Welcome to the Escaping the Accountants Trap podcast. It's a podcast to help accounts and CPAs and bookkeepers escape what we call the accountant trap. It's where accountants are not getting paid for their value and are forced to work long hours with high, demanding clients with little pay. Well, how do you escape the trap? One way is the topic of today's episode, and that's by leveraging technology such as AI.

To help me with the discussion, I've invited Eric Elstein, the co-founder of DACA and AP automation software. Eric, welcome to the show. Adam, it's great to be here. Thank you for letting me spend some time speaking to you today. Yeah, I'm excited to talk with you because you're the co-founder of DACA. It's a it's a software that helps accountants and bookkeepers with automating their IP.

We'll get to that a little bit later. But you are a technology person and you work with accountants. So that's one of the reasons why we wanted to have you on, to talk about how the role of technology, the role of things like AI in the future as it relates to accountants. So let me let me ask you the very first question, just to to eliminate any confusion.

What is AI exactly? I don't think it's a simple answer, unfortunately. There's AI and there's machine learning, and there's all this, like technology that gets very confusing. AI is the ability of a computer to be able to make decisions on their own, where machine learning is, the ability of humans to be able to program and for the computers to learn how to improve as it goes on.

So there is a difference between AI and machine learning. And I think often people get very confused between the terminology. Both of them are making automation happen, but they're all doing it in different ways. Interesting. Okay. So essentially AI is the ability for the computer to self learn to train. Yeah. Machine learning. Okay. And then machine learning is what I guess.

What is the difference again. So AI's the machine learns on its own and become smarter on its own. A machine learning is preprogramed with rules, and it becomes smarter by following the rules that have been programed into it. Okay. All right. So look at here's an example. If you look at Chuck GPT, GPT is becoming smarter on its own by feeding information in with the other ways where you can feed a whole bunch of rules into a system, and the system will become smarter, but it won't be able to actually learn more on its own about new topics.

Got it. Okay, so just to be clear, chatbots GT is an example of machine learning where it was fed a series of of rules or inputs, and then it just gets better at understanding and delivering information. Is that right? So I could actually be incorrect. I see ChatGPT as AI where it's being fed the rules, but it actually is able to then start thinking on its own about how to actually give the best answers to people.

It's not only taking the rules and just focusing on the rules, it's actually becoming smarter and learning itself how to actually build upon what it learns. So the best way of thinking about it is an AI is more like a human being. A machine learning is about very sophisticated rules and programing. Got it. Okay, so in the accounting world, what is an example of software that most people know that is using either machine learning or AI?

So the best example would be someone like Docker which is us. So we've looked at now millions of different documents and we understand on the document exactly how to be able to actually pull the information out of the document in the right way. And if something doesn't happen, it's like the date format is a very practical example. There are so many different variations of dates this month a year, this year, Monday.

There's dots, there's hyphens, there's dashes. And how does a computer know? By looking at a document whether to put the month a year, or whether the dots actually are showing a date. And that's what machine learning is in all context of Docker. We've basically programed thousands of different variations just on that date property of that date field, in order to be able to look at any single document and be able to ascertain whether that particular piece on the document is the date or not.

And if it is the date, should we be pulling it as the month year or the year month? What format we should put it? So that's a good example. I think, of machine learning.

Interesting. Okay. So it's essentially the machine the computer or the software. In your case, the software is actually taking a lot of the, the the menial task away from a user. So the user can actually focus on higher value tasks. Is that essentially the idea? Absolutely. You know, there's so much grudge work in the world today, especially in bookkeeping, accounting.

And I've been in the tech space now for a long time. And I think accounting, a bookkeeping has been left behind. I think that a lot of the other industries progressed really fast using technology like machine learning and AI, and I think that even today, we still see bookkeepers in the content. You walk in the office and they've got rooms full of leverage files with documents, and then you've got other accountants where everything is automated.

The documents are coming in via email. They PDF documents, they being pulled into a system like Docker. The data is being extracted. There's a recommended bookkeeping entry. The accountant looks at it and they use their obviously their accounting background to decide whether it's right. And they click a button and everything is done. So you've got these two types of accounts.

The bookkeepers today, one that is spending all the time doing number crunching and data gathering, and you've got other accounts and bookkeepers that have basically, really fell in love with the cloud and fell in love with technology. And they now have all this available time to add value to the businesses that they providing services to. And that's exactly where I wanted this conversation to go, is to see how we could understand first understand what AI or machine learning or whatnot is, and then and then paint a picture of how it could help the accountants or bookkeepers actually escape to the trap, get away from doing the low value stuff, start doing the higher

value stuff so you can get paid for it. So where do what is your vision? I mean, you created DACA to to be this this essentially this helper to accountants of bookkeepers in a way. So on a global scale, where where do you see AI and machine learning in the future as it relates to accountants and and bookkeepers?

