大家好，我是喜欢研究AI的一枚产品经理，平时主要从事新能源汽车智能座舱、AI大模型应用等相关工作。另外，我超爱自驾游~

导语：

“我们的聊天机器人出演了三部好莱坞电影和两部电视剧”。

“是时候聘请一位AI人工智能产品经理了”。

01 | AI时代，软件工程师：产品经理的对比正在发生变化。

先问大家一个问题：你们知道2023年之前，互联网大厂中，软件工程师：产品经理的比例大概是多少吗？

答案：大概是6:1或5:1这样。

可能很多人不以为然，这个数据是对于已成规模的一些互联网公司的统计结果。比如，字节跳动AILab：工程师：产品经理比例为5:1，并且从2023年后调整为最新的3:1。

（大家不要太过于纠结数据，重在看待和思考这个趋势变化）

所以大家想一想，为什么会出现这种岗位比例的变化呢？为什么又是从2023年开始的呢？

相信这个问题并不难，显然2023年是AI的一个分水岭，以GPT为代表的AI大模型和toC产品，第一次让C端用户切实感受到了一种真智能化的体验。紧接着2024年，国产化大模型+AI产品遍地开花，其中以大家熟知的豆包、KIMI、DeepSeek等为典型代表。

而这，其实还只是AI技术发展的萌芽阶段，AI的发展方向、应用前景、商业模式等等，这一系列变革才刚开始，所有人都是起步和摸索阶段。AI应用绝不是AI类产品的最终形态，比如Manus为代表的AI智能体，在解决更深层和复杂业务上，更具实用性和专业性。

AI未来的产品形态和应用场景，一定是多样化的，也一定是通用型和专业型，以及定制化兼备的。与当年移动互联网不同，当年是互联网+万物，而AI时代的全面落地，第一阶段最大的可能性是基于现有业务，实现万物+AI。

当年移动互联网是基建的升级，基于4G为代表的移动互联网，催生出了多种形态的软件服务，比如短视频，以及与实体产业相结合的新兴产业，比如外卖、网约车等。

而如今的AI还没有发展到基建的程度，它目前阶段还只是技术的变革，所以第一个阶段，它一定是在现在业务上进行赋能。当然，也不排除会衍生出一些全新形态的产品。只不过，基于AI的全面爆发阶段，还在后面，所以，这一次AI带来的产业变革，一定是长远且深远的，但又是有序的。

因此，现阶段，当一项新技术即将带来全产业的更新和变革时，最需要的就是有想法产品经理们冲锋陷阵，打头阵！先占城池，占坑位，然后再不断调整和扩充队伍，打造护城河，该坚守的坚守，该攻坚的继续攻坚。

因此，接下来几年时间，随着现有产业，尤其是互联网产业的“青黄不接”。我们急需“引爆”另一场产业变革，来打破僵局。这个不仅仅是我们的问题，也是全世界大厂共同面临的问题。

想必大家还记得，前几年全世界大厂都在炒的元宇宙、AR等概念和技术，其实也是因为现有技术和产业遇到了发展瓶颈，而急需寻找新的突破点和业务增长点。

大家试来试去，终于发现还是AI靠谱，而且从去年开始，AI的技术成熟度，应用可靠性已经达到了可商用的程度。那么接下来，就看各个企业如何面对和运用AI，来给自己赋能，做转型或升级了。

02 | 为什么我说AI产品经理将成为热门和必需品？

大家是否只有有一个经济学原理，就是两种互补的商品，当其中一个出现成本大幅下降时，另一个商品的需求也一定会相应的呈现出快速增长的态势。

举个例子。

燃油车和汽油就是两个互补产品，我们排除新能源汽车的因素，随着燃油车的价格不断下探，能买得起车的人越来越多，从开始的一家一人，变成了一家多车。这样，自然而然对于汽车的需求就越来越多了，对吧。

说回到AI领域，随着AI能力的增强，通过AI设计原型、AI画图、AI编程等智能化和自动化程度越来越高，其使用门槛越来越低，并且可用性越来越高，那么与之相关的产品经理岗位则一定会出现需求的扩张。

