244 Will A “Digital Employee” Be Your Next Hire?

Lots of AI news last week. And one thing Google dropped that kind of went under the radar. Something they called AI team members. Creating these pseudo people with all the data, like in your organization that you can talk with, you can email with, will hop into team chat. Some really interesting things in what they demoed that we're going to run through today that could impact the future of how we build out not only how engagements get done, but how we build, potentially build our org charts. So come on in. Nothing to be afraid of here. Let's explore this whole concept of an AI coworker. So every year Google has its annual developer conference. They do it once a year. It's like this is all the cool stuff we're most excited about. It's when the big announcements come. And to be totally honest, it was a little underwhelming. There wasn't really anything there that like knocked us off our socks. But there was one thing that was pretty interesting here that they teased. I'm going to play you a clip just so you can hear kind of how they frame it up.

We're exploring entirely new ways of working with AI. Now with Gemini, you have an AI powered assistant always at your side. But what if you could expect how you interact with AI? For example, when we work with other people, we mention them in comments and docs, or we send them emails, we have group chats with them, et cetera. And it's not just how we collaborate with each other, but we each have a specific role to play in the team. And as the team works together, we build a set of collective experiences and context to learn from each other. We have the combined set of skills to draw from when we need help. So how could we introduce AI into this mix and build on this shared expertise? Well, here's one way. We're prototyping a virtual Gemini powered teammate. This teammate has an identity, a workspace account, along with a specific role and an objective.

A workspace.

Let me bring Tony up, show you.

This thing literally has like a. So Google workspace is like the overarching, what they call the whole thing, kind of like Microsoft 365. It is an A AI like employee that has its own workspace account that you interact with just like you would anybody else on your team. Kind of an interesting concept. Increasingly, I'm finding that the easier way to work with AI is actually the way that we work with other humans. Like, part of what has me excited for speech getting better or being able to talk with AI getting more compelling. What gets me excited about that is, it's like our brains already know how to do that. We do it every single day, right? We talk with our colleagues. What we have never, ever done in the past is go log into this website and have to explain complex things in a chat box and have to do that whole conversation back and forth. Right? That's kind of a foreign thing. Like we will, like, text people and that sort of thing. But to work through big, complex business problems in some other system that you have to go log into and chat with it and it can't see all your other data, that's a pain. But working with an AI assistant in the same way we work with humans, I feel like that's a little bit more accessible, more useful. I'm gonna play one more clip here about how they set up this sort of like, quasi employee. Okay, so let me start by showing you how we set up this virtual teammate. As you can see, the teammate has its very own account, and we can go ahead and give it a name. We'll do something fun like Chip. Chip. Chip's been given a specific job role with a set of descriptions on how to be helpful for the team. You can see that here. And some of the jobs are to monitor and track projects. We've listed a few out to organize information and provide context, and a few more things now that we've configured our virtual teammate. Let's go ahead and see chip in action. So as you're listening to this, I'm looking at the, like one screen they use to design Chip, your AI teammate. And it's very, very simple. Basically, there's a text box for a description. The description for what this, like, employee's supposed to do is a virtual teammate who helps monitor resources, find potential problems before they happen, and make decisions when things are unclear. So that's the first description box. And then there's only one other box that is jobs and instructions. They've got four bullet points in here. Monitor and track projects, and then it tagged three specific projects, organize information and provide context, analyze data and identify trends and facilitate team collaboration. All very generic instructions, honestly. And what it looks like, if you're a nerd, is a GPT. So this is ChatGPT's version of custom assistance. Basically, just describe to it what its job is and what you want it to do, and then you can keep coming back and having a conversation with that assistant. It's kind of that on steroids inside the Google workspace, where it can see into all of the data in your ecosystem. But it is a Colleague that is designed to do a very, very specific job. And sometimes the hard thing with these demos is they can't solve super nuanced problems because Google is like the company for everyone, right? And so it's, it is a lot of general stuff like monitoring deadlines. So what they went on to demo