441 AI Use Cases with LinkedIn’s Top Finance Influencer

I got a treat for you today. One of the biggest AI finance educators probably in the world coming in. And we're just, we're just fully geeking out on all things AI, how it impacts how you build a team and the things that you would hire for versus maybe just use AI for. It's going to share a couple cool use cases that he has kind of developed with his AICFO community. And for me, it was an interesting peek into sort of an adjacent group of folks and how they're actually using AI. Actually some different advice than I usually give to accountants, which was interesting. But also if you are looking to do more advising inside of your accounting firm, like, this is so relevant to you. What does it look like to be an advisor in an age of AI? Like, I think there's a fundamentally different approach for how you do it. So without further ado, check out this conversation with Nicholas Boucher. Okay, Nicholas, for folks that haven't had the pleasure of meeting you or bumping into you online yet, you want to give us the 30 second intro?

Sure. If people don't know me, so they should find me on LinkedIn. Normally I am a finance guy. First worked 15 years in finance, first at PwC as an accountant and auditor in Luxembourg and Singapore, so Europe and Asia. And then I moved on on the corporate side working for a company called Thales, which is like Boeing, especially if you have a lot of Americans, but just smaller because it's European. So focus on defense and aerospace. And there I was a controller and a head of finance. But now actually I'm doing something that I enjoy even more. I'm teaching people how to use AI in finance. So either through courses or through my community, which is the AI Finance Club.

Nicholas, how many followers do you have on LinkedIn now?

1.1 million. Something like this?

Yeah, Nicholas, putting out very useful stuff on the daily. Also running webinars and actually like getting real practical, like rolling up your sleeves with real use cases. And that's kind of what we're digging into today is online in your community. I want to hear like the accountants. I want to, I want to peek into the finance world of what are the really cool things you all are stumbling into and, and where you're actually putting this to each day.

Yeah, that's, I think important because you hear a lot about AI, a lot about bs, I would say, where like, it's super theoretical and I hate that. And that's why in my content, I always want to show, to explain, so I might show something later. And for people listening, we, we will explain, I think what is on the screen, but I think you will also record that and put that on YouTube. So if people want to see in action, we are going to show that later.

Yeah, yeah. So if you're, if you are listening on your podcast player, there'll be a link to the YouTube version of this if you want to jump over and, and see anything visually. But can I like, just to set a bit more context, how did you get started with, with AI stuff? Like did you have any background in machine learning or anything like that?

I'm a finance guy first. The only thing is I love technology. At the beginning was Excel. Then it was even PowerPoint where I just, I was really a geek about all of these tool. I know how much you can leverage to be faster, to do cool stuff to impress your boss. And when in November 2022, I was actually in Qatar for the World cup and I got on my phone, I saw like on Twitter because I follow also all of these crazy people that are always like one step ahead. And I saw you could download this access to ChatGPT. And so I think it was the second day where it was available. I got it. And then I spent my nights just trying everything on this because I thought this is unreal. Like somebody's going to shut down this website. It cannot be. And at the time I was already posting a lot on LinkedIn. So I just, I was brainstorming on all of the potential posts I could do and quickly I used this for LinkedIn. Not a lot of people knew how to use this. So I was like, I got a lot of growth thanks to that. But as I was still working also on my job, I was thinking, okay, like let's use it for example to write a reminder letter. And it did the job perfectly. Then let's use it because I have a problem in SAP. I don't know which transaction to use. And then it gave me exactly the transaction I could use plus all of the settings I should click to get, for example, to have a list of overdues. Then I asked, okay, what about Excel? So like what is the best formula, for example to just to map to two tabs. And we all know Vlookup or Samif or xlookup is the one for this. But I had a finance team before and if they had a chatgpt next to them, they will have saved a lot of time. So this is a lot of things where really quickly I linked the two like, okay, Finance and Generative AI. How to combine both. Because at the time all of the marketers and Internet gurus were only about creating ads, creating copywriting, marketing materials. Yeah, exactly. But I was really focused on finance and on February 2023 I released a PDF guide which I did with ChatGPT in one weekend as well. And this PDF guide was 90 pages on how to use ChatGPT for finance and with 24 use cases. And that was my also my start in also selling courses around AI for finance and helping a lot of finance professionals.

