人工智能为组织带来的财务收益

欢迎收听这个播客。

Welcome to the podcast.

我其实还主持着三个与人工智能相关的节目，想借此机会给大家介绍一下。

I actually run three other AI related shows, and I want to give a shout out to all of them.

第一个是《AI应用》，我在这档节目里分享如何把人工智能融入你的职业生涯。

The first is AI Applied, where I cover how to apply AI into your career.

这档节目我和AI Mindset的首席执行官康纳·格兰南一起主持。

I host that with Connor Grennan, CEO of AI Mindset.

第二个节目叫《AI创业》。

The second one is AI Hustle.

几天前我刚在这档节目里做了一期，和杰米·麦卡利一起探讨如何用人工智能赚钱、发展和扩大你的业务。

I actually played an episode on this show a few days ago where I host that with Jamie McCulley, we break down how to make money, grow, and scale your business with AI.

第三个是《AI与信仰》，我在这里讨论如何利用人工智能促进精神层面的成长。

And the third is AI in Faith, where I cover how to use AI to help grow your faith spiritually.

节目简介里提供了这三个节目的链接。

So there's links in the description to all three of those shows.

但今天，我想放一集《AI Applied》的节目，是我和康纳·格兰南的对话。

But today, I actually want to play an episode from the AI Applied podcast, a conversation I had with Connor Grennan.

如果你对这个节目感兴趣，可以去查看，链接在简介里，那里还有更多往期内容。

If you're interested in that show, you can go check it out and find more episodes at the link in the description.

如果没兴趣也没关系，明天我们就回归正常节目。但我还是想提一提，因为这个节目我真的特别自豪，我们聊AI的时候特别开心。

If not, we'll go back to normal programming tomorrow, but I wanted to give it a shout out because it is a show I'm super proud of, and we have a ton of fun talking about what's going on with AI.

不多说了，咱们直接进入本期节目。

Without further ado, let's get into the episode.

最近，奥诺尔一直跟我聊《时代》杂志上一个特别有意思的故事。

Honor has been absolutely talking my ear off recently about a really interesting story in Time magazine.

文章讲的是领导者对AI投资回报率的误解。

It says what leaders get wrong about the ROI of AI.

其实上一期播客里，我们也稍微提到过这个话题。

And we're actually talking about this on the last podcast episode, I think, little bit as well.

但这个问题真的非常重要。

But this is a really important question.

其实，这个问题我也一直在自己的一家公司里反复琢磨。

And and actually, this is something I personally have been grappling with with with one of my businesses in particular.

我来分享几个挺有意思的故事。

I'll I'll share some funny stories.

AI能做的事，不等于就应该去做，关键得看投资回报率。

But just because AI can do something doesn't mean AI should do something because you have to look at the ROI.

我们得权衡的事情太多了。

And there's so many things that we have to balance.

自动化能做得特别厉害，但代价是多少？

There's incredible automations you can do, but but what is the cost?

有时候回报率很清楚，有时候却说不准。

And sometimes the ROI is clear, sometimes it's not.

接下来我们就来好好聊聊这些。

So we're gonna get into all of that.

Connor，你对这个想法最感兴趣的是哪一点？

Kicking this over to you, Connor, what got you most excited about, I guess, this concept?

是的。

Yeah.

我的意思是，我好像上一期播客里提到过这个话题。

I mean, I so I think I started to talk about this on the last podcast.

也许没提过。

Maybe I didn't.

不过最近我刚在摩根士丹利，正和那边一大团队深入探讨ROI，看看它到底该怎么衡量，因为我觉得这是个关键问题。

But anyway, so I was at Morgan Stanley just recently and I'm really working with a big group over there about, like, ROI and what does ROI look like because I think that this is one of the big things.

在AI Mindset，我们会跟一些大型企业合作，比如财富100强公司，一次性覆盖两三万人，推广这套课程。

And we so at AI Mindset, we get to, you know, roll out these enterprise partnerships with, you know, big organization like Fortune 100 organizations, like, you know, 25, 35,000 people at a time, kind of like roll out this course with.