basically three things. Inside of a group chat. The guy posed the question, does anyone know if you know, this specific thing was approved? And it's a group chat with a few other humans and this one AI colleague. And because that was related to one of the projects that it was its job to oversee, it chimes in immediately and says, yes, this has been approved and like provided the kind of the source. Next, in a different group chat, the human guy, the demo guy, asks if they're on track for launch with this specific project. The assistant replies, and it says, here's kind of a bullet point summary of where things at. And actually flagged one potential issue that could keep them from meeting the deadline. And then a different person in the team followed up in that group chat, asking it to prepare a doc summarizing workarounds for the issue that it had flagged. And I think the reason I like this is it's not like something new, it's something familiar that like can support us in the place that we already work. Like, we're used to working with colleagues and we're used to delegating jobs to people. And so it's maybe a little easier to get your head around how this AI colleague could be helpful. But a couple other things I've seen lately that make me more excited about what a colleague like this could be capable of. I saw a really interesting app lately. I think I shared it in the newsletter a couple weeks ago called BotX. The website is BotX Cloud. And basically what it does is it uses AI to like make decisions and workflows for you. So the way the app works is it's this big canvas with all these nodes, like kind of like a flowchart visualization. And it goes through all these different steps and it takes some sort of data in. But then you write in plain English, you say, if this is the case, go down this path. If this is the case, go down this other path. And it's not like if the number is bigger than 10 or the number is less than 10, it can be that it's more qualitative than that. So it's like if it looks like I have all the information for X, Y and Z, go down this next path and use this information for these subsequent steps. And it's just like a plain English flowchart of logic. Which is really interesting because this is in the end like how we explain to our colleagues or to an intern how to go through a process. And maybe the most meaningful thing that's actually happening here is AI is like making it so that you kind of just build software by telling it what you want. And so it's just like a hyper simplified version of building your own software. And the way you ultimately train it and tell it what you want it to do is actually the exact same same way that you would tell a person what you want it to do. So a few examples here. I want to start by giving you like an accounting example and a tax example of how we could use something like this in the tech that we already use every day. So take QuickBooks for an accounting example. Let's say QuickBooks had this sort of this element of a built in colleague, right? And I fully expect for this to become a thing because all of these software tools right now are thinking how can we make even more money by shipping cool AI stuff rather than just adding AI features to what they already have. I suspect what we could see is this notion that you can now like hire these quasi employees for you. And I think they may very well use this framing of like a colleague. Because when you're doing the ROI calculation of well, how much am I going to pay for this? That's very favorable for the software company, right? You want people in their head benchmarking the cost of this upgrade versus the cost of hiring another person as if we're not already paying enough for these things. But an example of this sort of colleague at work inside of a platform like QuickBooks, it can be as simple as telling it things like always, you know, add or match this type of transaction in this scenario, not unlike a bank rule, but you're just telling it like here's how you want it to handle it. So in a very simple form, it's like semantic or just verbal bank rules to call out things like always looking out for certain errors in like financial reports. So if you're reviewing a balance sheet or a P and L outlining the rules of like, yeah, if you've got this issue, we need to look into it and double check X, Y or Z. Or if we see this, it usually means that it's something like there's something wrong there. And they're all very small, like maybe bite sized things. But the beauty here is you build up this assistant over time to be a collection of like all of the things that specifically you are calling out. So imagine if you had this intern that could sit next to you all day, every day and you tell it these things to remember and it never forgets any of those things. That's kind of the idea here, this sort of digital colleague that you can continue piling more and more things onto and it can handle that stuff not only in a single accounting file, but probably across any number of accounting files. If those rules, you'd probably have to delineate between what is a generic rule versus what is like a client specific rule. But in the same way that we can just explain like verbal bank rules of how you want stuff to be matched, you can also do a verbal version of quality assurance. So what are