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At OPEXEngine, we speak with software finance leaders all the time about how their jobs are changing. This conversation with Brian Beaupre (CFO, Teikametrics) gets specific.
We discuss why strategic finance is now table stakes, and what CFOs should do with the time AI frees up. Whether you’re rethinking your finance org’s AI roadmap or developing the next generation of finance leaders, this one is worth your time.
Brian has been a SaaS operator for 20-plus years across VC- and PE-backed companies, and he talks openly about where AI is helping his team today and what he made sure was in place before layering it on. He also takes on a more difficult question: With AI taking over the grunt work, how do the next generation of finance leaders develop judgment?
A few highlights from the conversation:
- In FP&A, being strategic used to be the fast track to the top. Now companies simply expect it, and CFOs are asked to operate almost like a COO.
- Before AI touched anything at Teikametrics, the team built FP&A tools on top of Databricks, wrote down their business rules, and added a validation layer. Ask anyone there where a number comes from and who owns it, and they can tell you.
- With less grunt work on the calendar, the question is what finance does with the extra hours. The answer here: stop making excuses about time and data access, and go dig into the thing you’ve been meaning to look at.
- The grunt work used to be how more junior finance people learned the business. With AI absorbing it, building judgment has to be deliberate: learn the product, study the competition, and see the business through each leader’s lens.
- Managing a large team used to be a badge of honor for CFOs. What replaces it is doing more with less without letting quality slip, and knowing where people still need to be in the loop.
You can listen to the conversation as a podcast, or read the full transcript below.
Transcript
The Modern Tech CFO: Balancing AI, Data, and Strategic Leadership
Katherine Zhang: Welcome to this episode of SaaS Conversations. Today, we're joined by Brian Beaupre, CFO of Teikametrics. Brian is here to discuss the changing role of finance and its increasingly strategic role with the adoption of AI tools. Welcome, Brian.
Brian Beaupre: Thank you. Glad to be here.
Katherine Zhang: To jump off, tell us about what Teikametrics does, what your role is, and how you got to that role.
Brian Beaupre: Teikametrics is an AI platform for sellers on e-commerce marketplaces, so Amazon, Walmart, and TikTok. We combine patent-pending AI technology with experts in the loop -- hands on keyboard -- to help optimize for seller success. That means optimizing every dollar they spend, tracking profitability, and really optimizing for outcomes across a wide vector of objectives for sellers.
It's not just return on ad spend. It's making sure that whatever objectives customers have, whether that's improved profitability, organic search, inventory, or fulfillment, we're the hub and the centralized AI-based infrastructure to help them optimize for success.
In terms of my background, I've been at Teikametrics just under five years. I've been a SaaS operator for 20-plus years now. I've been at companies as small as $10 million in ARR all the way up to $300 million, and everything in between.
I've led teams across FP&A, accounting, revenue operations, and legal, in both VC- and PE-backed environments. Prior to joining Teikametrics, I was at a TPG portfolio company, which is where I had my first experience with private equity. I really enjoyed my time there and learned a great deal from operating partners, key stakeholders, and sponsors on the PE side as well as other business folks.
Teikametrics is my first “dipping of my toe” in the e-commerce space, but it's still recurring revenue. Very much the same management principles you would leverage in a SaaS business apply to optimizing growth and profitability. With the emergence of AI, we're seeing different ways of working and different metrics and KPIs that underpin the outcomes we're looking for.
That's a little bit about me. And I live in Milton, Massachusetts. I'm married, with two boys, 14 and 11.
Katherine Zhang: Great. I'm sure they keep you very busy.
Brian Beaupre: They do. Hockey and baseball are my part-time job, which sometimes feels like a full-time job.
Katherine Zhang: Going back to your official full-time job, given your long career, I'm sure you've seen a lot of changes in what it means to be a CFO and a finance leader. How would you say the role has changed in just the past two or three years?
Brian Beaupre: I'm going to cheat on this answer on this one and go back a little earlier than two or three years. One thing I've seen over my last couple of stops is that, as my career has evolved, I've come to the CFO chair through the FP&A track, not the accounting track.
I'm not an accounting practitioner, although I've managed the function for years. I know enough to know what a best-in-class organization looks like. The key is to hire good people around you to backfill the subject-matter expertise gaps you may have.
When I started my career in FP&A, this notion of strategic finance, partnering across the business and leveraging analytics and your skillset, felt like a cutting-edge path to rising up the corporate ladder. You’re combing a keen understanding of numbers with strategic thinking to bring something to the table that not a lot of other business partners could.