So we've hung out a bit. You've got like a unbelievable mind for like teaching and documenting all of these things and creating these frameworks. Like I'm incredibly jealous because you still get people who will comment on a LinkedIn post of mine. Yeah, but what do accountants even use it for? And like if I was Nicholas, I'd be like here, you dummy, here's a hundred page PDF of 50 use cases. But like I just, I'm, I, I gotta get there. Like you, you inspire me.

Yeah, that's, that's one thing where you know people are still need to be comments and for what works really well on, on LinkedIn is overwhelm people with information, but in a stricter way. So I did a lot of time also brainstorming for myself for the courses to convince people if I want to help them. Also using AI. That was like two years ago. That was really like convincing people, yes, we can use it for finance. And these are all use cases and even for me to structure my thoughts. Those infographics are great because you can use it for everything with writing. But what does it mean writing then a checklist. So for all of the accountants listening to us today, everything where you have to do a month end checklist, a yearly checklist, a budget checklist, even onboarding checklist, you can use this then if you want to write procedures, you want to write emails, you want to write anything where you need to spend more than two minutes, you should use this then after you have everything with tools. So it's another category, any tool that you use and not later than today. I had a problem with AI tool like agent tool that I'm building. I was just like giving copy and paste of screenshot to help me code and do this. And I'm not a coder, but I'm just using AI to code for me. So anything with tools like it gives you tutorials adapted to you and that's, I mean I don't know how long you have spent when you wanted to search Something on Google and YouTube when you had a problem with Excel. But it's quite long until you find the solution. Generative AI gives you straight away what you need in your context. And so I have like now also the thing I love the most is financial analysis because this is where you start to be nerdy with finance people. And at the beginning it was not really good. It was only good to brainstorm on what are the typical financials. You could do for example for sales or for headcount or for cash or balance sheet or KPIs. But now what is good is you can also start doing the financial analysis inside the tool. And that was not possible at the beginning. But one thing happened which made the thing available. And I mean, you know yourself, what is this magic thing that happened? Is the AI like all of these LLMs, they are not calculators, they are models that are probabilistic. And in finance we hate probability, we need accuracy. And so what we need is something that calculates. And what the guys at chatgpt and OpenAI did is they brought Python inside the chatgpt and then basically you have chatgpt asking Python to calculate and using this calculation for the answer. Which now actually for us in finance is not a black box anymore. You can look at what is happening and you can audit if the result is good. The only thing to change, and that's what I'm also doing with other experts. We need to bring the acceptance of Python into the finance world because that's the only way we are going to use AI in finance.

Yeah, so data analyst, which has been kind of a built in feature in ChatGPT for a while, but it's, I think a lot of people don't know about it because it's not presented visually in the UI really, but it just got, they just rolled out support for data analyst in the reasoning models within the last couple of weeks. I don't know, let's maybe, let's dive into an example. Do you have a data analyst example that, that you're excited about? We could run through, run people through?

Yeah, sure. So here I'm going to share my screen on what typically all of the SaaS business are doing. So if you're a SaaS business, you are purely doing a cohort analysis. For those that don't know what is a cohort analysis. If you are, if you have never been in the SaaS business, cohort analysis is analyzing your clients by cohorts and you can group them based on different criterias. One type of criteria that your business like to use the most is to group them by dates or by months when they started to become a customer. So here, what I'm showing is a heat map where on the left side you have all of the months, basically the last 24 months, where we see line by line, the client when they entered into our business. And then on the bottom you see how long they stayed. And what we see is, for example, the first line is Everybody coming from January 2022. So the OGs, the clients that were there at the beginning, we can see that the first four months they are staying. So 100% of them stayed. But then after the fifth month, 6% left, then the sixth month, 12% less left, et cetera. Until that two years after, only 42% stayed. And then you can compare basically month by month, if some months, clients stay longer than the others. And that helps you understand if some actions you did to acquire those clients were better or worse. For example, in the picture that we see in August, really quickly, the clients left. So meaning maybe there we had customers that came because we had a special offer or we got like a specific country. And this quality of client is not what we want to do to have for our business. So as a finance person, it's good to have this to get clarity on the sales. But Jason, do you know how long do you need to do that in Excel?