the things to look out for? What are common errors? There's a lot of tools, not a lot, but there's a decent number of tools out there that do quality assurance where you connect them to a QuickBooks file. And in my experience, the reason why those tools don't get more adoption is that your version of quality assurance looks different than this company's version of quality assurance because they can only do like a canned version that isn't really super flexible. But you, you can come into every single file and say, these are the things I want you to double check every single month. And here's how to fix it. If this thing comes up or that thing comes up. And there's part of me that's like, when I hear that, like, oh man, I gotta like build that whole thing from scratch, describe every little thing to it. There's part of me that's kind of annoyed by that. The notion that you would ever build something helpful by explaining those things one by one. But on the flip side, I'm like, man, that thing becomes an asset over time. Especially if like my team members can use it and everybody is speaking into it. That's something that gets more and more helpful over time. So that the notion of this sort of, you know, let's say in QuickBooks, in Qboa, like at the accounting firm level you have all of your firm users, but let's say you also have this like AI colleague that everyone is speaking into training. I don't know, maybe it's an assistant just to you. I'm not sure what would make the most sense there, but that thing would get really, really helpful. Send me a message if a bank feed breaks. If you see X, Y and Z, fix it. By doing this, the platforms will build in like generally helpful things. Just like we see general quality assurance tools now that are kind of helpful, but for us to be able to have a tailored version of that that we customize on the fly is much, much more helpful. A tax example, if you're on a tax firm, we've got a growing number of these tools that'll do OCR on all the source docs that we chuck in, right? And pull all the information off the government forms and all that into a more structured work paper file and sometimes even input that data into your tax software. Now it's a big hot mess because you usually don't have complete information. You still have to double check the data and how it goes in. Oftentimes because of just how hairy tax software is, it may not have been entered the way that you actually wanted it to be entered. And then you've got issues with like, you know, mortgage interest, can go six different places and just all of those issues if you do tax work, you know, but still hopeful that those tools will do OCR that it'll kind of get you part of the way there on the process. This episode is brought to you in part by Team up, helping you recruit top Filipino accountants without any ongoing monthly fees. The difference between teamup and all the other offshoring options is a team up helps you hire staff directly. No middleman. You work directly with your new hire in the Philippines. Hire the person, not the company. Guys, gals, gang. Here's just a few reasons to hire directly. You have access to higher level talent. Makes sense. You have complete control over team culture and training. They keep 100% of what you pay them and it's a lot more affordable for you. So you can retain your team for the long term. Team up could source accountants with experience working at US or Australian firms familiar with tools like Xeroqbo and Dex. Also recruit specialist roles, team leaders, tax specialists, administrative assistants, thought experiment. What if you had an executive assistant for the first time this tax season? Just throwing it out there. What would they do? Start at that email video I did on the main channel recently. Get help with that stanky old inbox. I digress. Team up recruits these talented folks for a flat one time fee of 4,000 US American dollars. That's it. 4K one time. Somebody at Robert Half just did a spit take. Robert Half reference. We ever going to get Robert Half to sponsor this pod? Not anymore. And they can connect you with an affordable employer of record if you need help with payroll and compliance. Once you hire that person. Big fan of Hiring in the Philippines. You know I did a bunch of that. Check out the link in the description to learn more about TIMA this episode. It is sponsored in part by the fine folks at Life Flow. Tell me if you've ever had this situation before. Somebody needs some information from the QuickBooks file. Maybe it's an advisor, maybe it's like the financial advisor, some other stakeholder, a board member, maybe even the client, but you don't want that person to have access to the actual QuickBooks file itself. Or maybe you're at like number of user limits for your QuickBooks license. Man, I had this all the time where I wanted to give them like a subset of information but oh lord knows I do not want them to have full access to the Books Gang is actually a really good use case for Live Flow because you can selectively sync any like little detail out of the QuickBooks file to Google Sheets situation where we actually had this a lot. You've got somebody within the company that like manages ad spend, but I need them to tell me like what events certain ads are associated with and they need that data for their own