Budget Battles, Politics, and AI: CFO Anna Tiomina

Anna Tiomina has faced multiple FP&A challenges in a 15-year finance career. This has included budget nightmares, all-nighters, and the stark realization that “politics” is central to any FP&A or finance role.
The former CFO of Sandoz, a huge pharmaceutical company, describes her move to finance chief at Softeq, a smaller IT and consulting firm. Most recently she has pivoted to become a fractional CFO helping finance professionals bridge the gap between “curiosity and confident AI adoption”. In this honest and frank interview, Anna describes:

Welcome to FP&A Today, I’m your host, Glenn Hopper. And joining us today is Anna Tiomina. Anna is an accomplished finance leader with over 15 years of experience. Anna has held key roles such as Chief Financial Officer at Softek and is now the founder of Blend to Balance, where she combines her expertise as a fractional CFO with her passion for AI integration, she has guided companies through complex budgeting cycles and financial transformations across multiple locations, all while leading distributed teams. Anna is here to share her unique insights into the challenges of FP&A budgeting and the evolving role of AI and finance. Anna, welcome to the show.

Anna Tiomina:

Thank you for having me. It’s a pleasure to be here.

Glenn Hopper:

We’re gonna get to the AI stuff. And it’s funny because I always, I get very, you know, just with my background, I get very excited when we have guests on who are equally as excited about ai, but I’m realizing as this goes on, that’s getting to be pretty much every guest. And if you’re not excited about AI right now, I’m wondering what rock you’re living under <laugh>. Yeah.

Anna Tiomina:

People are not there yet. So you were looking in a bubble. Sorry to say that.

Glenn Hopper:

Yeah, well, you know, and that’s actually, and that’ll be fun to talk about too, because, you know, as finance and accounting people, I think we are inherently risk averse. So there’s still a lot of people out there who are thinking, I’m not ready for this and all that, but it’s

Anna Tiomina:

Changed people. Yes. Yeah.

Glenn Hopper:

Alright, well, we’re gonna get to all that, but I guess before we do, um, kind of walk me through your, uh, career journey and how you came to the place where you are now, where you decided to go, go out on your own and do the fractional CFO and, and and AI integration consultant.

Anna Tiomina:

It’s actually not that easy to remember, but I’ve been a full-time, CFO, pretty much classic CFO role. And I spent five years in a huge pharmaceutical organization, a corporation with offices in like hundreds and 50 countries, A huge organization. And they moved me between the roles because this is what corporations do. And then I switched to a much smaller company, uh, that was doing ai, um, was doing IT consulting and software hardware development. So a much more technical company, but also much smaller. Both of the companies had international setup. So I was involved in a lot of inter-country activities in both of my roles. And I spent another five years in this IT company. And, um, early this year in 2024, they laid me off actually as a part of a big restructuring and, uh, as a reflection of what a lot of companies in the tax sector are now doing.

And somehow I got other companies contact me, and my ex company is actually one of my first clients as a fractional CFO. This is a very common story in a fractional executive, uh, story, right. So, um, somehow I naturally started to get companies contact me and, uh, I started this fractional CFO business, which I thought would be just a, something in between the full-time roles. And, uh, since I was, I got some time, like some time capacity during this period, I thought, okay, what should I learn that would increase my value on the job market? And the job market now is not really easy as a lot of people know, right? And, uh, instead of getting another certification, I thought, okay, what’s hot in there? And AI was really, really hot. And in this, um, tech company, there was a lot of innovation around. So I was very open to like looking at ways to innovate, but this is so hard to get into something new.

When you are in a full-time executive role, you don’t have enough time to even start looking at these new things. And AI space is so dynamic, you, you need to block some time to get there. So I had this time I started to read, watch YouTube videos, whatever. And uh, then I started to experiment in my fractional C for work. So, and I learned that the only way to actually start using AI is to start using AI <laugh>, like learn by doing. There is nothing else. And I’m a part of a couple of CFO organizations and I started to talk about what I’m doing there and people get interested and they thought said, okay, why don’t you do a webinar for us? Why don’t you get a group of people and tell them what you are doing and how you are doing that? And eventually my business grew like a second black where I do the fractional CFO work now, and I don’t want to drop it, but I also do the webinars. I do the workshops with the companies, helping them to start implementing AI because this is very, very difficult to do on your own if you are in a full-time role. So this is where I am now. The idea is that I will continue this both parts because I think there is a lot of synergy between them, but we’ll see. And you are right the AI stuff is very exciting, but the classic, um, CFO work is also something that inspires me a lot and I really love doing that.

Glenn Hopper:

Yeah. And I think what you’ll find is you get into this more, and as you take on more and more clients, there’s gonna be more people who are, you know, quickly become experts in AI, but that domain expertise that you developed through your finance career, that’s what’s gonna make you stand out. If if somebody’s looking to implement AI in finance, you want the finance person not just the straight AI person. So I think it’s you, you’re in a great spot.

Anna Tiomina:

Yeah. This is what I think you are, right. And also finance people are different. They’re much more conservative. They are risk averse, and you need to keep all the things in mind and not just offer them solutions that will not work for them.