It looks like a lot of work.

First, it's not a graph that is integrated in Excel in the graph option. So you have to do it everything manually, like you have to do if it's a heat map. You have to do all of the formulas and conditional formatting, everything manually. And if you ask people in SAS who are doing that, there are 10, um, the first time they build that in a few days and then after they need a few hours. Now I'm going to show you how you can do that using generative AI. And here, this is the table that we used. So the table has dates, so all of the transactions, the customer id, and basically product and amount. But we just need the amount actually. And when I use this table and this table, I'm going to be able to upload it later in ChatGPT. And for those who have difficulty with data confidentiality, I am using ChatGPT Teams, so my business is okay with this because ChatGPT Teams is under SOC2 and also in Europe is GDPR compliant. So I'm uploading this file and then I'm asking, can you do a cohort analysis? And I Add visually, because a cohort analysis can also do in a table or just calculations. And I explained that I want to analyze the retention rate and I want the cohort to be by month. And now what is happening is ChatGPT is asking Python, we saw it briefly, but is asking Python to do the calculation to do this graph for ChatGPT. So ChatGPT is not calculating, ChatGPT is not creating the graph, it's just giving the instruction to Python. And Python can do that. Python can calculate and Python can create charts. And this video is not accelerated. This video is not cut. This took 1 minute and 30 seconds to be created. And we have exactly here the heat map. And this replaced four to five hours of work.

Wow. And like to your point, I think you mentioned this earlier, like this is code being run across your data. Like this isn't an LLM making an interpretation where you worry about hallucinations and all that. It is like your actual data being processed.

Yes. And what I recommend also, because it might be still, for a lot of people, a feel of a black box. You use it like it's somebody in your team working for you. And Jason, if somebody is doing this analysis for you and just gives you the graph, probably you are going to ask, show me how you built it, show me the working files. And you need to consider this generative AI assistant In the same way some, like an intern that is really good at Excel, who with the right coaching, performs really fast and really well. But you need to control if the work is well done. And for this, what I usually do is I ask to show me the step by step to show me how it was built. So show me why you decided to do that and which step you took to arrive to this result. And then you can see if at one point maybe the reasoning just went wrong. So maybe I wanted something only on a typical type of product and it took the wrong product to analyze it. Maybe I wanted the retention rate. But here it's showing me actually the people that left, so just the percentage is inverted. And by asking the step by step, it helps us as human to understand what is happening. And even if you have after only the Python code to analyze, there again you can ask, okay, explain me each line and explain me like just I am five years old, just to make sure I understand what you did in this code. And then you can really quickly identify if something is wrong.