So maybe I'll give you two different stories. The first story is that when I was doing accounting myself, I used to spend my whole day basically collecting the documents from the clients. I used to go back and forward with them. I had to try figure out what the problems were. I then had to basically print everything out. I then created the bookkeeping entry.

I filed it into labor orchards. I took it to a different room. It was a very, very manual process and I wanted to try spend time actually helping my clients and not spend all the time actually just doing this number crunching. And then what happened is a couple of years later, I left the accounting field and I used accountants myself, and interesting thing is the same problem that I faced, I was facing with them because I didn't want them to just give me a trial balance, income statement, balance sheet and hand it to me and say to me, here's your numbers.

It meant absolutely nothing to me, maybe slightly more because my background was accounting, but I wanted them to be able to look at these numbers and analyze these numbers and say to me, are you spending too much there? And you should be changing this and brainstorm with me and add value to me. And unfortunately, what I was paying them was going into basically them creating the monthly report to me.

And so we really created Doca to save bookkeepers and accountants time. We want all this like grudge work, this manual work, this waste of time, this back and forth, this filing to actually be removed so that bookkeepers, an accountant can provide maximum value to their clients. It's really as simple as that. Hey there. Adam here from the Escaping the Accountants Trap podcast.

I'd like to personally invite you to a free masterclass that we're conducting this Thursday called How to Start a CFO service. To register, just go to the CFO project. Com and click Free Training at the top. See you then. I like how you I like that example because it highlights what business owners or your clients really want. They just want you to view the accountant or the bookkeeper to understand the numbers for them, and then just tell them what to do.

Just be their guide. And you know, what's absolutely fascinating is that when we started the business, we believed, and I think a lot of the clients that we worked with and the accountant, the bookkeepers believed that a lot of the number crunching and the time wasting was coming from the processing side itself. So taking a document and creating the recommended bookkeeping entry and then entering it into the accounting software that ERP.

And I think is a lot of time wasting there. And Docker saves a lot of time there. But what we discovered along this process is that the overall process itself needed to be streamlined. So when you think about it, the documents could come in through a shoe box, which is becoming less and less likely these days. But when it comes in by a PDF, you often still need to print out the PDF.

And then if you need an approval on it, you're going back and forth to people's offices or on the phone. If there's some discrepancy, if there's a PR involved with the numbers don't match you on the phone, phoning people back and forth or emailing them, they not available. And so when you finally get the auditing you create the recommendation.

Then you need to upload the document into the accounting software of the ERP. And it doesn't stop there because after that, a year later, the bank then asks the client for the document and they have to go and try to find where do they store this in Dropbox or OneDrive or in this library file? Really? Yeah, it really is a bit chaotic, the whole process.

And so what we realized is that processing can be streamlined and it can save a huge amount of time, but there's a lot more around that. This whole process about the collection, the approval and the document management side. And so what we did is we built one system that handles all of this together.

So can you give us an example of one of your accountants that are using your software. How their practice is transformed. Like what what were they doing before. And now what is their practice look like now. So I guess there's two different types of practices. There's the one practice we have started using doctor which are more I guess you can say old school that had the files in their offices and they were collecting a lot of shoeboxes.

And it is a big challenge for them because they're not often used to software like Docker, but they're also not used to cloud accounting software often. And so Docker goes hand in hand with cloud accounting software like zero or Qvo or. Net, which is this one where a lot of the clients might be using a software like QuickBooks desktop, and they're not using a remote version of it, and it's still very old school.

So in that way it's like an entire transformation. The business is no longer leverage files. It's no longer approvals. Everything becomes digitized. It's what we call a digital transformation. If the companies are already using cloud accounting software and they're already used to more of a technological advancement, then I think Docker just makes their lives a lot easier by filling in all the gaps.

How to collect the documents quicker and easier. We've got many ways of doing it. How to create the recommendation so they don't even need to think about it. How to upload it automatically into the ERP accounting software. So I think for people that already on the cloud, it's easier to start transforming into full digital transformation. But actually one of my favorites all when you get these people who have these rooms full of leverage files and they are old school, and then they move into Docker together with, let's say, NetSuite with zero cubo, and you can just see the way that their lives change because they free up so much time to be able to

add value to their colleagues and clients. Oh yeah. And you know, in at least in my experience, most accountants and pretty much all the counties that I've talked to want to add value. They want to they want to do less of the transactional compliance work and more of the value add that they know their clients really want. So it sounds like leveraging technology will help them get there.

