built today.

对方可能只是个刚入职一个月的22岁年轻人。这项技术最激动人心之处在于——你不需要技术背景，只需要足够聪明、富有创造力。只要具备这些特质，你就能打造出真正创新的东西。

And it could be some 22 year old who it's their first month on the job. And what's exciting about this technology is you do not need a technology background. You need to be smart. You need to be creative. And if you've got those skills, you can build things that are really innovative.

我认为这才是最精彩的部分。如果能将‘自上而下’的战略重要性与‘自下而上’的技能赋能、技术支持和动机激励相结合，这就是成功的秘诀。

And I think that's what's exciting. So if you can combine the top down that this is important and the bottoms up with giving people the skills and the the technology and the motivation, that's the secret sauce.

杰夫，对于正在思考如何在这个环境中开启职业生涯的下一代大学生和应届毕业生，你有什么建议？

Jeff, what's your advice for the next generation, college students, recent college graduates, as they're thinking about navigating the early parts of their career in this environment?

凯蒂，首先我认同你的观点。所有人都在问‘我该学什么？’老实说我不知道标准答案，但我建议学习你真正关心的领域，选择让你充满热情的事业。第二点虽然老生常谈——但我会努力成为你们学校最精通生成式AI的人。

Well, Katie, first of all, agree with what you say. Everyone's like, what should I study? And the answer is I don't actually know the answer to that question, but I would study what you care about. I would do something that you're passionate about. And the second point, and I I hate to be a broken record on this, but I would be the single best user of generative AI at your college.

可以参与非营利组织志愿工作，或和朋友一起开发应用案例。当你参加第一份工作的面试时，要展现出你能够高效运用这项技术的能力——这将成为你职场首秀的制胜法宝。

Volunteer with some nonprofit, build a use case with your friends. When you walk into your first job, impress in your interview that you are able to use this technology in really effective ways because that will make a difference in your first job.

我很好奇，在金融服务或其他行业中，你认为哪些领域是人类永远能胜过AI的？

And I'm curious. Are there areas where you think humans will always beat AI, whether it's in financial services or other industries?

我认为我们作为人类，拥有建立信任和情感关系的能力。这不仅让我们比机器更擅长于此，也是人类永恒的追求。虽然社会中可能有人持不同观点，但总体而言，人与人之间的关系至关重要，我相信这将在未来很长一段时间里成为我们的独特优势。凯蒂，作为全球研究负责人，生成式AI如何改变了研究工作的方式？

I like to think that we are human, and that gives us the ability to build trust and emotional relationships. And I think not only are we gonna be better at that than machines are, but I think that's something that we as humans will always want. I think that there there may be some individuals in the society that that may feel differently. But I think as a general rule, the human to human relationship is something that's really important, and I like to think that it will be a differentiator for a long time to come. So, Katie, from where you sit as the head of global research, how has GenAI changed the way research is being done?

在你们团队的协助下，杰夫，我们已将AI融入研究全周期：从假设验证、数据分析到高效撰写报告，贯穿出版流程，最终用客户当地语言生成分析师风格的数字内容。目前我们正在开发客户互动工具，用以优化研究团队的时间分配。这显著缩短了将阿尔法生成理念推向市场的周期，同时为团队释放了更多时间。

With the help of of your team, Jeff, we have now embedded AI through the life cycle of investigating a hypothesis, doing the analysis, writing the research in a concise, effective way, pushing that through our publishing process, developing digital content in our analyst voice in the local language of the client. And now we're working on a client engagement tool that helps direct our research team's time. And so the impact here is it reduces the time to market to get an alpha generating idea to our clients, and it's freeing up time for our teams.

凯蒂，我想进一步探讨。生产力是个重要议题。抛开研究本身，从管理角度看，你们团队如何运用AI？看到了哪些效益？又是如何利用AI节省出来的时间？

So Katie, I want to build on that. Productivity is a big theme. And away from the research itself, from a management perspective, how are you and your team using AI, and what do you see as the benefits, and how are you spending the extra time that's freed up by AI?

我认为研究AI战略的核心不在于工具本身——虽然工具确实关键且基础——而在于工作流程的革新和团队时间的重新分配。节省的时间正被投入到你们负责的主题研究领域，这类研究需要更多协调协作、全球跨资产视角，从假设开发测试到内部辩论直至报告发布，整个过程耗时更长。

I like to say that the research AI strategy is less about the tools. I mean, those are critical and foundational. But it's more about how we're evolving workflow and how our teams are spending time. And so the savings are being reinvested in actually your area, thematic research, which takes a lot more coordination, collaboration, a global cross asset view. It just takes more time to develop and test a hypothesis and debate internally and get those reports to market.

但这对我们帮助客户创造阿尔法的核心战略至关重要。回顾过去三十年的股票市场，极少数股票贡献了全部阿尔法收益，而这些股票往往与特定主题相关。因此我们正将时间投入到提前识别这些主题上，帮助客户捕捉阿尔法。另一方面，分析师团队约25%的时间用于客户沟通，因为他们需要与行业专家会面并进行深度分析。

But it's critical for our core strategy, which is to help our clients generate alpha. When you look at equity markets over the past thirty years, a very small number of stocks drive all of the alpha, and they tend to link to themes. And so we're reinvesting time in identifying those themes earlier than the market to allow our clients to capture that alpha. And then the other piece is when we look at our analyst teams, they spend about a quarter of their time with clients because they have to meet with experts in the industry. They need to do the analysis.

他们还要构建财务预测、管理团队、参与内部文化建设。借助这些工具加速部分任务后，我们预计分析师与客户的互动时间可翻倍。当我们向市场推出发人深省的全球协作主题内容时，客户会更愿意与我们深入交流——这才是最根本的个人层面影响。

They have to build the financial forecast, manage their teams. We have internal activities, build culture. And with the ability to leverage these tools to speed up some of those tasks, we think we can double the amount of time that our analysts are spending with clients. And if we're putting thought provoking, you know, often thematic global collaborative content into the market, our clients wanna spend more time with us. And so that's the ultimate impact on a personal level.

我想二位都有体会。当前释放的时间主要用于紧跟AI领域的快速变革，追踪最新技术和供应商。但长远来看，我希望这些时间能用于更人性化的个人活动：学习艺术、保持活力。如果我们把时间再投资到既有商业影响力、又能丰富职场外生活的活动中，这将对社会产生深远益处。总结来看，AI的影响力正快速扩展，不仅限于数字和知识领域，更日益渗透到现实世界的方方面面。

And I think both of you can relate. I think a lot of the freed up time right now is just following the fast pace of of change in AI and keeping up with the latest technology, the latest vendors. But long term, my hope is that this frees up time for more human activities on a personal level, learning the arts, staying active. So this could be potentially very beneficial to society if we reinvest that time in both productive activities that have impact in business, but also productive rewarding activities outside of the office. As we wrap up, it's clear that the influence of AI is expanding rapidly, not just in digital and knowledge based sectors, but increasingly intangible real world applications.

随着这些创新的发展，我们与技术及环境互动的方式将持续演变，无论是在工作中还是生活的其他方面。杰夫、史蒂文，感谢两位分享见解。也感谢听众朋友们的参与。如果您喜欢本期节目，请在收听平台留下评价，并与朋友同事分享您对市场的看法。

As these innovations unfold, the way we interact with both technology and our environments will continue to evolve, both on the job and elsewhere in our lives. Jeff, Steven, thank you both for sharing your insights. And to our listeners, thank you for joining us. If you enjoy the show, please leave us a review wherever you listen and share thoughts on the market with a friend and colleague today.

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