Glenn Hopper:

Typically. I think we could spend the whole episode talking about ai, but, um, you and I were talking before the show about, um, we’re in budget season right now. Yes. It would be fun to actually go through and do some budget war stories. And I do wanna get to those because I know you’ve got some Mm-Hmm. <affirmative> that, uh, a lot of us will be, you’ll, you’ll find a lot of us shaking our head and saying, oh yeah, I’ve been there. I remember that. Yeah. But let’s back up a little bit, uh, before that. And you know, one of the things that our listeners are always interested in is hearing. Um, so I know you were at the, at the huge company before and then the smaller IT company, but sort of hearing how FP&A teams are set up and, um, so how it’s set up and how you manage and how the responsibilities were. So either looking at your last company or even when you were at the larger company, maybe comparing and contrasting, tell us a little bit about the teams that you ran.

Anna Tiomina:

It’s not easy to compare them because the big company and the small company are like two different worlds if it comes to fp a. Right. But I realized that I was on this remote setup long before everybody switched to that with just the different that everybody was coming to the offices and was jumping on the calls from the offices instead of doing it from home as everybody does now. So I live in this remote setup for like 10 years already, maybe a little a bit more. It is interesting. In this big company, I was first in a market CFO role, and then they switched me to a cluster C. So I was responsible for several markets and it gave me such an interesting perspective on how the cluster people or FP&A teams look at the market and how the market looks at the cluster, right?

So how the budgeting process is organized, how it is communicated. When you are just at the very bottom of this process, you sometimes get irritated, like, why didn’t send up something night before it had to be submitted? Right? But then you realize that there are like five people over the people that you are talking to, and they don’t necessarily have control over this process, and they are doing their best to make this process as comfortable for you as it can, but it’s not always possible. Right? Another thing is that I learned that it is very important to mind the cultural differences in a international team, right? And sometimes you will get a team that is very diligent, follows all the deadlines. You can always rely on them, but sometimes you will get a team that needs five reminders before they do something that switch their computers 6:00 PM sharp, and you will never get to them until nine in the morning.

And you really have to keep that in mind and to change your communication style. And you do these reminders because like, what else is there to do? That was a lot of learning for me in switching between the roles. And in a smaller company, I had a little bit different challenges. So the company was relatively small, but international, we had five different offices, right? I couldn’t afford having a separate finance or FP&A person in every of the offices. So the way we handled that, every person on the team was wearing multiple hats. So it was either an administrative person doing some office management and doing some FO^A on top, or we would hire someone from finance, but then we would add something else to their role. And it was not easy to balance these two parts. People were not always happy with having to switch between something that they prefer doing maybe more or something else. Or if we would, for example, acquire an office and I would inherit a team there, team, the team would not necessarily understand how even finance works. So I would inherited a team of non-finance people and I would have to put some financial tasks on their table. Then we had to teach them how to handle the numbers, what, uh, balance sheet is all this stuff. So all, you know, all ways of trying to balance complexity and small size of the company.

Glenn Hopper:

It’s funny when you, my brain just kind of skipped and I had a a, a war story of my own that I remembered, and I normally don’t tell these stories, but this one was, this was at a <laugh>, a small company. And when you were talking about, you know, picking up the team that finance may not be their first responsibility. So I had, uh, it was myself and a controller, and we had someone for AP and someone for ar and I really needed a senior accountant or a staff accountant. Mm-Hmm. <affirmative>. And, um, I went to the CEO and this is a, you know, this is a company that did 12 or 15 million a year in revenue. So very, very small company. And, uh, I said, you know, this is the amount of work we’re doing. We, I actually, I need to get a staff accountant in the house. And he said, well, you are in luck. Um, my sister’s looking for a job. Mm-Hmm.

Anna Tiomina:

<affirmative>.

Glenn Hopper:

I said, oh, your sister’s an accountant? No, she’s an executive assistant, but that’s, it’s all the same <laugh>, <laugh>. So I ended up getting someone with no accounting experience to be my, uh, experie, my senior accountant. And it was, um, she, she was great and we got there, but that’s, that’s tough when you inherit a team that this is not what they’re doing and you’re trying to, to manage that. So

Anna Tiomina:

<laugh> Yeah, I, I had more or less the same story. One of my key people on the team managing a lot of accounting stuff is not an accountant. And she, she, she is great, but she needs really a lot of oversight on, in, in the accounting layer of what she’s doing. But she, I think has a marketing background and she ended up doing accounting just because, you know, somebody asks her, do you want to take this additional responsibility? And she said, yes. And this is how, you know, she evolved <laugh> into an accounting role, which is funny sometimes, but this is how it works. Yeah.

Glenn Hopper:

Let’s dive into some more, some more war stories. So I know one of your stories with, and we can all relate to this, I, I, I had to kick off of an ERP implementation one time, uh, while I was on my summer vacation to the beach. Uh, so that wasn’t much of a vacation when I was on, uh, onboarding calls all day from <laugh> from the beach chair. But, uh, one of yours was submitting reports Yeah. During the family vacation and reformatting overnight. What, tell us about that, about that story.

Anna Tiomina:

It’s actually two different stories. So one was, um, you know, when you are in this big corporate role, you try to understand when is a good time to take vacation because there are no people to back you up. And you understand that you will take your laptop with you and still be responsible for the things that you’re responsible for, right? So I, I was completely aware of that when I planned my vacation, but I have a family, so I had to adjust to the schedules of everyone in the family. And initially this time that I blocked for vacation was not supposed to be the time when we would be submitting the budget, but the company was changing the software and something didn’t work well, so they pushed the deadline. So I found myself on a beach resort with my family and with a very, very poor internet connection.