analysis. But you can't give them the full P. And liflow can be a really great solution here to just get the information out of there that they need to see without getting them everything else. Now Lifflow does a whole bunch of stuff, syncs data out of your QuickBooks file to Google Sheets, can be a one time sync or can keep updating that stuff on an automated basis. They've got a killer consolidations product now where you can roll up theoretically an unlimited number of companies with different sets of chart of accounts all in the same like really simple, easy to use Lifflow interface. People are using this for like liveflow for everything from like managing month end closes, even internally. Like they set up all their work papers in Google Sheets. Kind of wild. That is LifeLow. Learn more about that one in the link in the show notes. But what do humans do when they come in to complete the work? Well, you've got kind of a a set of steps that you always do to fill in the void of what the software is not doing. You're gonna use your judgment and come in and be like what are the things that we're missing? There will be like systematically things where it's like well we had a prior year amount here. Nothing has been done to get the insurance expense for this rental this year. Like that's something where you can begin developing a sort of assistant or colleague for you to take this even further in a way that's customized by you. And so in this case, this sort of colleague is probably a component of either where all that data lives, like your work paper management system, or maybe part of the system that extracts the data from the source documents and kind of puts it into a work paper for you. And in some cases both those systems will be the same system. But this assistant is probably sold to you by that vendor and it's a collection of all of the things that you've ever told it and all the processes that you want it to go through. So if the very first time I run through it with the 1040, I give it three instructions, I say, anytime you see this San Diego thing on a W2, do this with it and annotate it this way. Anytime you see this type of real estate tax statement from this goofy county that we're in, double check that the amount that they used matches, you know, this, this amount on the form. Let's say you build in three things like that the very first pass when you go through it, the next time you start a file, this digital colleague has those three things in there already and it will do those things. And so over time, obviously this gets much, much more helpful, particularly as it is infinitely scalable. Right. And once you've built that thing out to be very comprehensive, or you as the firm say no, we're actually going to build kind of a single colleague that will be the starting point for everyone in the firm's projects. So you kind of centralize the development of it and then maybe folks can take it their own direction off of, off of that kind of base firm approach on a whole, across all of your projects. That's potentially a massive, massive time saver. Right? And I'll be totally honest with you, we've more or less got the tech right now to do this pretty darn well. We talked last week about how OpenAI announced a desktop app for ChatGPT. They can see everything on your screen. We're getting more and more assistance built into the apps that we use, usually on like a panel on the right hand side or something. But this is all the same technology that can drive this sort of like built in reasoning where it takes actions for you. Now it's all gonna get way better for sure as the underlying AI models get stronger. Supposed to have, you know, GPT5, the next big model from OpenAI we're supposed to have this year. And the step of that model is supposed to be similar to the steps of past models, which is to say really, really big, making it capable of much, much more. But there's a pretty compelling version of this that I would argue could actually be built today. We've already seen how GPT4 the like the current best language model that OpenAI has and that you use in ChatGPT, if you put something like a W2 into that, it is capable of extracting the text off of that document better than any OCR technology we've ever had in the past. But to my knowledge, every single, with a couple exceptions, almost all of the tools today that do OCR off of tax documents and put it into a work paper are still using ocr. So it's an example of where the tech is here, but like vendors are still playing catch up to implement a better version of this other places that this could be used. Almost certainly we're going to see this in our practice management systems. In fact, a really helpful, really practical use of this is managing just projects and deadlines has always been a nightmare. A few weeks back when we spent a whole week on work scheduling, one thing that came up when who was it? It was Vince Porter was telling us about their approach to work scheduling and how they bucketed all their clients into quarters and they deliver all those clients based on whatever kind of quarter they have them assigned in. But one of the things that they mentioned that he mentioned was they have in the firm a project manager, somebody whose job it is to be following up with clients to ensure that we're getting all the info in that