他们最常问的一个问题，贾登，就是：我们该怎么衡量ROI？

And one of the big questions obviously they have, Jaden, is like, well, how do we measure ROI?

我们其实有几种思路，但我们的想法也在不断更新。

And so we have like a few ideas on this, but like our thinking has evolved.

所以我打算跟你们分享几个看待这个问题的角度，同时，我很欣赏凯蒂·乔治，她以前在麦肯锡，现在在微软，刚在《时代》杂志上写了一篇关于ROI的文章。

So I'm going to kind of take us through just like a couple of ways of thinking about this, but then at the same time, Katie George, who I'm a big fan of, she was over at McKinsey for a long time and is now over at Microsoft wrote that piece in time about like ROI.

首先，我非常认同她对这一点的看法，但她说的其实意思是，人们总把这当成是刚上线的新系统或新产品，一安装上去，投资回报率就立刻飙升。

And first of all, I really agree with sort of like what she was saying about this, but I'm also, you know, what she was sort of saying is essentially like people keep looking at this as if it's, you know, a new system or a new product that you put in place and all of a sudden your ROI jumps.

但她强调，根本不是这么回事。

And she's like, it's just not like that.

关键在于改变人们的做事方式。

It's about how changing how people work.

这恰恰也是我们的看法。

And we're like, that's exactly how we think.

所以，让咱们先从头说起，我们对这个问题的理解是这样的：我来分享两种思考方式。

And so, Jean, just to sort of kick off this conversation that we've the way we think about this is I'm going to give two ways that we think about this.

第一，其实我们每次发工资的时候，已经在衡量投资回报了，对吧？

Number one is we're already measuring ROI now every time we give somebody a salary, right?

如果你公司给某人发二十万美元的年薪，那背后是基于一个预设：这个人在这个岗位上创造的价值，能覆盖这份薪酬。

If you give somebody a salary for $200,000 in your organization, you are counting that on the fact that there's an ROI on that person in that role paying that amount of money to.

但大家都知道，不是每个岗位的回报率都一样。

Now, everyone knows that there's not the same ROI in every salary.

你知道，有些人拿的薪水其实是一样的。

You know that sort of like people can be making the same.

有的人的回报率能达到十倍之多。

On some, like the ROI on that salary is like 10X.

但有些人呢，回报率可能就一倍、两倍，或者差不多这样。

And on some, it's like, oh, it's like 1X or 2X or something like that.

你基本上是物有所值的。

You're basically getting your money's worth.

为什么呢？

Why?

因为每个薪水背后都是一个活生生的人，他得干得更好，或者干得更少。

Because behind that ROI, behind that salary is a human that has to work better or work less.

如果这就是回报率，而人工智能的目的又是提升人们的工作方式，那你就等于在放大这份薪水的回报率。

So if that's the ROI and AI is intended to augment how people work, now you're talking about x ing that ROI of that salary.

实际上，简，我们在AI Mindset也跟一些对冲基金合作过。

It's not like and, Jane, we do some work with hedge funds at AI Mindset.

你听好了。

And listen.

真佩服你们这些做对冲基金的。

God love you for a hedge fund out there.

你们可不是好打交道的那类人。

You're not the easiest people to work with.

这点你应该清楚。

I think you know that.

你心里早就明白。

I think you already know.

我说的这些，你都不是第一次听说。

I'm not telling you anything you don't know.

对冲基金的特点是，你们常常从算法这类东西的角度去思考问题。

But the thing about hedge funds is that, like, they're thinking often in terms of, like, you know, algorithms and things like that.

比如怎么在巨额投资——上十亿美金的投资——上稍微提升一点回报率。

Like, how can we, you know, just sort of, like, get a slightly better return on investment, but on huge investment, on, you know, billion dollar investment.

我明白这一点，但这不是人工智能。

And I get that, but that's not AI.