And I kind of did everything I could before going there, but the submission of the reports still needed to be done during this week. And because the internet connection was poor and the company systems didn’t work well, I had to really spend like six to seven hours a day just loading and reloading the report, which was like, you never wanna find yourself in this situation. Kind of, I did everything I could to avoid that, and my family was very understanding, but that was not a nice experience. However, when I reflected on that and I thought, okay, going forward, what, what can I do not to ever get myself into that situation? It’s actually not possible because of the ways big corporations structure the finance teams with little to no backup in executive positions, right? I never had a number two that would replace me in, in this situation.

So the teams are very lean, do more with less, um, all this stuff. So, um, it is, it is very challenging to manage the work-life balance in this big corporation. Although they often declare that they care about it, it’s often in practice, it’s not how it works. And the second story is a kind of funny story. Um, so we did this like 72 pages presentation for a regional business review. So it was like previous year budget, current year budget, all this story between. And, uh, I submitted everything on time and everything looked great, but like the night before this review was planned to take place, someone from the region contacted me and they said, you know what? We have a new standard that you need to now use dots instead of commas as decimal separators. And, uh, it sounds like an easy task, but in the presentation you have so many data formats that you really have to look through every piece of information.

And what makes it, what made it even more challenging the regional CFO at that time was a very, very tough guy who wouldn’t let us have, you know, any errors on the budget presentation. And if you had even a small rounding error, he would like stick it to your face. So I had no chance to, you know, get any excuses on not doing that. So yeah, like I spent a night redoing and rechecking everything. I just thought it was a true waste of time. And, uh, when I got into the cluster role, I, I never did that. Like, you need to focus your team on value adding activities, not in checking if the dots are in the right place.

Glenn Hopper:

It is funny though, I, I, I think anyone who’s, uh, been around for a while and loves to try to solve things in Excel, I was immediately trying to figure out the solution there of, of like, but then when you get to the, you know, the number format you, it’s not like you can search

Anna Tiomina:

Yes

Glenn Hopper:

For the comma because it’s being put by the format. So then I was like, well, could you concatenate? I I bet some of our listeners, there’s some like Excel MVPs that I’m sure they’ll say, oh, here’s how I would automate that. I, but I’m stumped here. I don’t know, other than it’s, it’s because of the form, the formatting that happens in the

Anna Tiomina:

Yeah. And the presentation itself was connected to the internal company system, and then you had all the numbers as a part of the text in the presentation. And sometimes we even had like the pictures, like screenshots of graphs included. So on the screenshots, we also had to go back and change it in Excel and then redo the screenshot. So, you know, like maybe there would, would be a good solution, but you would never find it inside like three hours. So Right.

Glenn Hopper:

When

Anna Tiomina:

You are under a tight deadline, you just go with the classic ways to solve things and hope that you get there. You don’t experiment.

Glenn Hopper:

Yeah. I’m somehow picturing on the screen with that old, uh, that liquid paper, the whiteout stuff, <laugh> taking the bottom of the comma off and turning it into a, do

Anna Tiomina:

Imagine it was like maybe 15 markets that had to do that, so all finance team didn’t get to sleep before a very important presentation day. That is a good story.

Glenn Hopper:

Yeah. <laugh>. So, you know, you’ve been through those and I’m sure there’s, we all have like our sort of our, our big wins where you get through that and, and get out on the other side. But, um, having gone through several of these, uh, cycles of budgeting, how would you say, and, you know, maybe it’s, I don’t know if it’s more based on time and technology changing or if it’s the size of company where you’ve been, but how have you seen the budgeting process change kind of over your career, especially with the growth of distributed teams and fast moving tech companies? Have you seen differences from when you started to Today?

Anna Tiomina:

I don’t think I’m in the place to really compare because I’m not in the corporation anymore. And I wouldn’t be surprised if I go back and I see that the process five years, because the corporation is so rigid, they, and it is difficult to change when you have 150 countries right? In, in your, um, in your structure. But what I am able to see is that a lot of companies are now trying to implement some higher level of agility in the budgeting. So in the corporation, we would do two budgeting cycles in the year, right? And it more or less worked now the companies want to do quarterly, some companies are doing monthly. In the tech company, I had monthly recalibrations on the budget going pretty deeply into the layers, right? So it’s not like a latest estimate that you would do on the top line, on bottom line and just skip everything in between.

We would go into the hiring updates, we would go into like what we buy, what we purchase, software, whatever else, because the environment is so rapidly changing and the expectations of the leadership team is for the CFO to be able to keep up with this change. And they don’t want you to do that. Coming to the every department every month and asking them questions. Everybody gets irritated by that. So you got to come up with ideas how to automate that, how to make it work on its own. AI actually helps there a lot. But the demand for this higher density of budget updates, I think it is there maybe in in corporations as well, because I hear it from fellows.

Glenn Hopper:

You know, it’s funny, I, um, I started out not in finance, but in the military, and I did have, in my department, I had a budget I had to manage, and I would think about the budget every year. And the military did it very differently. It was basically, uh, back then, anyway, maybe they’ve gotten smarter since then, it’s been a million years ago. But they, you basically had to be sure that you used all of your budget by the end of the year, otherwise they would take it from, take it away from you. So it was people just buying stuff they didn’t need at the end of the year. And um, oh, this

Anna Tiomina:

Is still happening. This is still happening. And how stupid it, it’s, it is not bringing value to the company. Right? But it is, I don’t think it’s changing. I I still hear, like, if you talk to salespeople, they are at the end of the year, so everybody’s trying to push sales because the companies have budgets to spend and why the companies have budgets to spend. Because if I save this budget, my regional head will never let me use this budget in the next year when maybe I needed more. They will just say, okay, you have savings here next year, bring more savings please. Right? And the same goes with revenue. If you overdeliver revenue, then the next year you have to overdeliver more. This is why all the companies are playing games with revenue recognition, pushing it forward or backwards. Yeah. Depending on what they want to get. Um, I, I think I don’t have an answer how it should change, but I hear a lot of frustration in finance team across, you know, every industry because you want to, to bring some value in your role, not just to manipulate the numbers to what that, that’s like a dance. We’re all dancing.