But let me ask you this on a on a larger scale, do you think I because this is this has been a hot topic in our industry. Do you think AI or machine learning or whatnot will ever replace accountants? The million dollar question. I remember that you've been asked this question basically from day one, and I remember looking at a website years ago, and I wish I could remember the name of it, and it actually went into, an article about how accountant bookkeepers will never get replaced because there's always going to be a need for someone to support the business.

And if you look at the roles, like in a bigger business, you have your CFO and then your controller and then your head up your different departments and then your team under it. All that's happening is that that bottom level of people is moving upwards. So they moving, for example, from an AP assistant into an AP person and the other roles are moving up.

So each of those is elevating their knowledge and elevating the value that they can give to other people. I personally don't think that bookkeepers accountants will ever go away. I think there's always going to be a need for it. I think that businesses will always actually need to know what's happening in the business. And the more you know it, the more you analyze that, the more you talk about it, the more the businesses can figure out what's working or what's not working.

And that's the difference between failure and success. So I just think that what's happening is using this accounting software, such as cloud accounting software such as Docker, the way the industry is working is transforming. And I think it's better for the industry as a whole because it allows the accounting bookkeepers to provide much greater value to the businesses, which means the businesses can become more profitable, they can pivot quicker, they can make better decisions, they can become more efficient whether 20 or 30 or 50 years from now, this will all be automated.

I think the only way it will happen is if the entire world becomes AI driven rather than machine learning driven, which means that human beings won't do anything. They won't be CEOs. They won't be doctors. They won't be doctors. It's basically at this particular moment, I think it's probably rational to think about it. Will it happen 50, 100, 200 years from now?

You know, technology is changing so quickly that I can't tell you what's going to happen 50 years from now, but ten years from now, bookkeeping accountants will definitely move up the food chain and they'll become more value add partners rather than number crunchers. They definitely will not go away. Yeah, yeah. And I agree that makes sense. I because if you think about it, what business owners or clients want from their accountant, a bookkeeper now is to be their business partner is to be their guide, their confidant, their advisor.

And, you know, it sort of reminds me, have you seen the show Mad Men, the, you know, the the fictional advertising company set in the 50s and 60s? Well, when the show first started, it was in, I think in the late 50s or maybe early 50s, but they had pools of secretaries that today with all, all 30 of them will be replaced by one computer, you know, and Microsoft products.

And that but the, the, the managing of the business itself is still needed as long as there are humans buying things and humans owning businesses, they need an advisor, another human advising them, and that human can and leverage technology. The advisor can leverage technology to to, to elevate their job, help their job run smoother so that they can provide the client what they actually want, which is advice on how to have a growing successful business.

So having having said that, I do think that technology is moving very quickly. When I look at our industry that we're in, we've seen changes probably on a monthly or quarterly basis across the entire industry, and we finding the industry is progressing extremely quickly and extremely fast. And I do think that it's really important for bookkeeping accountants that have practices or running small internal teams for larger businesses, that they do embrace the technology because even though I don't think bookkeeping, the contents will be obsolete in the next 20, 30 years, I do think that bookkeepers need to really embrace the new technology, because businesses will require the bookkeepers in the countries to have the skill

set, which is really interesting from our side, is a couple of months ago, we saw thieves of bookkeeping accountants, and they're actually starting to mention staff as a skill set. So in the old days, you would have Excel and Microsoft Word and others. And now we were looking for some thieves for a particular role. And the people that applied to us, some of them had docket as a skill set on their CV, and both the accountants each embraced not only the technology they need to embrace technology overall in order for them to become as efficient as possible.

Yeah, I love it. Well, Eric, we're almost out of time here. Where can somebody learn more about DACA and that they have and start the process of of automating their practice? I think the best thing is to go to the Docker website, dotcom and there's a lot of information. We've actually got a fantastic content team. We've written hundreds of articles about everything from AI to becoming a better outsource to content company to becoming a better CFO.

We've got checklists. We've got a lot of information on the website. And once you've gone through it, fill in the form and book a demo with us. We do them on zoom. It takes 30 minutes. It's not just us demoing the software to you. It will be interactive. You can ask questions, we can have a discussion about it, and you can actually find out more about not only about Docker, but about technology as a whole.

So come, come and spend a bit of time with us 20 30 minutes and let's have a conversation. We can show you what we're doing, and we can also maybe give you a little bit of input about what we've discussed today as well. Excellent. Well, Eric, thank you so much for coming on the show today. And to everyone listening and watching.

Thank you so much for spending the last few minutes with us. As we discussed how to escape the encounters trap. Bye for now.