那问题到底出在哪里呢？

So where does the disconnect come in?

问题在于，人工智能看起来像一项技术，行为却像一个人。

It comes in because AI looks like a technology, but acts like a person.

对吧？

Right?

我们都知道，尤其是在跟大公司打交道的时候，我们经常说，这看起来像是数字化转型，但实际上跟数字化转型毫无关系。

What AI, we we know, and we do this with big companies, what we say all the time is like, this looks like a digital transformation, but it has nothing in common with a digital transformation.

它跟变革管理才是息息相关的。

It has everything in common with change management.

数字化转型是指你把旧系统换成Salesforce，然后彻底淘汰旧的客户关系管理系统，再把所有人迁移到Salesforce上。

The digital transformation comes when you switch out your old system for Salesforce, and then you have to burn down your old CRM, and then you move everybody over to Salesforce.

那才叫数字化转型。

That's a digital transformation.

你只是把人们从一个效率低的系统换到了一个效率高的系统。

You've moved people from a less efficient system to a more efficient system.

AI可不是这么回事。

AI is not that.

AI讲的是怎么增强人们的思考方式和工作方式。

AI is how do you augment how people think and work.

所以当我们谈投资回报时，第一点，就像我说的，是看团队里你期望员工达成的关键指标有没有提升。

And so when we think about ROI, the first one, as I said, is can you look at the KPIs that you expect out of people in teams and are those things going up?

顺便说一句，这也不一定非得靠AI。

And by the way, it doesn't have to be AI.

比如，我不在乎一个人是开车十分钟到公司，还是走路走了两小时，反正他到公司了。

Like, I don't care if somebody shows up to work and and they took their car and got here in ten minutes or if they walk two hours, like, they still show up at work.

所以某种程度上，AI没那么关键。

So in a way, AI isn't that important.

你明白我的意思吧？

You know what mean?

其实，AI本身没那么重要，关键在于什么才是真正创造价值的因素。

Like, the AI part is not as important as what are the what drives value?

对吧？

Right?

接下来第二个我想说的是创新指数，杰登。

So and then the second, one that I think about, Jayden, is the innovation quotient.

我们确实在AI思维这个项目里做了这套方法。

And we do this actually at at AI Mindset.

我们为此建立了一整套评估框架。

We have a whole framework around it.

这个理念我们其实和沃尔玛一起实践过。

But the idea behind that is and and we did this with Walmart actually.

我们发现，过度追求效率反而会抑制创新。

Like, we find that productivity tends to be the enemy of innovation.

我的意思是，哪怕你每小时只提升了那么一点效率——

And what I mean by that is like an hour of productivity gain.

假设你每小时的效率提升了百分之二十，

Let's say you've kind of like, you know, gotten your 20% more productive over an hour.

你看，

Look.

这种提升会慢慢积累起来的。

That's going to add up.

这确实不错。

That's great.

这太棒了。

That's awesome.

好像人人都觉得目标就是这个，但我们谈ROI的时候不是这么看的。

That feels like everybody has the end state, but that's not how we think about ROI.

我们更看重创新带来的回报。

We think about ROI as like in terms of innovation.

你到底怎么实现真正的转变？

How do you actually transform?

如果你花这一小时，专心思考怎么重塑你的工作角色，用AI帮你分担认知负担，你就不用再自己琢磨所有这些事了。

If you spent that hour and just like, you know, really focus on how you would transform your role and use AI to lift the cognitive load off you so you don't have to figure all that out.

这时候你谈的就不是10%的回报了，而是十倍的回报。

Now you're talking about ROI that's not 10%, it's like 10x.

我这可不是在夸大其词。

And I'm not even exaggerating.

我们看到像Anthropic这样的公司就已经做到了，关键就在于你是否真正聚焦在创新上。

Like, because we see this with companies like Anthropic, this is possible, but that's when you focus on innovation.