What I've noticed over the last five-plus years is that being a strategic thought partner focused on enabling growth in the business is now table stakes. What used to be a differentiating skillset for potential CFOs is, today, the expectation. When a company brings in a CFO or finance leader, it expects that person to be strategic in nature, almost acting as a COO in a lot of ways. You're expected to partner across the business and leverage your unique skillset to deliver outcomes that nobody else in the business has the capabilities to do because of your intimate understanding of the financials. And how to create that connective tissue between financial outcomes and the inputs inside the business that drive those outcomes.
The first thing I would say is that a CFO is now expected to be a catalyst for strategic thought and growth in the business.
Another way things have evolved over the last five years is the expectation that CFOs stay up to date with emerging technology and innovation, and find ways to work smarter, not harder.
Even before AI, there was a proliferation of tools across order-to-cash, procure-to-pay, cash modeling, and other processes that used to require a lot of FTEs. Tools have emerged that help streamline those processes and integrate with your ERP and BI systems. There's an expectation that CFOs understand these capabilities and bring them into the organization so headcount can stay flat as the company grows.
That segues a little bit into the AI era we're in today. CFOs now need to embrace AI, and I think all of us are at different stages of doing that. But there has to be an openness, desire, and intentionality about introducing AI into how you and your organization deliver value. You also have to understand how everyone else in the business is using it and connect that to your cost footprint and the other KPIs that follow from it.
That's a bit of a long-winded answer, but hopefully it takes you through the time series .
Katherine Zhang: Absolutely. Let's stick with the need to embrace AI. I definitely want to come back to the idea that being a strategic thought leader is now table stakes. But in terms of embracing AI and working smarter, not harder, there are a lot of AI use cases being pitched to CFOs and other leaders, definitely on the finance side, right now. Where are you seeing actual, meaningful productivity gains versus things that are just interesting apps?
Brian Beaupre: My first reaction is that there's a lot of content out there and, hopefully I'm not alone in saying this, it can be overwhelming. You open LinkedIn and see all that sponsored content. In a lot of ways, I beat myself up and think, "Wow, we're really far behind what I'm seeing people are weaponizing AI to reinvent the modern G&A organization."
The reality, when you talk to people, is that everybody is at a different stage in terms of how they’re adopting and using AI. I saw an interesting graphic on LinkedIn about deploying AI inside a finance organization. It described a pyramid: different ways to capture value from AI depending on your role. One interesting point was that the most tactical and tangible ROI is at the bottom of the pyramid in recurring business processes.
Accounting is, at the end of the day, a process-oriented function. If you can automate processes that used to require hours of manual data entry and reconciliation, you can take that time off people's calendars and shift their focus to reviewing results and understanding the drivers of the business. We'll come back to that later in the conversation.
From a pure ROI standpoint, that's where the gains will be most immediately visible: automating recurring, time-consuming processes that keep people from spending their time on more strategic work and developing as professionals. Freeing people up to be better leaders and business partners is an area you should absolutely focus on. It's an area I think we're behind here, and I know the team is anxious to start doing more.
But it takes time. In accounting, people have done things a certain way for a long time. Asking them to flip that on its head, be vulnerable, and get comfortable being uncomfortable is difficult. The nature of that role is wanting to tick and tie every single thing and make sure what you deliver is accurate, reconciled, and something you can sign your name to. I completely understand hesitation or a latency in terms of implementation at that bottom level of the pyramid. We're working toward it, and some roles will need more intentional and prescriptive adoption.
Where we're using AI most today, I would say, is FP&A and my own role. My job is to digest reams of data and information, parse through it, and figure out the "so what." What's the story, and how do you translate it into frameworks your cross-functional business partners can understand and use to create actionable outcomes?
One of my strengths has always been knowing the story I'm trying to tell. The challenge is how long it takes to build that story myself, whether in PowerPoint or by building an Excel model from scratch. AI has absolutely changed my life from a productivity standpoint, and I think it's helped me learn, too.
We've worked hard to get the data inside our business crisp, reconciled, and connected to our different systems. We have a validation layer. Now I can overlay AI on top of that and say, "Here's the story I'm trying to tell. You tell me if it's the right story. You can pull this data from here and that data from there. Help me synthesize those data points to tell the story."
That's been incredibly powerful for me personally. It takes away the countless hours that would otherwise go into delivering that work. Whether it's board presentations or partnering across the business to examine how we're executing at the top of the funnel, I can ask it to go into Salesforce and pull information. Everyone, CFO or otherwise, has a massive list of things they're trying to accomplish. AI has allowed me to knock things off my list that I've always wanted to tackle but never had time for because I had to prioritize other areas.