因为在AI出现之前，可能你有一个想法，但是受限于当时技术成本而无法落实，那现在这个成本已经大幅降低了，可能只要一个产品经理就能搞定从需求到设计，再到编码的全过程了。至少可以很低成本的先落地一个MVP产品，快速投入市场进行测试验证了。

所以这时候，产品经理，尤其是懂技术，且懂AI技术的产品经理，一定会热门。因为他们除了有想法外，再有点技术和动手能力，再加上AI带来的技术平权，对于很多小团队小公司来说，这不仅仅是人力资源的降低，与此同时还提高了生产效率。所以，AI产品经理的需求度和含金量，未来几年，一定会越来越高。

03 | AI Product Managers Will Be In-Demand

对于AI智能产品经理的发展前景，我并不是自说自话，就在年初，AI领域的大神吴恩达，他的履历太强了，我就不多说了。反正他曾带队负责百度大脑的建设，是在线教育平台Coursera的联合创始人，DeepLearning.AI创始人，等等。

吴恩达博士就是今年年初发表了一份公开信，信中表达的就是随着AI时代的到来，随着AI带来的技术平权，AI产品经理的需求将“井喷”。

不废话，下面就是吴恩达博士的原文，感兴趣的朋友可以阅读感受一下，来自AI领域最强领头人的呼吁。

Dear friends,

Writing software, especially prototypes, is becoming cheaper. This will lead to increased demand for people who can decide what to build. AI Product Management has a bright future!

Software is often written by teams that comprise Product Managers (PMs), who decide what to build (such as what features to implement for what users) and Software Developers, who write the code to build the product. Economics shows that when two goods are complements — such as cars (with internal-combustion engines) and gasoline — falling prices in one leads to higher demand for the other. For example, as cars became cheaper, more people bought them, which led to increased demand for gas. Something similar will happen in software. Given a clear specification for what to build, AI is making the building itself much faster and cheaper. This will significantly increase demand for people who can come up with clear specs for valuable things to build.

This is why I’m excited about the future of Product Management, the discipline of developing and managing software products. I’m especially excited about the future of AI Product Management, the discipline of developing and managing AI software products.

Many companies have an Engineer:PM ratio of, say, 6:1. (The ratio varies widely by company and industry, and anywhere from 4:1 to 10:1 is typical.) As coding becomes more efficient, I think teams will need more product management work (as well as design work) as a fraction of the total workforce. Perhaps engineers will step in to do some of this work, but if it remains the purview of specialized Product Managers, then the demand for these roles will grow.

This change in the composition of software development teams is not yet moving forward at full speed. One major force slowing this shift, particularly in AI Product Management, is that Software Engineers, being technical, are understanding and embracing AI much faster than Product Managers. Even today, most companies have difficulty finding people who know how to develop products and also understand AI, and I expect this shortage to grow.

Further, AI Product Management requires a different set of skills than traditional software Product Management. It requires:

Technical proficiency in AI.

PMs need to understand what products might be technically feasible to build. They also need to understand the lifecycle of AI projects, such as data collection, building, then monitoring, and maintenance of AI models.

Iterative development.

Because AI development is much more iterative than traditional software and requires more course corrections along the way, PMs need to understand how to manage such a process.

Data proficiency.

AI products often learn from data, and they can be designed to generate richer forms of data than traditional software.

Skill in managing ambiguity.

Because AI’s performance is hard to predict in advance, PMs need to be comfortable with this and have tactics to manage it.

Ongoing learning.

AI technology is advancing rapidly. PMs, like everyone else who aims to make best use of the technology, need to keep up with the latest technology advances, product ideas, and how they fit into users’ lives.

Finally, AI Product Managers will need to know how to ensure that AI is implemented responsibly (for example, when we need to implement guardrails to prevent bad outcomes), and also be skilled at gathering feedback fast to keep projects moving. Increasingly, I also expect strong product managers to be able to build prototypes for themselves.

The demand for good AI Product Managers will be huge. In addition to growing AI Product Management as a discipline, perhaps some engineers will also end up doing more product management work.

The variety of valuable things we can build is nearly unlimited. What a great time to build!

Keep learning,

Andrew

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