ROI可以有很多不同的含义，但我希望大家思考的不是：我们现在有了AI，公司能带来什么预期？

So ROI can mean a lot of different things, but what I urge people to think about is not like, we have now have AI, what can we expect from our company?

重点不在于你对公司的产品有什么期待，而在于你对你的人有什么期待。

I'm like, it's not what you expect from your company or product, it's what you expect from your people.

这才是真正有意思的地方。

That's where it gets interesting.

百分之百。

A 100%.

我觉得这其中一个有趣的地方是，你可以想，我们怎么把现在做的事优化一下？

And and I think one interesting thing about all of this is, you know, you can you can be like, okay, how do we optimize what we're currently doing?

我们用了AI，效率提升了10%、20%、甚至50%，但还是在原来那些流程里打转。

Okay, we're using AI, we're getting you know, 10% better, 20% better, 50% better in all of the same processes.

但AI的用法，或者AI能做的事，其实能从根本上改变整个公司的运作方式。

But the way you use AI can or what AI can do can fundamentally shift how your entire company operates.

你总在想，怎么让马跑快10%、20%？

It's like, how can I get my horse to go like 20% faster, 10% faster?

别再用马了。

Don't don't use the horse.

直接换汽车。

Go to a car.

那你已经不在同一个层级了。

You're you're in a completely different league.

你是在用完全不同的方式做事。

You're doing things in a completely different way.

这挺有意思的，虽然这个比喻可能不太恰当，但对我而言，当我刚开始用 ChatGPT 的代理模式时——大概一年前吧——我得每个月花两百美元才能用。

It's interesting, and this is probably a terrible analogy here, but it's it's kind of like, for me, the way I think about this, when I first started using Chat GPT's agent mode, which was like, maybe like a year ago, I had to pay like $200 a month to use it.

它在屏幕上做的每一件事，都是按照我平时的操作方式来的。

And everything it would try to do on my screen was doing it the way I was used to doing things.

截个屏，移动鼠标，点个按钮。

So take a screenshot of my screen, move the mouse, click a button.

截个屏，移动鼠标，点个按钮。

Take a screenshot, move the mouse, click a button.

速度特别慢，还老出错，问题一堆。

It was very slow, it had glitches, it had issues.

后来 Claude 出现了，它的 Co-Work 功能彻底火了，使用量飙升了八十倍，原因在于，它虽然也会看屏幕、截个图，但根本不会去点按钮。

Then came along Claude, and the way Claude's co work, which has absolutely taken over and they went up 80 x in like you know usage, is because with code and co work, what it does is it, sure it might look at your screen, it might take a screenshot, it doesn't try to click the button.

它会在后台运行一个 Python 脚本，把网页上的所有内容都抓出来，自己判断按钮在哪、流程怎么走，然后分析你到底想干嘛，再用逻辑推理制定计划，最后直接跑脚本来完成任务。

It runs a Python script in the background that extracts everything on the web page and figures out where the buttons are and how everything goes, and then it formulates a plan and does like logic and reasoning to think about what you're trying to do, and then it's like running scripts to do things.

我曾经让它在 CapCut 里剪个视频，本来以为它会打开 App，然后在界面上点来点去地操作。

I I told it to edit a video on CapCut once thinking it was gonna open up the CapCut app and click around the UI and edit the thing.

它先试了两秒，说太慢了，直接关掉CapCut，打开它自己生成的文件，修改了代码，然后说：好了，视频已经剪好了。

And first, it tried that for two seconds, said this is too slow, closed the Capca app, opened the file it had created, edited the code on the file and said, okay, your video is edited.

我打开一看，所有需要改的地方它都帮我弄好了。

I opened it up and it had edited everything for me.

这完全是另一种解决问题的思路。

This was a completely different way of approaching the problem.

如果我只是想问，用CapCut剪视频能快多少？Claude打开界面，点击操作，比我自己快20%，那又怎样呢？

If I was like, how much faster can I edit a video in CapCut, and Claude opened up the screen, and it clicked, you know, 20% faster than me on the edits I needed to do, well, whatever?