we need in time to be able to get it out the door when the project needs to go out the door. And most of us have probably worked with a firm at some point that had this person back in the day, they were literally making the rounds, going around to everybody's offices, checking in on the projects that they had, making sure everything was on on track. This notion of a project manager, while done wrong, can be annoying and overbearing is really nice from the standpoint that it's like, okay, it's this person's job to make sure that everything's on the rails. You want to talk about a really helpful colleague that could be built into the practice management systems that we use. PMs today basically just give you like filtered views to see what's coming due soon. But they don't go as far as to say, well, we've got these outstanding requests that the client hasn't even gotten back to us with yet, but the project's due in three days and oftentimes for the accountant, we kind of just out of sight, out of mind. Don't even think about the projects where we're waiting on the client because it's easy for us to wash our hands of it and say it's their fault that we can't work on it yet because they haven't gotten it back to us. But oftentimes this comes at the expense of missing really important deadlines. I've had clients where I followed up with them a number of times. You know, a few times in the summer, and then we're getting to the extended deadline. I may not know how much tax they owe. I had a really, one really hairy example of this where two days after the extended tax deadline, they got me some info that made clear that they were going to owe a crap ton of tax. And we were like just a couple days past the filing deadline. So now they were getting late filing penalties on top of the penalties to not pay the tax in. And it ended up being this astronomical penalty for what was less than a week of them not getting the information that we need. And I hadn't followed up with them in months because I'd followed up a few times prior and hadn't gotten anything back. And so I was like, well, it's their fault. And I think in total, I'd followed up with them maybe three times and hadn't gotten anything back when if I had a, like a project manager that understood a degree of what was actually really important and maybe what was less important. And even if that project manager could like follow up for me. So it wasn't this uncomfortable human thing where this person keeps messaging me every single time. And after a certain number of times, it's like the social discomfort that probably stops you from following up more. If I've got a project manager that can work backwards from the deadline to tell me, like, okay, like, it's very important that this stuff gets in within this timeframe. You need to contact these people. Or if you want, I can contact these people for you. That's so much better than just the like grid list views that we have today of just project deadlines, right? So you could totally see a colleague that is like a project manager colleague. It lives in your practice management system and literally its job is to do what that person used to do. That would walk around to every office and say, okay, give me all your projects. Where's everything at? How are things coming along? That's now like an AI colleague that can help everybody with that inside of an accounting firm. I could Absolutely see this. And I could see a PM like rolling this out and being like, you can add this as basically another user to your practice management system. And part of me, like the, I mean, where the pricing and how they monetize this comes down. This will be really interesting to see. And I'm a little afraid that it could be cost prohibitive. Maybe that's the wrong outlook. I don't know. Maybe that is a really important job. Like, if that's doing the job of the person I was paying to walk around everybody's office, then maybe I shouldn't be bent out of shape if it is expensive. But there's a big part of me that's like, man, we could have this like before next tax season. Like, this isn't. This is possible with today's technology. And then the last really interesting example here is what it could look like to develop these sort of AI colleagues in the context of our clients, businesses. I mean, how many clients do we have where we come in and they have like no standardized process for reimbursements or receipt management? All of these things that are like 101 for us, card management. And we come in and we help them kind of develop a better system or we just take that work over for them. Imagine being able to help your clients, whether it's inside of Microsoft 365 or Google Workspace or QuickBooks or whatever it is. Imagine being able to come in and help for your clients develop these sort of AI colleagues to hold the whole team accountable to, you know, whatever the processes are that, that everyone has agreed to. You're doing all the hounding and following up and all of that stuff that you used to do. But with this AI teammate, imagine how helpful us accountants can be coming into client situations and setting that stuff up for them or helping them get that set up. Like, at that point, we're genuinely pretty much building software that is bespoke to them. That's a actually really cool, really high leverage opportunity