It's allowed me to be much more productive, and I think my Director of FP&A would say the same. I consider that the top of the pyramid: strategic analysis, scenario building and modeling, and accelerating the path to the "so what" for people whose role is to synthesize data, create actionable storyboards and frameworks, and drive business growth.
Katherine Zhang: When you talk about synthesizing data points to tell a story, that sounds very simple and logical. I'm guessing there's a lot of work before you can get there, right?
Brian Beaupre: Yeah. I've talked about this with some of our investors and other folks in my CFO network. Early on, when AI was emerging, I think there was an assumption that it would sit on top of your ERP, CRM, and point systems and replace the FP&A tools and BI capabilities that existed before it.
I actually think quite the opposite. We've invested a lot of time and effort in FP&A tools that sit atop Databricks and pull data from all those point systems. We've been intentional about codifying business rules and democratizing data so everyone is working from the same pane of glass. We're clear about where a number comes from, who owns it, how it's calculated, and how we reconcile and validate it so it can serve as the true source of truth in the business.
Only at that point does it make sense to overlay AI. We consider that our validation layer that sort of sits between AI and the underlying point systems. If you haven't put in the work to understand whether numbers coming in through AI are accurate, that's a scary proposition.
It's especially important when different systems use different definitions. You have GAAP revenue, and you might also look at pro forma metrics that don't necessarily live in your ERP. It challenges people to ask: Do you understand the metrics in your business? Do you know what's right and wrong? When you overlay tools designed to accelerate analyses and scenarios, can you pressure-test whether the data they produce is accurate?
That's a powerful skill. Traditionally, doing the grunt work helped you understand what was happening in the business and all the inputs and key drivers. When you eliminate that work, you have to be very intentional about learning those things. What's happening in your function and across other functions? Do you understand what your business does? Are you seeing it through your cross-functional partners' lenses? Can you tell whether the numbers are accurate?
I think AI can be a really powerful forcing function for people to evolve. Previously, someone might say, "I was working on this for five or six hours. I didn't have time to zoom out and understand what was going on." Now you have to. AI can make mistakes, and it does make mistakes. It's up to you to understand what's right and what's wrong, because you can essentially engineer it to tell you whatever you want it to tell. And that's not how finance works. You have to understand what’s right and what’s wrong. You need that judgment, and I think developing it is a great opportunity for people to evolve their skills and for professional development.
Katherine Zhang: In your experience, what's the best way for someone coming up through finance leadership to develop that kind of judgment, especially if they're not doing the grunt work day-to-day?
Brian Beaupre: That's a great question, and something I think about quite a bit because my career track has largely been eradicated now because of AI. The question becomes: how do you develop judgment without going through the ups and downs with people, the grunt work, the late nights, and the deadlines?
I think the only way is through learned experiences. People will have to be really intentional about exposing themselves to other functions across the business. The best finance business partners I've worked for or alongside don't stay within their four walls and just understand the numbers and their drivers. They understand the product, how it works, and the competitive landscape. They truly see the business through each functional leader's lens.
Especially now that AI has short-circuited a lot of the work, the way to build mature business judgment is to understand the different dimensions of the business. What are the key priorities? What keeps other leaders awake at night? Do you understand the product, your competitors, and the threats out there? Have you used the product and experienced it like a customer?
That's how you start to drive value and leverage AI as intended. You can combine cross-functional knowledge with analytical rigor and an understanding of the connective tissue between the financials and the business. I think that can take your career, and what you can do for the business, to the next level.
Katherine Zhang: That's a good segue into the strategic role of finance. As you said earlier, being a strategic thought leader is now table stakes. How do you move beyond the table stakes?
Brian Beaupre: You move beyond table stakes by recognizing that so much of your bandwidth, which used to go into building things, can now go toward understanding the problems in the business. That means really listening and deliberately exposing yourself to gaps across the organization.
Previously, if you were in finance, you might say, "I'm focused on the close. I can't take meetings until it's done," or, "We have an audit," or, "There's a board meeting coming up." You had a built-in reason to hunker down and pull together important work for the company.
Now a lot of that work has been eliminated, so the question becomes: What do you do with the bandwidth? To move beyond the table stakes, you have to listen for the pressure points in the business and look for places where you can deliver value, help this business partner, or solve this problem. You have to be proactive about it, and that doesn't always come second nature to folks in the finance field.
Create a checklist. Say, "I heard in this meeting that someone is struggling with something. Let me try to fix it without being told to." Or at least bring some telemetry to the problem that they might not have considered and that could help them find a solution.
Be very intentional about listening and exposing yourself to the day-to-day challenges that exist across the business. There are countless challenges, and we have tools at our fingertips to help solve them. Otherwise, you're just saving time on things you did before. What are you using that extra bandwidth for? How are you using it to drive the business forward?