它确实快了20%，但用的是完全不一样的方法。

It got 20 but it did it in a completely different way.

所以，这其实适用于所有行业，我觉得这是我们该认真思考的大问题。

So anyways, this applied to every business is I think a big thing that we should be thinking about.

关于AI的最后一点，就是AI和投资回报率，这倒不是重点，只是我顺带提一下。

And then my last point on AI, which is AI and ROI, which this isn't really the point, this is probably a smaller thing, I just have to I'm here shift for this.

转向另一个

Towards another

我支持这个。

I'm for this.

这简直快把我逼疯了。

It was killing me.

前几天我运营一个新闻网站，叫 aichatdaily.com，它会抓取二十个不同来源的信息，整合后写出高质量的文章，每天汇总AI领域的最新动态。

The other day I have my news site which is aichatdaily.com and it basically scrapes 20 different sources and writes up, consolidates the news and writes some really great articles on everything happening in the news every day in AI.

所以我之前要做的一件事，就是为每一篇自动生成的文章配上出色的缩略图或者封面图。

So something that I was doing was I needed to generate like really good thumbnails or like hero art for every article that was being generated.

我之前用的是 OpenAI 的 DALL·E 1.5 或者 DALL·E 2 图像模型来生成这些图片。

I was using OpenAI one point point five or OpenAI two image model to do this.

我有一套特别棒的提示词体系，还设计了一个循环机制，用了大概二十个不同的提示词，轮流测试，生成的图片效果惊人，还会从维基百科抓图再做二次编辑。

Now, I had these really amazing prompts and I had this amazing prompt cycle where I had like 20 different prompts and it would cycle through them and it was making these images that just looked incredible and it was like grabbing them from Wikipedia and then editing.

总之，我搞了一整套流程。

Anyways, I had this like whole process.

效果特别好。

That was amazing.

问题是，每张图都要花我五毛钱。

The problem was every image was costing me like 50¢.

这是个新网站，还没赚到一分钱。

This is a brand new site that wasn't making any money.

我每天要生成一百篇文章。

I was making like a 100 articles a day.

这么一来，每天光是图片成本就突然涨到了五十块。

And so, I mean, that was like $50 a day that all of a sudden I just started having to pay for all of these images.

我当时就想，虽然AI能做，效果也确实惊艳，还有人在LinkedIn上发帖说：天啊，你看到这个新网站了吗？

And I was like, I was like, just because AI can do this and it looks amazing and and I like I'm getting people on LinkedIn that are like posting like, oh my gosh, have you seen this new website?

做AI新闻真是再合适不过了。

It's like so good for AI news.

我心想，这确实挺酷的。

It's like and I'm like, wow, this is cool.

居然真有人在找这个网站。

Like people are finding this.

我特别兴奋，但问题是，这个全新的项目啥也没干，每天却要花我50块，我忍不住算了一笔账：这样下去一年得花多少钱？

I was thrilled, but like it was costing me $50 a day for like a brand new project doing nothing and I'm like extrapolating like how much am gonna spend on this in a year?

总之，最后我干脆改了流程，让系统每次生成图片时，自动把它归到某个类别里，然后我给世界上每个公司、每个人建了个文件夹。

Anyways, at the end of the day I was like, I basically just changed it so that every time it made an image, it automatically categorized it into a category And then I made a folder for every single company and person in the world.

接着我就把每个名人、每个公司生成的十张、二十张图片都放进了对应的文件夹里。

And then I just put, you know, ten, twenty images that had been generated of every person in the world into these folders.

之后系统就自动从中选一张，轮流使用。

And then it just automatically picked one and cycled through.

差不多每20篇文章，就轮换一次图片。

So every 20 articles, it kinda cycles through them.

明白了。

Okay.

一下子，我的开销从原本的高额变成了几乎零成本。

All of a sudden I went from spending x to spending free basically on this.