Today's episode is sponsored in part by the folks at Cloud Accountant Staffing who help you find talented accountants in the Philippines. We Get a tremendous amount of inbound from anyone and everyone that's got like offshore staff and wants to come and work for us. Right. So how do you cut through the noise and know who's legit? Well, for one, I'm gonna let two offshoring groups sponsor my content and I now know two tens tons of firms that have used each of them to great success. Anytime I hear about them using them, I always ask how did it go? How was the experience? Have heard nothing but positives and it's why we've, we've stuck with them. So how's that for a filter? Because I have talked with a lot of them that ought to put them ahead of most. But the other thing to look out for in any of your vendors is are these folks turning up at accounting conferences and having real conversations with real accounts to understand what we need. I can take cloud accountant staffing like they are making the rounds this year. If you are out on the circuit at all like I am, you're going to see them and that is a great signal that they care that they're not some like random offshoring group that are just throwing work at people with all sorts of various skill sets. Like they are very focused on the accounting firm and exactly what your needs are. They're actually run by folks that used to run an accounting firm. Fancy that. Let's go to account staffing to learn more about them. Check out the link down in the show notes. This episode is sponsored in part by Makers Hub gang. It has never been more important than it is today to ensure that you have hitched your accounting firm wagon to the tech partners that are going to take your hand and lead you into the AI era. I don't care if you think AI is going to going to be the end of everything or the start of something better. AI is already here, it's already happening. And Makers Hub is at like the bleeding edge of what I can enable for the accounts payable process. I know. Wow, sexy. Listen, just be happy that they're doing it so you don't have to use an AI vision models and LLMs to push, you know, automated extraction from bills and kind of the subsequent logic further than we've ever been able to do before with just pure OCR technology. And honestly the bigger thing is when you have somebody that knows their stuff like that. And makersub has come around really just in the last couple of years. So really in the age of generative AI, I have a high degree of confidence that whatever is around the corner when it comes to AI, they are in the driver's seat to lean into that stuff in a way that oftentimes the incumbents are not makers up. You're also going to see them out at a whole bunch of accounting conferences this year. So they are having conversations with accountants. They understand the problem of the firm, how you run a scalable bill pay service. So that's something that your firm does. Or if you got clients with gnarly bill pay issues, makers Hub do it. It's the platform of choice. Learn more about it down in the show notes. So what we just did was Data Analyst is built into ChatGPT and it visually presents that in ChatGPT. When would you use that versus having it say write an Excel macro to do the same thing.

So this is really cool when you want to go fast and get a quick analysis. I never recommend to substitute your work with this. It's rather if you start and you never did an analysis, it's a really cool way. Really cool to start with this. But then after what you can do is you can ask how can I do that? Either in my Excel file if you want to replicate that, or here is actually easier, we have already the code. So you ask okay, how can I do that in my own environment in a productive way? And there we'll give you the code that you can execute in a tool like Google Colab or Visual Studio. And again, like might be for a lot of people be complex because nobody coded, nobody heard about Python, nobody heard about Google Collab or Visual Studio. But that's what people that want to become AI CFOs and that's in my community that's what people do. They learn this with us and only after half an hour they are able to do it because we give them exactly the shortcuts to do it. So I can understand that people don't want to learn, but you don't have to learn how to code. You just need to learn where can you place the code and execute it. And those tools are now like Google Colab is like Google Docs, really easy to use and you just need 15 minutes of coaching from us to use it. But I still feel that Excel is the place to start. So here you have a lot of charts that are available in Excel. I took an example that is not available in Excel, but a lot of analysis are available in Excel. And so I will ask how to do that in Excel and then give me the step by step and I will even add if you don't want to Put your data inside if you still want to get help. Well, ChatGPT or Gemini or Copilot cannot read your mind. ChatGPT, Gemini, Copilot, they cannot see your screen with your data because you don't want to show it. So what do you do is actually imagine like you have somebody on the phone. So, Jason, I call you and I have a problem with Excel. I'm going to tell you, look, this is how my file look like. My file has in a one header called client. Then in B1 it's date and then in C1 is revenue. And then I have 100 lines and the date looks like this because the format of date is super important on Excel. And then I will ask you, okay, I have, in another tab I have customer name and customer country. So how can I map these two tab to have maybe like revenue by country. And because you are good at Excel and you are starting visualizing all how the Excel file looks like, then you can answer to me by giving me maybe the Vlookup plus after pivot once everything is mapped together. And that's how you should do with ChatGPT or Google Gemini or Copilot or Claude. You need to do that. If you don't want to give your data, you need to explain enough. So without giving any of the confidential data, but just the structure and some fake example if you want even to reduce the risk of problems. And when you do that, it's incredible because you get exactly the formula you can use. It's not just, oh, you should use Vlookup, no use Vlookup, then parenthesis, then A one, then it will give you like all of the, not the code but the formula with all of the cells inside. And this will save you a lot of time and also will make you much better at using Excel and automating also your work.

