How AI Is Reinventing Enterprise Finance

[00:00:15] Melissa Howatson Welcome to The CFO Show. I'm your host, Melissa Howatson, CFO of Vena. AI promises efficiency, automation, and smarter decision-making. For large organizations, the stakes and the challenges are far greater than simply adopting a new tool. From legacy systems to complex data environments and organizational resistance, AI in the enterprise space requires a very different playbook than it does for startups or SMBs. To help us make sense of it all, I'm joined by Rajat Bahri, a seasoned CFO who's led finance at scale across iconic companies like Wish, Jasper, and Align Technology. With deep experience in digital transformation, IPO readiness, and building global finance teams, Rajat brings a rare mix of strategic vision and operational insight into how AI is and isn't changing the way that large finance organizations operate. Welcome to the CFO Show, Rajat.  

[00:01:20] Rajat Bahri Thank you for having me, Melissa.  

[00:01:22] Melissa Howatson You've had a really impressive career across multiple industries. Can you share with us a bit about your journey and what led you to your current role at Icertis?  

[00:01:32] Rajat Bahri Sure. So as you know, I've been CFO for various companies, big companies, startups. And when I was looking at Icertis, what attracted me was, as a CFO, I always wanted a solution when I'm negotiating a contract. What is happening? How can I do it better? Never had a solution. It was always a very manual process. And Icertis had a platform which digitizes contracts and then uses AI to provide insights into the contracts, to help you manage your obligations, manage your costs. And as a CFO, I was very attracted to what they were really appeal, the product really appealed to me. And at the same time, this company, the product, the platform was the number one player in this space, very high growth metrics and a really great management team. So that's what attracted me to come to Icertis,  and I've been here three years and it's been a fantastic journey.  

[00:02:32] Melissa Howatson It's great to hear, and you've had, as we mentioned, a variety of experiences. What do you think are some of the key differences when it comes to running finance functions in an enterprise organization compared to SMB and mid-market?  

[00:02:47] Rajat Bahri So in enterprise space, there tends to be much more complexity. There are hundreds of systems. There are tons of legal entities. The data is all over the place. And in mid-market, the solution tends to a bit more simpler. The Icertis platform is very focused on enterprises. We have over 400 enterprises that we serve. We serve roughly 30 to 40 percent of Fortune 1000 companies. And what our platform does is it integrates with all the systems in a company, and then applies AI on top of it. So enterprise is the biggest challenge tends to be how do you get the single source of truth with so much complexity? And that's what at Icertis is our platform primarily service the enterprise markets because of the integration capabilities and the fact that we can apply AI and solutions on top of it.  

[00:03:44] Melissa Howatson You've led finance across large enterprises. Can you share with us how you're thinking about AI, both at Icertis and across the customers that you see, which are also large enterprise, how are they seeing AI and where they're applying adoption of it?  

[00:04:02] Rajat Bahri Yeah, great question. And let me address how our platform works with other enterprises and I'll also dive into how we are using it internally. So just to step back, what Icertis is about is managing or realizing the full potential of a business relationship between our customers and their customers, which could be their suppliers, their customers their partners. And contract is governing every dollar that comes inside a company and goes outside the company. And what we do is we basically use our platform to manage all contracts, the contracts performance, the contracts obligations, provide a lot of insights into all the dollars that are flowing inside and outside the company. And that enables enterprises to manage their cost bases with their suppliers, their revenue optimization with their customers, their compliance requirements. We basically help companies get better cost, better revenue, better compliance, better control. So, and what we have done is we've also taken that and applied it to Icertis. And as an example, you know, we, a few years ago, we were very unprofitable. And we are very profitable right now because we used our platform to, again, reduce the number of suppliers we had, scale the number of suppliers, get better costs from our suppliers, make sure we're getting the best terms from our customers. And so we applied that platform and been able to significantly improve. Our profitability and revenue because of the advantages that our platform brings to our customers.  

[00:05:31] Melissa Howatson And when you're dealing with these large enterprises, what are the things that are top of mind for them when they're assessing tools? There's so many different tools they're looking at right now that have AI. They're also trying to figure out how to embed AI within their own organizations. What are you seeing as common approaches and themes that are coming up with those customers of how they're going about it?  