for accountants. And just like almost everything else, I mean, especially the folks that tune into this podcast, like, we are generally so far ahead of small business owners on how progressive we are on tech and security best practices and all these different things. And so if we are starting to lean into this stuff, you better believe we're going to be ahead of the curve with our clients, which creates a massive advisory opportunity. The idea that you could come in and help your clients develop these kind of AI teammates to be wildly more productive. Now that's all really cool, Jason. That's exciting. Like ultimately, how does that impact me today? My thinking is this, this probably pulls forward a little bit my expectation for some really impactful things that we could see from our tech partners. Normally we're seeing AI framed through the lens of like, oh, here's a chat assistant or here's this feature made slightly better, you know, like email summaries or generative email or something like that. But the next stage of, of AI coming into our work is, you know, AI agents is the vernacular we always hear. And this is this whole AI teammate concept is an example of an agent in action. And there's something for me that is, that's easier for me to get my head around when it's functioning like a person. There's something a little more accessible about that rather than this like new type of bot that is going to just do things based on, you know, what I'm telling it to do. And it's like, okay, is that happening on my computer? Is that happening on a software on a server somewhere? Like, exactly how does that come to be? As opposed to here is an AI teammate. I can assign tasks to it, I can teach it new things on the fly. It can see into the same a system that I'm using. If it's like inside your practice management system or your accounting system, that's really exciting and that's, that's a, a very, very practical example of how like tailored, specific to us AI can be really helpful for the pro. And it's not to say that product companies and, and bench and QuickBooks Live bookkeeping and all these, these, you know, TurboTax, it's not Sally's other services won't be doing similar things. But when my clients have specific problems, this is an example of AI actually making the professional wildly higher output. This episode is sponsored in part by Cloud Accountant Staffing. Tell me how this resume sounds. Graduated with an undergrad in accounting in 2012. 14 years experience now the last five with US public accounting firms. Software experience, QBO, Xero, Netsuite, bless your heart. Bill.com stripe, Shopify, Gusto, Justworks. Rippling full cycle accounting. Oversaw the monthly close and review. Onboarded new clients, coached and trained staff. Oversaw a small team of bookkeepers getting stuff done. Not bad, huh? That is a real resume from Cloud Accountant Staffing. A super talented accountant in the Philippines that could join your team. Not this person specifically because this ad read might be old but to find the accountant of your dreams, all you gotta do get on the horn with Cloud Accountant Staffing. Talk about what your needs are. They've got recruiters on on the ground in the Philippines. They'll find you somebody great. You get some resumes, you do some interviews, you want another wild thing? You don't pay a dime until you decide to hire somebody. Literally. What do you have to lose? The only reason you're going to end up cutting a check to Cloud Accountant Staffing is if you got somebody that you absolutely love. So why not? I shared before I hired a bunch of people in the Philippines. Completely changed how we approached staffing our onshore firm. Give it a try. Link to Cloud Accountant Staffing in the Show Notes this episode is sponsored in part by Melio. If you have small business clients, and I know you do, you know just how hard it is for them to track all their payables and receivables, especially when they're doing it manually. Now there's an easy to use solution that turns all that tedium into an easy task that only takes a few minutes each week. Melio is a B2B payments platform that saves you and your clients many hours each month on bill pay by offering robust payment capabilities including advanced approval workflows and a two way sync with your accounting software. Also helps maximize cash flow by allowing you and your clients to pay vendors however they want to get paid, including instant transfers and per payment financing. They can also use Melio to pay international vendors. Can all be done in minutes and you can more easily keep track of everything on your end on May 21, set your calendars. Meo is hosting a webinar for accountants and bookkeepers where they'll cover some exciting updates to their platform that includes new features, product improvements and more. What could that be? What's in the more you think they'll also answer any questions you may have helping you set up your account to ensure a smooth onboarding process. I'll put a link in the Show Notes where you can sign up for that webinar and get to know this platform. That's a game changer. Spots are limited. Make sure you claim your seat asap. Thanks to me. Leo, Check out that link to the webinar down in the Show Notes. I was listening to an interview today that was kind of saying it was actually Sam