Glenn Hopper:

Yeah. And that’s, I mean, my biggest takeaway after seeing that, I mean, the military seemed like, I mean, I know exactly what you’re talking about with when a deal closes on revenue and, you know, the whole revenue recognition game to try to hit your numbers, but not overshoot too far and, and all that. Um, but, you know, seeing the behavior that that drove in people and trying to, like you want people to be frugal. You don’t want them to be buying extra office supplies just ’cause they’re trying to figure out how to, how to blow their budget at the end of the year so they don’t get taken away. So, and it was early in my career, in my, in my first finance leadership roles, trying to get people, you know, it’s like, look, here’s your run rate. We can, I’ll give you your gl you can look at, uh, what your department did, you know what by region, by city, whatever. But we’re gonna do a bottom up budget. Mm-Hmm. <affirmative>. And, and it would drive them crazy. They would say, I, you mean I’ve gotta start and fill out what I’m gonna do? And yes, you can look back at the gl, but we’re, we’re gonna, we’re gonna knock that away. You know, you end up Mm-Hmm, <affirmative> Yeah. End up in that kind of hybrid where it’s somewhere, you know, top down, you know, you’ve got your goals and then you’re gonna

Anna Tiomina:

Yeah. Meet

Glenn Hopper:

In the middle. Yeah. The biggest thing now is, is the technology side of it, how it’s getting a lot easier because the way that things are are tracked and, but it’s also, it’s the same thing. Smaller companies don’t have access to the better, you know, ERPs and, and yeah. Software systems out there. So I don’t know, it’s, it’s been a couple years since I’ve been doing consulting. Um, I’ve, it’s been a couple years since I’ve had to go through budget season, and it’s probably like an accountant with tax season. Like when you’re in the middle of it, it’s, it’s not fun. But getting on the other side and having a budget, and especially when you watch how your, how your budget does compared to actuals in next year when you feel like you really nailed it. It’s like that’s one of those small victories in finance.

Anna Tiomina:

We got that. I agree. But you mentioned technology and technology does help in a lot of things, but I don’t think it’s gonna help with this dancing in politics. That is a big part of the budgeting process still in many organizations, right? So it can, technology can make the analysis easier, like presentations, like writing, maybe reports. Yes. You can leverage it for sure. I don’t see a way it would change this like, like take it to leave it approach or the necessity to manipulate numbers. And I had to do that. There was no way I could get out of that because my market was expecting me to look up for their interests. And, uh, it all eventually goes to how people are identified, right? So bonuses depend on what target you agree on, which makes the target discussion not a finance or data discussion, it makes it a power game and politics.

Glenn Hopper:

Yep, yep. Did you, I mean, and I’m sure it was slightly different at the massive corporation versus the smaller one, but were there, were there lessons that you picked up along the way of, of how to maneuver the politics through budget season? Anything you, any, any tips you could share with our listeners?

Anna Tiomina:

Like ideally I would not have to share any tips. Ideally, I would like to find a way to get outta this whole situation, <laugh>, but because I was in this both situation when my, I was at the bottom of this whole process, and when I was somewhere in the middle between the region and the countries, I can say that actually CFOs should double down on politics, unfortunately, right? Because, um, when I was in this cluster role, I realized that if I get a stretch from the region, I am looking for the easiest market to put it on. Okay. Like, I would look for a country that would push back as little as they can, and this punishes the com the, the countries that actually respect me, but trust that when I give them a stretch on the budget, I actually have an idea how they’re gonna get there.

But I didn’t always have this idea. I would just be challenged by the region and I had to put it somewhere between my teams. So when I get back to a bigger country role, I would always push back as hard as I could, which made it difficult for everyone in the process, right? So it’s like a lot of unnecessary actions. Uh, so unfortunately things I’m telling the, you know, aspiring CFOs is, it’s not that important how you handle data. It is important how you build relations and how you navigate this politics in your organization. This is much more important than how you handle your numbers. That’s, that’s the reality. I I hope it’s gonna change someday, but I don’t see it changing right now.

Glenn Hopper:

Yeah. And what’s interesting when you say that is as we look at all the, uh, sort of AI and, and automation and, and what we’re doing with data and, and the parts that AI and automation can replace versus that very human element of our job, the politics, while, uh, you know, maybe, uh, I think some people probably enjoy it, but it’s, you know, it, it, it can be a difficult part, but if you are able to navigate the politics and the company at budget time and, you know, befriend the right people and mm-Hmm. <affirmative> don’t back down to the right people and all, I mean, it’s a, it’s a big part of our job.

Anna Tiomina:

It’s, yes, but I can actually share a story of how I see AI changing that it, it’s an interesting one, and this is like current budgeting season. Okay? So I’m helping a company in the budgeting process, and they have this, you know, approach of top down and bottom up ap uh, like approaches meeting somewhere in the middle. And there is always a lot of politics. The top down tries to stretch the bottom up, tries to be as conservative as possible, right? But this year we did this AI exercise, so we analyzed a lot of data and we came up with AI generated forecasts. And having AI didn’t make this, you know, possible it was possible to do it before, but it made this exercise much easier. So you don’t need a data data analyst, and we don’t need to hire a team of people to actually get it done.