How much of this? Like you talk about being kind of an AI enabled cfo and I guess I hadn't made this connection because AI is, I mean it's so many different things, but the way you talk about it, a lot of it is just unlocking like the ability to write code to solve the problem. Like, is that a big percentage of what you see an AI CFO kind of being capable of is being able to leverage code for the first time.

There are two aspects, three aspects. The first one is AI for your productivity because a CFO is not only calculating. You have so many things during the day. You have meetings, you have presentations, you have to solve problems that are not, I Would say monetary, but more strategic. So I think you should just make AI your assistant next to you and have an AI first approach. Then after, for everything linked to financial analysis, you have first the step of are you doing the right Franchon analysis? So then again you can brainstorm with AI to choose the right analysis. But then after, how can you execute this analysis faster? And that's where code comes in. Because instead of clicking everywhere with our mouse or entering ourselves the formula, you can let AI give you the code that will do that. And then you can save a lot of time. And for people using Google Sheet, I will really give you a tip. Try Google Apps Script. And with Google Apps Script you can for example ask to do for you all of the cleaning of your data. So imagine if every day you just download data from your accounting system, then you have like 10 tabs and you map the tabs, you delete columns, you clean some lines, you can ask any Genai tool. So you can take ChatGPT or Gemini and you say, this is what I'm doing every day in my file. So for example, I'm deleting always the last column. Can you write the script that does that all the time so I don't have to do it manually? And then it will give you the Google Apps script and you can add that in the Google Sheet and just press play and then this is done for you automatically. And once you have done this mini step and you see it works, and I always recommend start with something super small like this, then you can be more ambitious. You can say okay, now filter out only from one company. So I want to get rid of all of the other lines that are not from the company, Acme incorporation. And then again these steps which maybe takes you five minutes, but if you add all of these five minutes at the end you have a script that will do all of this cleaning for you. And that's where you save time. And the third is also being aware of all of the tools that exist that you could incorporate in your environment. Because this is what you can do with Excel with Google Sheets. But a lot of tools like all of the accounts payable process, you are not going to build a big app yourself that gets all of the scans of the PDF, then use OCR then code that you could, but it's not your role to do that. And then it's more getting aware of what is the best app right now based on your needs, but also based on all of your tech stack. And that is moving so fast. That's why Talking with other people that already implemented the app is something where you are going to save a lot of time and if it works well, you are also going to save a lot of money for your company.

You said something earlier when you were talking about productivity, about using ChatGPT as your assistant. Does having AI change? And I know you have a team. Does using AI change how you would have built your team, like pre or post AI? Like does it replace anything that you may have hired out before or impact that?

Your question is really well timed because last night I couldn't sleep. ChatGPT just released the image generation. For people who know me, I did a lot of infographics on LinkedIn. Some got millions of views and that's how I grew a lot. And when I tried and I put my infographics inside ChatGPT image and I just say okay, do this infographics. So let's imagine 100 Excel shortcuts and now I say do 100 PowerPoint shortcuts. It could give me exactly the same templates of visually and on top the content inside. So the content was not perfect, but it was still 80, 90%. So what we used to take hours to build was done in 30 seconds in front of me at and that's a problem with AI is often only 80, 90% okay. And I'm like, I was like, okay. My designer, like now either his job is changing, meaning he's the person who is going to use ChatGPT to do it, or if he cannot do it, then I will hire somebody who has maybe less design skills in Canva, but who can just be more efficient and maybe make the prompt right that the output is 99% correct. And that's like I have always these reflections in my company is really like we have to be AI first because we are teaching that. And it's interesting that I have to push still my members and my team for this. So I think it's not that at the beginning I will have done something differently, but by each change I'm rethinking how we work. So my designer now is job is going to change, that's for sure. And if you cannot change, I will have to hire somebody who will change. And that's the fact for finance as well. Like if you don't change, then other people who will just be more able to use AI will have more advantage in the market. And I also hired a developer. I never thought that I would do that because we are not a SaaS business, but I hired a developer to work on data to create a system where we can use all the data. We have to be ready when AI is good enough to customize everything we do to each subscriber. And that's like we are not there yet, but we are building more and more data, capture more and more systems. And my vision is if somebody downloads a PDF from LinkedIn, if I can know which because they give me their email address, if after I can know, okay, who is it really? Is it a CFO in the us? Is it maybe somebody who is living in the same city than me? Then the message that I will send after will be totally different. And I want to customize the experience based on this. And I think it's really possible. It's just I need to put in place a lot of processes for that.