Altman, CEO of OpenAI. Seems kind of saying like everybody's in love with the notion of this sort of like runaway super fast, crazy aggressive AI growth strategy, but that it will probably all happen on a slower timetable than we expect just just because of like the inertia of the world and how Things get done today. And they were talking about it through the lens of maybe the risk of like, runaway AI being super, super helpful and it displacing a whole ton of jobs really fast. He's saying maybe over. Over the time horizon of a decade, like, you could see, like, big impacts like that. But he said his hypothesis right now is that because there's just so much inertia in the way that the world works, it's almost certainly not going to be this overnight. A new thing comes out and, like, entire markets change just like that. And think about the work that we do. Like, that seems pretty darn reasonable, right? Like, that actually seems pretty accurate. There isn't a thing that's going to come out tomorrow and create a correct tax return or a perfect month end close. But I can see how a really helpful system assistant that we can develop and, you know, instruct how to do new things, and it remembers all that and it works in the tools that we already use kind of alongside of us. I can see how that can make us wildly more productive over time while still having, like, the professional's hand kind of guiding things and ensuring everything's coming out the way it's supposed to. I know something about that AI teammate. Teammate framing that kind of, like, sounds like it totally makes sense for the type of work that we do. Everybody likes to jump straight to the black box. AI that's capable of anything. And I don't know, maybe that exists or appears overnight someday. But the more logical progression to me seems like this sort of thing where we are crafting sort of our own assistance on the fly that will do what we already do, but in an automated way, like with software. Like, I'm telling it every time I open a tax return or every time I open a month end close. These are the first things that I'm doing. Cool. If I can tell an assistant to do this. And it remembers that, and it does that for me every time that I start a new project that feels like a very logical progression from where we are today to where AI could take us. And honestly, much more helpful than, like, this chat assistant that kind of just lives over on the side of an app and is ephemeral and it doesn't remember anything like that colleague that is more built into the platform that I'm almost instructing as I go through that work. Like, that makes a lot of sense to me. In fact, speaking of AI teammates, let's just bounce something off of AI Jason here. This is a bot that we have that's Trained on all the episodes of the podcast. Supposed to be a reflection of me and all the things that I've ever said on the podcast. Almost like an AI teammate. Right. Let me bounce this concept off of him to see if he has any other thoughts. Maybe we aren't considering around how this changes the client relationship. Hi, Jason here. How can I help? Hi, Jason Bot. So we were just exploring a new concept from Google about AI teammates. The notion that you have these assistants in your workspace that you talk with just like you would any of your human colleagues. Curious what your take is on how this can change? I guess what client engagements look like, like what the client relationship looks like. Particularly if we could even help our clients set up AI teammates to make their own finance processes more efficient. Oh boy, this is a juicy topic. Let's dive in. The idea of AI teammates is super intriguing, especially when you think about how it can reshape client engagements. Imagine this. Instead of clients waiting on us to get back to's with answers, they could get instant responses from an AI teammate. This could be a game changer for efficiency and client satisfaction. Think about it. Clients could ask an AI about the status of their tax return, pull up past communications, or even get quick advice on common financial questions. This would free up our time to focus on more complex high value tasks. And for clients it means faster service and fewer bottlenecks. But here's the kicker. The AI needs to be smart enough to know when to loop us in. We don't want clients getting generic or. Or incorrect advice. So an advisor in the loop model where the AI handles the straightforward stuff and flags the more complex issues for us could be the sweet spot. Okay at it. That it kind of trended back towards some stuff that we've talked about in the past, which is more AI and like the client communications support. And I do think that's helpful. I guess I hadn't thought about how an AI colleague in my firm, you know, in the, in the Google workspace example, it's like an actual user in the workspace with an email address. I guess I hadn't considered what if this is something that my clients could even email? Is that interesting? I don't know. It kind of hit the nail on the head with the whole notion that it comes down to its confidence level in the response. Sometimes it'll ask a question and the AI is like, yeah, no, I've got that right here. Like that's easy. Other times it could be kind of fringe where it's like, I want you to Ask me, but what would the interface for