So we introduced this AI generated forecast and what it did to the budgeting process, it was a kind of like neutral input, which you never have in the budgeting process. You always have someone protecting their interests. And now you have like a robot who doesn’t have emotions, who doesn’t have any interest, and whose bonus doesn’t depend on what it says, right? So the budgeting discussion really shifted from, I need this number and I can only deliver this number to something like, okay, why does AI think we can get here and not here? And then you look at the assumptions and you look at the model and the forecast was not perfect, but it bring it, it brought a very different perspective. And I could see how the discussion shifted to something that, to me would be much more valuable than just, you know, playing this power game.

Glenn Hopper:

Yeah. That’s interesting that you say that with ai because that was sort of the approach that I would take when I was dealing with department heads who, uh, you know, just would not, you know, <laugh>, they, because they would have, you know, sales and marketing was always, always the toughest Mm-Hmm. <affirmative>. But so say we’re looking at top line and you know, the company, maybe the CEO is saying, look, we need to increase revenue by 15% this year with the stretch of 25% or whatever. And then you’d go and look at the prior years and, you know, all things being equal. You could do a forecast and say, look, this is all things being equal. This is our forecast. This is the 95% probability of where it’ll go just on the statistical. Just yeah,

Anna Tiomina:

No,

Glenn Hopper:

No matter what we do, we’re just launching this out. And if you could show them the band Mm-Hmm. <affirmative> of like, you know, here’s, here’s your max, uh, median and in and minimum, like, here’s the band, look where your forecast look, where you, you’re either way high and you’re way low. Neither of these are justified. But it was trying to do that same thing where it’s just, let’s just be cold and analytical here.

Anna Tiomina:

Yes.

Glenn Hopper:

And look at this. But the thing is then they were like, well, how can you say, you know, they not not being stats people, they would say, well, how can you say what the 95% probability is? You’re just making, you know, you’re making those numbers up, but if you have the AI do it.

Anna Tiomina:

Yeah. And

Glenn Hopper:

The, and you know, you have the forecast go out and it’s like, look, this is where we are. And then, so you can, it’s almost like it gives you someone to blame for the rationality that you’re imposing on them. Exactly. Yeah. So, so if our gross margin is X percent and it has been X percent for the past five years, why do you think we’re gonna cut that by in half? You know, what, what are we gonna do? And then, but that, that meat in the middle of the Mm-Hmm. <affirmative> top down and bottom up is, if you have a, a program or a project, we’re gonna do something to do away with one of our cost of good sold, whatever, then you can come up with it. But it is what I do like about using ai or even just statistical modeling, if you took step back and, and before ai, I would think of this as like, what a private equity person to do.

If I’m evaluating a company, I’m not gonna listen out of the gates to what the CEO tells me the strategy is for how they’re gonna grow top line and how they’re gonna cut these costs. I’m gonna say, let me, what do the numbers say if we just continue the trends? And then you look at it, and AI kind of helps you do that because it’s very easy, right? And you don’t even have to be in Excel whiz to do it. If you’re using generative ai, you just tell it, forecast this out based on the trend.

Anna Tiomina:

Yes. But then you can also ask like, what, what assumptions did you use? So you can challenge AI and you can say, if it says, I am assuming that everything will be the same as in the last three years, you can say, okay, this is not what we’re expecting. We want to do this and that. And it’s very easy with the natural language just prompting together. So you don’t need to translate this into some data analytics stuff and then ask the person to embed it in some model that somebody developed for you. So the accessibility of this analysis is now much, much higher than it used to be. And not only companies like Amazon can now use, you know, AI to do whatever analysis they need,

Glenn Hopper:

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Right now, people like you and I, and I’m, I’m sure a lot of our listeners too are going out and they’re playing around with chat GPT and Claude and you know, llama and, and whichever model they’re using, and they’re seeing how you can, now, you can run Monte Carlo simulations, you can do all this stuff within the inline window on these tools, but they are outside of our workflow. Mm-Hmm. <affirmative>. So getting the output from them, you can do it, it just takes a lot of massage, you know, having it output as a CSV, and then you take the CSV and you put it back into your Excel models. And if you go back and run the same, you could do the exact same prompts and, and queries two different times and get different answers. And that’s, you know, you shouldn’t, obviously for numbers that are set in stone and already done, obviously that’s a mm-Hmm. <affirmative> hallucination of problem. But even if you’re doing the forecast, just like if you went to two different financial analysts, yes, you might get different interpretations of it. So I’m wondering, as you’re working with companies now, and as you see it right now for this budget season, mm-hmm, <affirmative>, and, and I know you touched on it already a little bit, but how would you recommend people assuming that they’re within their company’s generative AI usage policy? Mm-Hmm. We have to put that. Yeah,

Anna Tiomina:

Absolutely. Yes.

Glenn Hopper:

But how would you recommend people right now, in 2024 budgeting season for, for 2025 and beyond? How could they use generative AI to help them today?

Anna Tiomina:

That’s first of all, that’s an excellent question. And what you described is one of the most common challenges that I see. I also see that there are a lot of finance professionals who are trying to bring some ai, but their companies are very much against that. So, um, you know, if there is a strict policy, if you don’t do anything, don’t break the policy, try to talk to your security department, trying to talk to your IT department, but don’t go against the policy. It’s not worth it. But my clients are mostly like small, smaller companies, smaller up to, I dunno, $20 million. Uh, they don’t usually have advanced security settings or advanced security departments. And we are, and they’re using also very basic software for budgeting. It would be Google Sheets or Simple Excel, right? So in this setup, it is very easy to add some chat GPT or code into that, and it already enhances the process.