AI能做一件事，不代表它就应该去做。

Just because AI can do something doesn't mean AI should do it.

你得看看投资回报率。

You have to look at the ROI.

所以呢，我虽然对人工智能特别兴奋，但有时候我也意识到，这些东西还是得优化。

And so anyways, I get really excited about AI, but even I sometimes realize you gotta optimize this stuff.

我不确定这是否是文章的重点，但我非得跟你说说这个故事。

I don't know if this is the point of the article, but I had to share that story.

不是。

No.

我特别喜欢，因为在我看来，它还涉及好几方面。

I I love it because it to me, it's sort of like a couple of things too.

对吧？

Right?

就像那个《AI聊天每日》。

It's like like AI Chat Daily.

我其实是它的粉丝。

I'm a I'm actually a fan of it.

挺酷的。

It was pretty cool.

Jade 给我讲了这件事。

Like, Jade was telling me about it.

我当时就说，对啊。

I'm like, yeah.

但其实它做的和别的东西差不多。

But that kinda does the same thing everything else does.

我还想，哇，这东西真不错。

And I'm like, oh, this is actually, like, really good.

说来好笑， guys，我们做这档节目调研的时候，Jaden 直接上自己的网站。

And now the funny thing, guys, like, when we're, like, researching for this show, Jaden just goes on his own site.

所以这不只是外部工具，它还帮他筛选好了内容，本身就有回报。

So it's not only, an external thing, but, like, this thing's already curated things for him too so that there's an ROI on that even.

对吧？

Right?

因为你知道，Jayden一天也就那么点时间。

Because, like, you cause Jayden only has so many hours in a day.

所以投资回报率不一定非得跟以前一样。

So ROI doesn't have to look the same as, as ROI always has in the past.

不过我想说的另一点是，Jayden，你还记得之前有个小技巧吗？

But the other thing I guess I would say is, you know, Jayden, you remember there's this, so this is a tip.

我平时不太爱分享这种技巧。

So I don't usually do a lot of like tips.

对吧？

Right?

但我可以告诉你一个对我特别管用的方法。

But I'll just tell you something that works really well for me.

Jade，你还记得吗？在推理模型出来之前，大家常会用一种方法，就是所谓的思维链提示。

Jade, remember when before like chain of before the reasoning models came out, the way you could sort of like hack that was to sort of say like, it's like the chain of thought prompting.

就是说，你直接问他：你给我一步步讲讲这个。

It's like, hey, walk me through this.

你再深入想想这个问题。

Hey, think deeper about this.

那个深呼吸的建议，其实整个意思就是。

The whole tip about take a deep breath.

大家都好奇，为什么这个方法有效？

And everybody's like, why does that work?

这是因为AI能明白你这么说背后的用意。

It's because AI understands what you mean by that.

其实就是让你想得更深入一点。

It means to think deeper.

所以我平时老是这样，心里默默提醒自己：

And so, like, what I do all the time is I'm sort of, like, thinking like, hey.

我想做这件事。

I wanna do this.

然后我就赶紧把思路理清楚。

And I'm kind of, like, faster horsing it.

对吧？

Right?

我慢慢在进步，越做越好。

I'm sort of, like, kind of working my way up, and it's getting better and better.

我觉得这太棒了。

I'm like, this is great.

然后我总是做同样的事。

And then I always do the same thing.

我通常用Claude或者Gemini这类工具。

And I it's usually in Claude or Gemini, something like that.

我会说，嘿。

And I'll say, hey.

听好了。

Listen.

你知道我想做什么。

You know what I'm trying to do here.

对吧？

Right?

你能不能想想，如果你刚进来，想要重新设计这个，同时又想回应我、模仿我的做法，你会怎么说？

Can you just think, like, what would you say if you're coming in and, like, reinventing this because you're sort of, like, trying to answer me and do what I'm doing?

Claude 经常会说，是的。

And Claude will often say it's like, yeah.

听好了。

Listen.