Hey, real quick. This episode is sponsored in part by the folks at Teamup Team Up. They help you find talented accountants in the Philippines. Teamup's got a killer PDF guide to how to do this stuff. They call it their 2025 salary guide, but it covers way more stuff than just salaries. And one of the things that digs into is I think the biggest misconception about hiring folks offshore is the difference between outsourcing versus hiring direct. A lot of folks that have had negative offshore hiring experiences, what they're actually doing is working with an outsourcing group where they're buying month end closes or buying tax returns. And it's up to that outsourcing group to manage how it gets done. And the training of the team members and all that. That was not the model model of offshoring that I did. I did what Team up does. Direct hiring. All it is, you're working with human beings in another country and they're capable of all of the things that my onshore people are. At the end of the day, it's up to me to, to train them and kind of develop them from A to Z. But there's no like middle person. Oftentimes in these outsourcing groups you're paying. And I this was the case for me because I'd done both. You're paying that group pretty much the same amount as that person's salary. So like double the cost. I just want to work with the person directly. Team up will help you do that. Check out their guide covers a lot of just like kind of the questions you're kind of too, too embarrassed to ask. You can download that one down in the show notes. Hey, real quick. I write a weekly newsletter, goes out every single Thursday and let Me tell you it is a banger if you ever struggle to keep up with like a high news updates. Things are happening so fast Jason, where do I learn more? What is the most up to date tippy top hot goss in the industry and tech advice and all that? It's the newsletter buddy. Straight to your inbox Every single Thursday, 2pm Eastern. Thousands and thousands and thousands of thousands of accountants read it. I'll put a link to it down in the show notes. If you aren't on that list yet, you better get on it. Yeah, part of the challenge here is like how the fact that the team set up like the right answer changes every single time there's a, there's a new release and that's the image generation thing you mentioned. OpenAI just they tweet hey we're going to live stream at 11am Pacific and they announced this new thing and nobody knew it was coming. I mean some people had kind of had expected it but that's very hard to plan around and overnight that's is actually a great framing and I'd heard something similar from someone lately is it's getting to the point where I'm. I'm increasingly unwilling to employ people who won't lean into AI because your, your graphic designer, it's like well it only gets 80% of the way there so I probably can't DIY it still. But if, if they're not making use of the tool that gets them 80% of the way there then I now want someone who will. Right?

And for the story I had six months ago, I hired an assistant to manage my emails, calendar, client discussion and I hired somebody experienced because I wanted to implement processes I didn't have. So for example, how do you really onboard a client? How do you document meetings? How do you follow up leads? How do you answer to emails? And after three months I was still involved too much in my case. So I stopped with this assistant and now I have actually built AI assistants that are doing 80% of the job that she was doing. An example what she was doing is classifying the emails based on the importance. Is it something I need to read? Is it something I need to answer? Is it something for the rest of my team? For example, a customer has a problem to log in. Now I have an AI tool which is done with N8N and this N8N tool. So it's one of the workflow you can create. It starts by getting an email, then once the email arrives it will read so it will get the content from the email. And then after we will send this content plus a prompt. And the prompt is you are email classifier. Here are the four or five categories where you need to assign the category. And then we send that to the OpenAI API. So it's like me going into ChatGPT and coding in with a copy of my email plus the prompt just now it's automatic because it's with API. And then the answer is the label. So it will give one of the label that is in my. That I decided and then it will go back to Gmail and say, okay, Gmail now assigned this label to the email. And now with this, I have like 20% only work to do on only the emails that are important. And this cost me maybe $1 per day or even not even like 50 cents per day. And so that's like something where it's already possible now. And to your point, a lot of things I'm like, should I really hire somebody because I can do it myself or I can maybe train somebody in my team with AI to do it. And a lot of time I also push my team if they don't know something. I say, first go and check with AI and then be critical about it. But then make me a proposition with this.