And you don’t need to invest a lot of effort and money into building some system. Uh, so in this company is what I found out is that learning by doing and small steps, this is what works. So when they start with a small project, and I usually like to point something that is really painful for everyone. If the company, for example, has a, a lot of unstructured data or data in different formats, right? You can use AI to reformat stuff for you and, and it can do it pretty reliably. You don’t get two different answers when you ask the same question. So maybe start with something that guarantees good results and then share it inside the organization and expand the AI usage. In bigger companies, CFOs alone can’t get there. They, the only thing they can do, they can scream on the top level guys, we are behind. Everybody is already doing that. We are not, which is not true. But

Glenn Hopper:

<laugh>,

Anna Tiomina:

You can, you can try doing that because there is no way that CFOs alone will be able to implement those policies, set up everything that needs to be set up in order for AI to be embedded in the company processes. At least this is what I hear, and I hear a lot of frustration from the CFOs. I hear there are, um, like there are reports that are saying that people are using AI on the workplace regardless of the company supporting that or not. But I, you can’t bring something up during the budgeting season and say you used AI for that if your company doesn’t support AI.

Glenn Hopper:

Yeah. And that’s, you know, every time it seems like every couple months you see a new survey where the number of people who are using AI in the workplace is going up and up, but at the same time, the number of companies who’ve gotten a handle on it and have figured out how to direct them has stayed pretty flat. So you’ve got these employees out there who are, who are figuring it out on their own, but they’re kind of, because they’re doing it in this rogue way and it’s not systematic. Mm-Hmm. <affirmative>. And it’s not being controlled by the company. You know, you’ve got these cyborgs who are, you know, enhanced humans Yeah. Doing this, but they’re also potentially putting your data at risk. They could be just loading it into regular, you know,

Anna Tiomina:

Yes.

Glenn Hopper:

Regular cloud provided stuff outside of the protected environment. So everybody’s getting pressure from, whether it’s investors, bosses, boards, you know, everybody’s saying we need to lean into ai, but it’s not, it’s not really there yet. It’s not ready to, as and I, you know, I, I work with clients, uh, very similar size to, to yours. And what I tell most of them is, I’m gonna show you some cool things we can do. I’m gonna show you how we can use it. I’m gonna show you how you can use it safely. We’re gonna work on your AI usage policy and make sure that everybody in the company understands. We’ll show you. We’ll set up a system where you can train rescale, upscale everyone to understand how this works. But truthfully, unless you’re depending on the industry, and I would say at least over, you know, 50 million in revenue, and, and even then, depending on the industry, you may not have the team. But if you have an internal security team and data science team or BI team even then, you know, then you may end up building something internally you’re using. Otherwise smaller than that, most companies are gonna be at the mercy of, they’re gonna wait for data rails, AI assistant, Mm-Hmm. <affirmative>, NetSuite’s AI system, whatever it’s gonna be in the SaaS tools that they’re already using. That’s how they’re gonna use generative ai. And it’s not gonna be just going out and dumping it into publicly accessible chat GPT or whatever.

Anna Tiomina:

Well, you are right. But you know this, when the smaller companies get access to this AI in a bigger software, they often don’t know how to use that. And they heard a lot of stories specifically with data rails. Like, we wanted to get access, we implemented data rails. It doesn’t work. Why? Because people don’t know how to handle ai. And I am trying to argue that companies should be using AI in safe cases, in safe environment, even if they don’t use it at scale right now. Because working with AI is a very, very different thing compared to rule-based automation that everybody is used to, right? And, uh, it is very important for CFOs and executives to understand this difference, but also for everybody else who works on normal office tasks, because it’s so much different how you interact with that. You ask the same question, you get two different answers, right?

People don’t get it anywhere. Finance teams don’t get it anywhere where you ask the same question and you get a different answer right. To tomorrow compared to yesterday with exactly the same input. What I’m trying to bring into the company is this is the safe setup. This is the safe data or safe like document set that you can work with. I think that like paid team subscription for ChatGPT is safe enough for the company to use it on some internal data. Not like social security numbers, but like contracts probably. You could use it on contracts, you could use it on company financials, even if it’s not a public company. It’s not, it doesn’t work. Like your balance sheet will be in the internet tomorrow, right? So again, I think the best way is to learn by doing and by starting small. So even implementing it in some process, which is not critical, but painful it in, it gives the company, you know, the exposure to what it is.

And then the finance team is able to understand what other processes are a good target for AI implementation. And then you can add technology, you can bring in the team and you can implement the software specialized in this specific, um, like use case. It can be budgeting, it can be account payables processing for example, or account receivables or expense reporting, depending on what’s the most painful, let’s say, process in the work. But if you don’t expose people to AI before, I don’t think you can successfully implement that. That’s, that’s what I’ve seen. I’ve seen a lot of failures in implementation just because it’s not easy. The difference is too big between the classic tools and AI tools. And you use it daily. I use it daily and we tend to forget, but I still forget how it felt when I started, like six, seven months ago, and how many times I was frustrated and how many times I wanted to drop it, because, you know, it, it doesn’t work.