让我稍微停一下，好好想想。

Like, let me just take a second and think about it.

这其实是个挺奇怪的、有点过时的2023年小技巧，但效果出奇得好，因为它能让你像 Jayden 一样——如果你和我正一起搭东西、坐下来喘口气，就会说：

So it's it's a weird sort of, like, old timey 2023 trick, but it works unbelievably well because what it does is it's Jayden, if you and I were sort of, like, building something and sitting back, it's like, hey.

咱们好像往这个方向走了，但咱们到底想达成什么？

I guess we're going down this road, but what are we actually trying to accomplish?

你明白我的意思吧？

Do know what I mean?

我们通常都会走这些步骤。

Like and so and usually, we're taking all these steps.

但关键是达成最终目标，而Claude有时候会直接说，是的，康纳。

But if the if the trick is to get this end state and Claude will sometimes literally say, yeah, Conor.

听好了。

Listen.

我之所以一直这么做，是因为你一直让我这样做的。

I've been doing it this way because you've been asking me to do it this way.

我的想法是，如果你真想搞定这件事，为什么不换种方式试试？

My thought is, like, if you really wanna get this, why don't we do it this way?

贾登，凭我自己的思维局限，我根本不可能想到这一点。

And there's no way, Jaden, because of my cognitive limitations, I ever would have thought about that.

所以，各位，这里有个简单的技巧：稍微停一下，拿出你的2023年技巧手册，然后对Gemini、Cloud Chat，或者你用的任何工具说，嘿，先别急，喘口气。

So, guys, just an easy trick on this is just to sort of, like, pause, get that twenty twenty three tip handbook out here and just be like, hey, listen, Gemini, Cloud, chat, whatever you're using, just take a breath for a second.

我们真正想达成的目标是什么。

This is what we're actually trying to accomplish.

我们目标是把收入翻十倍，我带你走这条路，而你正在帮我搭起这座小阶梯。

We are trying 10 x our revenue, and I'm taking you down this path, and you're trying to help me build this little staircase over here.

但你能不能在背后直接建个电梯，就那种，简单点的？

But is is there an elevator that you could just, like, build, you know, sort of, like, over there in the background?

这招效果惊人。

It's unbelievably effective.

完全没错。

100%.

各位，非常感谢今天收听这期播客。

Guys, thank you so much for tuning into the podcast today.

如果你们喜欢康纳的这番分析，我最推荐你们去试试康纳的AI思维课程。

If you enjoyed Connor's breakdown here, the number one thing I would absolutely recommend you have to do is go check out Connor's AI mindset course.

他会深入探讨很多这类大问题，比如大家对AI投资回报的误解，还有如何从根本上转变你对AI的认知和应用方式。

He gets into a lot of these kind of bigger questions, you know, what people are getting wrong about the ROI with AI, a lot of ways to fundamentally shift how you're thinking about AI and how you apply it.

我觉得这里最有价值的地方在于，他提到不同公司会一次性采购上万席位，全公司内部推广使用。

And and the place that I think this is the most valuable because he's telling me about, you know, in different organizations, they will buy like 10,000 seats for their whole organization to get this rolled out internally.

我强烈建议你把这套方法带到你的部门，跟你的上司聊聊，也在你们整个团队里推行开来，让每个人都能真正提升对AI的理解和应用能力。

That's what I would really recommend is bring this to your department, bring this to your boss, bring this to your own organization, and roll this out for everyone in there to really be able to level up themselves with AI, how they're approaching AI, and what they're doing.

简介里有Connor的AI思维课程链接，这是我目前最推荐给大家的AI课程。

So there's a link in the description to Connor's AI mindset course, the number one course I would recommend to anyone on AI.

简直太棒了，尤其在企业场景下。

Absolutely phenomenal, especially in enterprise.

好了，非常感谢你收听本期播客。

Alright, Thank you so much for tuning to the podcast.

我们下一期再见。

We'll catch you guys all in the next episode.