that be? Like, would my client just email with this AI teammate? Or would it be what we're already seeing with some support, like, approaches, where it emails me but then gets an auto response? Kind of like the auto response that you get when it's like, hey, okay, we got your ticket number, blah, blah, blah. Here's what we think the solution is. And if we answered your question, click Resolve here and we'll close out the ticket. For example, the client emails me, but then Chip, my AI teammate, replies to the client and copies me and says, hey, Steve, check this out. I think here's the answer. There you go. Is that helpful? Is that weird? Is my client going to be pissed? I don't know. Kind of interesting. Time will tell. I was in Austin at rightworks last week and one recurring trend that kept coming up, there was like a big sort of AI keynote from like a non accountant. I can tell you a little bit more about that in the Q and A on Friday. It was a little bit doom and gloomy, but it was from a person outside the space. One thing that kept coming up at the conference was we're really fixated on how AI potentially impacts our accounting firms, but we're not really thinking much about how AI could impact our clients. Like, I could be a big brain AI nerd and my firm will never be in trouble. But what if all of my clients have like, turned their brains off to AI and their businesses get disrupted? It doesn't matter how cool I am, if all of my clients get disrupted, I'm straight back to square one. That's problematic, right? And so, so much of this is like becoming core to the way that we work and build businesses. That it's. And like, it feels like it's gonna be real hard to be a good advisor unless we are plugging into this stuff, at least to a degree right now. We are not at a stage today where anybody's running an accounting firm that's twice as profitable thanks to AI. Like, we're just not, like, it's not at the point where you need to clear your calendar and go spend the next week just deep diving on all things AI. But it is to the point where I think everybody needs, in their sort of information diet, like a couple sources that are giving you good sort of practical, everyday use cases, right? Like, we don't need a huge volume of this stuff, but everybody ought to have like one or two, like solid follows, not the like engagement baiting, like, oh, AI just killed this type of follows, but more the like practical. Here's how to make sense of what we're seeing in the news. Like, I almost feel an obligation to talk about the OpenAI announcements and the Google announcements from last week because there is so much engagement baiting going on and so many news stories about groundbreaking this and that that they just announced. I feel a degree of obligation to be like eh, for what we do. Like nothing that's super is going to set our world on fire in the short term. When I say set our world on fire, I mean like in a positive sense. But it would be good to know if it was a negative sense also. So like these days I feel like you just need a couple of those folks that you're following and to not be afraid to have these conversations with clients too. You know, just like when we went to the cloud and this is way bigger than the cloud transition. But these days, I mean you can hardly advise a client on how to build their finance tech stack without talking about cloud software and how to integrate your apps, right? And so it's not about being an AI person, it's about like just kind of the future of knowledge work and not being like a huge, I mean AI rocket scientist versus just knowing enough to be able to ensure that you're bringing your clients along too because they're subject to, I mean people are telling our clients all the same things that we're telling us by and large that, you know, AI is kind of putting us at risk when these days I don't really think of it as putting us at risk as much as it'll definitely change what we do. And so the folks in that scenario that are at risk are the ones that are unwilling to change what they do or hiding under a rock and not paying attention to like better tools to do that job that enable you to then like do more meaningful work. Okay, interesting framing there that Google shared around AI teammates. If they release future updates for this, I'll let you know they said that they're quote unquote prototyping it right now. Anytime a big company like this shares this concept also it can, it can spawn kind of a group of startups that are like, oh yeah, we're going to go do our version of that now. I talk with a bunch of folks who are building quote unquote AI agents for accountants, but they're all still very early days when I talk with them and struggling to find like what is the compelling problem that I can solve. The people who are probably in the driver's seat here are the ones that already have the platforms, already have the data, your practice management systems. Like how can we create an AI teammate that does something helpful? I suspect we'll probably see it from folks like that first. Okay, that's my AI ramp for the week. We got some pretty solid stuff, non AI related coming up the rest of the week. Any questions on all that stuff? Anything doesn't make sense. Want to get the crystal ball out? Drop a note in the comments. I'll see you tomorrow, Sam.