Okay. Close it. <laugh>, let’s go back to Excel. It is a new technology. It is developing very rapidly. Even what changed since I started, since like six, seven months ago, the models evolved significantly. Now you also, you don’t only need to know ai, you also need to know how different models work, different models, how you speak to them, how you interact with them, which use case is the best for which model. So the complexity has increased significantly. And, uh, the starting point is now much farther, I would say, than it used to be. So if you started a year ago, you would be in, in a pretty comfortable situation. Now if you are just starting today there, there’s a lot to digest.

Glenn Hopper:

Yeah. And I wonder what do you think it means for the future of, and this, you know, you could swap out what I’m about to ask and plug in any profession. Okay. Any sort of, uh, white collar thing. But I’m thinking, you know, because our focus is fp and a, if I am an FP and a person and I am very good, I’m, you know, can do anything in Excel, I’m, I’m, I can, I’m power bi even. I’m just super analyst. I can use all this traditional software and I have defined myself in my career by my ability to write, to build a really cool model. Mm-Hmm. <affirmative> to use Power Query to use SQL when I need to. I can even use Python and Excel, all this cool stuff that is Yeah. Uh, cool to FA maybe nerdy to some my kids probably <laugh>. Um, but you know, so I’ve, it’s, it’s like being an engineer.

It’s, or you know, I’m very good at these specific tasks. Now generative AI is coming along and it’s saying that all the, the code that I used to be able to write can now be replaced with natural language and just interact. So instead of having to learn how to write a SQL query, I can just use generative AI and ask the same question. It returns my results. What do you think, and to your point, if you’ve just tried to even just keep up with the different generative AI models that are out there, like how does that make you better at your job? If you know the difference between Gemini, Claude chat, GPT, you know, that’s like almost a distraction because you’re chasing this AI arms race. What do you do? Whether you’re just starting your career or you’re kind of mid-level, or even senior level, and now there’s this rapidly advancing wave of technology. I mean, and, and, and if you haven’t started yet, mm-Hmm, <affirmative>, this is kind of the million dollar question. What should people be doing right now to use it today and to kind of prepare for the future? What should they be looking at? I don’t, what do you, I mean, what are your thoughts on that?

Anna Tiomina:

That’s a good question. I’m actually issuing a newsletter tomorrow dedicated to this exact question, because I hear that a lot. And, um, you are right. It’s not easy. My framework that I kind of developed is start using something. If you don’t know what I would say, okay, chat GPT is the basis plus whatever you are using. Maybe if it’s a Microsoft Suite company, then it would copilot rather experimenting and learning by doing works much better than just, you know, doing a training. So I did trainings before, and when I get back to the company a month later and I ask, okay, did anybody start doing that? And during the training everybody’s wow. Like, wow, really? Then you come back to them a month later and you ask, did you change anything? No, because nothing changes when you don’t manage this change, first of all. So you have to be really managing the state change from the top.

And also you got to let people experiment and push them towards these safe experimentation. But, um, right now I would do five simple steps. I would do a short training. Uh, Google has pretty good training on basics of AI, machine learning, just to get the vocabulary. I would identify a process that is manual painful and doesn’t touch sensitive or confidential information. Something like expense reporting, for example. And I would try to implement a, a simple automation for this process based on the existing tools that the company is using and some ai. And it can be very, very simple automation. And then the people who will see the result, they would be very excited because normally this is a game changer in this manual tasks. And then you do a sequence of step-by-step, implementing more processes, more AI in more processes, and then your team gets some free time to experiment and to learn more.

So this is how I got to where I’m with a lot of experimentation, a lot of hands-on experience, but also you need to dedicate time for that. And I’m subscribed to a lot of newsletters. I listen to podcasts, I watch YouTube because there is no way you can navigate this space without dedicating time to learn. Now is it a waste of time? Partially, yes. If you are in a full-time role, you don’t have five hours a week to spend on that. But the flip side is that if you are not doing it now, right, in six months, it’s gonna be much more difficult to start than it’s now. And now it is much more difficult than it was six months ago. So the longer you wait, the more difficult you make it for yourself. And even if you are an advanced Python person, you will find yourself in the situation when there are a lot of CFOs who never learned Python, but who can do the data analytics tasks now better than you do without even going to you. So what’s gonna happen to your value on the market?

Glenn Hopper:

Yeah, it’s an interesting time trying to figure that out. I don’t know. It’s, uh, I, I like you, um, leaned pretty heavily into this because I don’t know, you know, exactly when the robots are gonna come for my job, but I felt like the more I knew about how the robots worked, the safer my job would be <laugh>. We’ll see how long that lasts. But um, yeah, I think, you know, it’s sort of for fp and a for anyone right now, I say statistics first. That’s kind of the gateway. Mm-Hmm.

Anna Tiomina:

<affirmative>

Glenn Hopper:

Into machine learning.

Anna Tiomina:

Yes.

Glenn Hopper:

Which, and then from machine learning, when you understand how that works, you understand how the generative AI models are, are working and you, it makes it easier to navigate this, this world. Yes. But with natural language, even if people don’t, you know, you could learn everything you could about coding and all that, and you could still, someone who never did before could just type in a query <laugh>, you know, and, and get an answer. So it’s, it’s an interesting time.

Anna Tiomina:

It’s, it’s, it’s, but don’t you think that like knowing AI will be a requisite for, you know, a part of any job description? And how soon do you think it’s gonna be?