So that tool you mentioned, n8n if you're not familiar with it, it's. It's kind of like a zapier. Like it's a custom workflow builder. And that's. I mean, so, so what we're talking about here is like this is getting beyond chat, which we have talked about on the podcast a little bit. Like the, the big opportunity to me with chat is getting your whole team on board finding the killer use cases, but then putting those on autopilot. Like building the workflow to where that stuff just happens. Like I just get a slack message with 10 tweet ideas every time a new meeting transcript completes. Like when I get out of me, like, like, don't make me go to ChatGPT and remember to do that. Like just make it happen. That's super exciting. But I think you find those by, by getting chatgpt into everybody's hands to begin with and seeing what are the, the most useful things that filter out of that.

Yeah. And for NH and what is good is either on YouTube, you check people who already built those workflows and those agents. And what is good, you can steal their templates. They give it often for free. So you can just use the template and adapt it by just entering your credentials for Gmail. Your API for OpenAI and at 90% it's good enough that you can just do it yourself. And I have one agent that I am now customizing. The agent is preparing me for my meetings. So it will read the Google calendar and will tell me you have a meeting with Jason in one hour. What is good is if it doesn't work, you can customize it a bit. Nobody gets angry here.

Yeah, or you still get angry at least it's just your fault at that point. Nicholas, thanks for coming and doing this, man. Obviously we will share Nicholas's LinkedIn down in the show notes your community. You want to tell them a bit about your community and who that's for.

Yeah, so it's for either CFOs or fractional CFOs or people who want to become some CFOs or fractional Cfo's. But the focus is how you become an AI CFO and in the community. So we have now more than 250 members is people from beginner to advance. So people also help a lot each other. And I bring experts because me, I'm teaching a lot, but I bring people like Christian Martinez, anatomina. I bring also people that are expert in their field. I have a chief data and AI officer of a bank. I have like for N8N I'm bringing an expert that is going to teach us how to do it. And the goal is really learn together every week. Also publishing new content, having live events to learn and having the place to become aicfo. Because alone, even myself, like I never learned that alone. I watch your video, Jason. I learn a lot from your videos. I watch experts from other fields and me, it's my job to learn. But a lot of people, they want to learn. They only have one hour per week. And I think people listening to us, if you have clients, you still want to be the expert in your field. And how can you do that if you don't spend 20 hours per week? Well, you can join the community because we share all of this and it's quite easy to consume as well because if you have the app on your phone, then go in the toilet and read a bit about AI for finance.

What a great. If you go to his community website. That's right, that's the hero copy right at the top. The best community to read from the toilet. Nicholas, thanks again for doing this, man.

Yeah, thank you. And it's great that you do that because I think people listening, it means already they understand that they need to invest time in their development and if they're listening to you. So continue like this one important note. If today you learn something and as I say you are here investing in time to learn but other people didn't listen to this podcast. Other people maybe like underestimate the power of learning and we need to bring them, we need to bring them with us. So make sure to share all of these learnings with your teams, with your colleagues because it's changing fast and I think if we are lucky to understand that we need to make sure that our closed ones and our colleagues we also bring them with us. If not for them it's going to be even harder, man.

That's one thing for me kind of the existential dread of employing people and them falling behind if I don't bring them up to speed. That's a very real pressure now I think. All right, man, thank you for doing this.

Thanks Jason. Sam.