Katherine Zhang: Thinking about Teikametrics specifically, how has what you as the CFO look at in terms of pressure points, business drivers, and key questions changed as Teikametrics embeds more AI into its offerings?
Brian Beaupre: I need to do a better job of continuing to put this into practice. I can talk about what the best finance business partners should be doing. That doesn't mean I'm always doing it. I try to be focused on the business and think about areas where I can help.
The way I'd answer that today is that I'm trying not to restrict myself. In the past, you might see a problem, or simply want more transparency into some aspect of the business, and think, "I don't really have time to dig into this, but I know it's an area I want to explore." The way my job has evolved is acknowledging that there really are no excuses anymore.
If there's something I want to dig into, there's no excuse not to. Our team has done a really nice job of driving alignment across our different tools. It's a never-ending journey, and we always have room to improve, but we've embraced this wave of AI as a company and worked together to use it to drive favorable outcomes.
The information is at our fingertips. When I think, "I'd really like better visibility into this, and I think that could lead to a productive conversation with someone," I have to be intentional about telling myself that I now have the tools to get that visibility in a fraction of the time it used to take.
That discipline will evolve over time because we're conditioned to think, "I'd love to see this, but it will take hours, and I have to prioritize X over Y." Now I need to remind myself that there are far fewer limitations on what I can tackle.
A lot of that comes down to collaboration. Our business has done a wonderful job of making the data sources and point systems that feed critical business inputs available to people using AI day to day.
So it's not a direct tactical answer to your question. For me, it's really a mindset shift: you don't have those same excuses anymore. If you think something is amiss, put in the work to investigate it. The old restrictions on time and data availability are much less of an issue.
Katherine Zhang: As a closing question, what's your one piece of advice for finance leaders who are looking to follow the CFO path over the next five years?
Brian Beaupre: First and foremost, getting comfortable with AI tools. The modern finance organization is evolving. It used to feel like a badge of honor to be a CFO managing a large, sprawling team across the globe and a lot of complex processes. You could hang your hat on that.
I think that paradigm has shifted. Now it's about how much you can do with less, without letting the quality of the work decline. The next generation of CFOs will need to understand what the modern finance organization looks like. Where should you automate? Where can you work smarter without necessarily adding FTEs? And where do you need to overlay the right people to bring judgment and problem-solving skills into it?
If you’re an individual navigating the CFO track, one thing that scares me is that introducing AI so early in people's careers has the potential to decay problem-solving skills and judgment. You learn those through experience: working through ups and downs with people, succeeding, failing, learning, and applying those lessons the next time.
If you're an individual contributor looking to advance in your career, be really intentional about developing the skills AI won't necessarily help you develop. Understand the business through your business partners' lenses, and focus on relationships. At the end of the day, business is all about relationships and how well you work with people.
AI will help you gain insights without having to do as much of the work that once went into producing them. But it won't replace how you deliver those insights, how you engage with people, how you exchange notes, and how you learn to see the business through their perspective.
There are two sides I just went through with this. For the CFO, it's about what the modern finance organization will look like and how to strike the right balance between automating processes with AI and bringing in the right people.
For an individual contributor, many of the experiences I went through as an FP&A professional, building models, building scenarios, and turning raw data into an elegant model you can apply across projects, have largely been eliminated. So what are you going to do to drive value? I think the best way to do that is to have an intellectual curiosity about how the business works, how other business stakeholders are seeing challenges through their lens, and really weaponizing AI to drive those outcomes
It's table stakes to be comfortable with the technology. We're getting to a point where people will say, "I know you're going to use AI to solve this problem. I want you to tell me why you approached it this way. What was your thought process?" If you can't answer those questions and you're just relying on the tool, ultimately you're going to get exposed.
Katherine Zhang: That's great advice. I think any advice worth hearing is usually worth hearing in a lot of detail, so thank you for that. And thank you so much for joining us today, Brian.
Brian Beaupre: Thanks for having me. It was a great conversation. Apologies if some of my answers rambled on a little. Obviously, this is a topic I'm passionate about and something we think about a lot as CFOs and finance folks.
It's evolving every minute of every day, and we need to evolve as well. I think quite a bit about it, and I have a lot of perspectives on it that will continue to evolve. I really appreciate the opportunity to share some of those thoughts with you.
If you come back to me six or 12 months from now, I might say something totally different from where we are today. I think that's just the nature of where we are. Thank you for the opportunity.
Katherine Zhang: We'll hold you to that six-to-12-month follow-up.
Brian Beaupre: All right. I'm here. You know where to find me.
Katherine Zhang: Perfect. Thank you.