Glenn Hopper:

Every couple months. It seems like indeed puts out a study. I’d like to see where they are in job descriptions with AI fluency. And you know what,

Anna Tiomina:

I can tell you where they are in. They’re not, right now, they’re not. Um, because I am like, I’m doing this and I’m in a lot of CFO groups and I talk to them a lot, and AI is never there, is is not there at all right now. Even the companies who are using AI as a part of their business model, they haven’t put AI as a requirement for finance people yet. So it’s interesting. And, and there is a lot of requirements like advanced Excel user. Okay,

Glenn Hopper:

Yeah. Co-pilot’s about to make that moot. It’s gonna be

Anna Tiomina:

<laugh>. Yeah. Right. Yeah. It, it’ll, and, and there is, uh, there is already a way to like add AI to Excel, so you don’t really need to be that advanced to do whatever you need to do.

Glenn Hopper:

Yeah. Well I’m, I’m sure we could talk about this all day, but we are bumping up against time and I do want to get to a couple questions we always throw out at the end just to, because we went straight into Mm-Hmm. <affirmative> to work and, and AI stuff, <laugh>. So at the end, uh, one is we always like to ask our guests, what’s something that, um, maybe not many people know about you, something we couldn’t find just by, by Googling you. Any, uh, any interesting personal tidbits you’d like to share? <laugh>?

Anna Tiomina:

Well, I’m, I’m actually a very open person, so I don’t hide stuff, but what I don’t, uh, necessarily like share with everyone is that I am, I took singing hinning lessons. So I like to organize, let’s say karaoke parties as a part of even my work bonding. So whenever I would go and have to meet a new team, I would do karaoke with them. <laugh>. It’s not that I do, you know, professionally, but I enjoy it. I think it’s a good way to bond and a good way to find stuff about your team that they don’t necessarily share with the world. Yeah. Everything else, I’m, I’m an open book. I’m very open.

Glenn Hopper:

That’s funny. I think if I tried to do karaoke with my team, they would all just immediately quit. They would be like, if this is any indication of <laugh>, how anything else goes in your life, your singing voices telling me that you <laugh> you should not be allowed in public

Anna Tiomina:

<laugh>. I, I, I’m sometimes surprised with how great singers my team is, and this is not what you see necessarily in the work environment because people tend to be closed and they don’t wanna share it with you. Uh, so for me it was like a door opener in many cases. And, uh, that’s great. Yeah. But I can’t imagine the situation when people are not happy with this approach, <laugh>. So I’m, I’m trying to be cautious, but so far it works.

Glenn Hopper:

<laugh>. That’s great. Alright, now, now our, uh, our classic question. What is your favorite Excel function and why

Anna Tiomina:

<laugh>? I, I was hoping you’d skip this question because I don’t, I don’t have a favorite Excel question and, uh, Excel function and, uh, CFOs shouldn’t be necessarily dealing with Excel a lot.

Glenn Hopper:

Fair point. Yes.

Anna Tiomina:

But, uh, I, I used to have a team of people who would do all the preparation for me and I would, you know, just press the button. But I like pivot tables. I think it’s a very good tool when you need to structure the data. I do a lot of visualizations. I’m not a visual person myself, I like to look at the numbers, but a lot of salespeople, sales teams I work with, they don’t see the way I do. So I would plug in and make a simple visualization and this is how they see what’s going on. So they can see the trends, they can see the, like if it’s growing, if it’s dec declining. So maybe this is, this is what I use most frequently.

Glenn Hopper:

Yep, yep, yep. And I, and I totally get you on the Excel thing. I, it’s funny, the, the more I get removed from the, uh, day-to-Day operations, the more I think, like I’m, I think of my early bosses who had their financial calculators and they would love to sit in meetings and calculate net present value on their calculators that nobody <laugh>. I, I’m talking old school stuff the way that they used to, but yeah, I hear you on that. So, alright, well we are, we’re right at time here, so, but before you go, how can our listeners connect with you, learn more, find out about blend to balance and, and all that?

Anna Tiomina:

Well, I have a website blend to balance.com. You are always welcome to visit it. And you can just set a call with me. I can, I keep my calendar open. I am trying to very carefully balance the C FO parts and the AI part, and I’m open to new clients in actually both, um, directions. Although, I mean, maybe I’ll just switch to full-time AI consultations at some point. But I do think there is a lot of synergy and it is important to practice what you teach. And, and this is why I think this is, um, this is a good setup for me at least now. And as you can hear from the name of the company. I’m a big fan of balance in all meanings, including balancing two, not necessarily same activities. So it, it worked. I am very active on LinkedIn. It’s very easy to find me there.

So go ahead and connect with me. I am issuing a weekly newsletter or a cover, a lot of stuff that we talked about. And, uh, I don’t know, like I’m just working on my tomorrow’s issue and I’m trying to fit everything I wanna tell, and it’s not easy. So maybe I’ll switch to daily at some point. Not now. It’s, uh, it’s a lot of effort, but there is, yeah, there’s only so many hours in the day. There is a lot going on. Um, yeah, so I’m very, I’m always happy to connect to people who are also exploring AI and finance, finance and AI and all the combinations of the two. And, um, I love what you are doing, Glen. I I am very happy to hear your podcasts and to read your articles. Um, I think we’re all going in the same direction and, you know, the more people are talking about it, the easier it is for, for us to, for us CFOs to like get the understanding on leadership teams about why it is important, why companies should start, if they haven’t started yet, and get more open maybe about AI in, in even some operations that deal with secure data.

There are ways to set it up securely. It’s not a blocker, it’s just a thing to consider.

Glenn Hopper:

Absolutely. Well keep up the great work. Let’s stay in touch. Um, we’re, we’re kind of running down the same road at about the same pace here, so <laugh> we’ll have plenty to talk about going forward.

Anna Tiomina:

Yeah. So thank you. Thank you for having me.