[00:05:53] Rajat Bahri Yeah, again, a great question. AI has been on top of mind lately for the customers with all the buzz around AI. And we've been selling AI from the very beginning in our company, even seven or eight years ago. Our whole philosophy was that contracts are such content-rich objects. So much information exists in contracts. They are defining the rules of the business. And if we can provide great insights into all that information, it will lead to better business decisions. And what's happened lately in the last couple of years is the generative AI has come about, which has really increased the interest in everybody's mind. And there's a strong hunger from our customers to understand how can they use AI to drive, to automate things, to drive different business decisions? They are inundated. They are basically talking to a lot of vendors about using AI. So basically they're looking for something that really impacts their business. How can they make better business decisions? And as, you know, there's a lot of pressure nowadays on growth and profitability, and they're trying to see how they can optimize those things through use of AI. So there's lot of appetite, lot of desire to engage and understand how can AI help them make better business decision.  

[00:07:16] Melissa Howatson And I agree. I think that it's almost becoming table stakes now when companies are assessing vendor tools to at least understand what is the AI roadmap of this? Where will that come to play? And how does that fit within my own parameters of how I've decided I'm gonna govern around AI? So certainly it's become a pretty integral part, I would say, of the buying decisions that most companies are making. Can you share with us what some of the biggest barriers you've seen to adopting AI for finance organizations has been both in your own experience as you run your own finance team and look across at their overall use of AI and various AI tools, as well as what you're hearing from your enterprise customers.  

[00:08:07] Rajat Bahri I think the two biggest things that stand out is generally how accurate is the AI. If you look at ChatGPT, other types of model, they don't tend to be that accurate. They focus on a lot of publicly available information and they don't have a lot of proprietary information. I'll give you an example. We have 15 million contracts in our own model. We know how a car manufacturer works. We know how a plane manufacturer works. We know how financial services, a bank works. And we have those contracts in our repository. A ChatGPT-type of platform will never be able to get that kind of information because it's not available in public. So the models that we have are much more fine-tuned and much more context-based based on the use cases that our customers are looking at. So one of the things that comes about is like, what is the accuracy, generally, of your AI solution? And that's very, very important for a customer because if it's not accurate, then they cannot rely on the information that AI generated. So you really need a very high level of accuracy. The other piece is the trust factor. They want to make sure that they have trust in the AI. It leads to good things. So I would say trust and accuracy are the two important things that as people look at AI, they want to get comfortable with those two type of things. And that's what our focus has been as we sell our solutions to our customers. We're talking about a lot about our differentiators, which is a big data moat and how we have good AI practices, responsible AI practices. Those are becoming a much bigger part of the discussion.  

[00:09:57] Melissa Howatson Now let's move on to our audience question segment. Here's the question. Where have you seen the most value using AI at an enterprise level? Now that's a really good one, because I think that CFOs would have differing opinions on this one. For me, I would say that the easiest way to start to get the enterprise-wide interest in this is picking some of the enterprise-wide tools that you're gonna really double down on. Whether that's Microsoft Copilot, ChatGPT, but something that allows you to at enterprise grade with the security and controls, start to get all your employees playing with it and starting to see what it can do because that starts to open their eyes to tools that might be in the market and how they might be able to help them. Where are you seeing the biggest improvements in efficiency and finance from AI broadly?  

[00:10:54] Rajat Bahri So two things, one is the finance folks are becoming, I'm seeing a lot of automation, things that were a lot have done manually if you were to do some research around things, around contracts or any other thing, research when you're doing your SCC filings or all that. So there's a lot productivity that is coming by use of AI tools and a lot of automation possibilities. And then the other thing that is even more important is by using the data and the insights that are coming from AI is leading us to make more smarter decisions in our day-to-day lives. So I would say there are significant gains on productivity by using AI platforms. And then the other side is finance people tend to be analysis driven and finance people tend to give a lot of recommendations around business decisions. It's enabling the finance teams to get to better analyzes, better decision-making, better outcomes for the business. So very exciting time. Honestly, it's a very exciting time for the finance organizations at this point.  

[00:12:03] Melissa Howatson What do you think are the biggest differences in running finance for a large enterprise compared to SMB or mid market?  

[00:12:12] Rajat Bahri The biggest challenge tends to be because they have a lot of legacy systems, so their data is fragmented. So they are looking to themselves sees what is the source of truth that they can apply AI to. That tends to be the biggest challenge. And, you know, what we have seen is it is an incremental approach. You apply AI two certain sets of, you don't need to rip off all the legacy systems and go and transform all of. It's basically getting data integrated and getting it to a source of truth where you can apply AI to. So that tends to be the biggest challenge in the enterprise organization is the fragmentation of data across the company. And they're working through it. And as we said, it's an incremental approach to that versus ripping off the systems and you have to wait two, three years. You can get to a lot of use cases incrementally over time. So that tends to be the biggest challenge for enterprises. The challenge with the mid-market tends to be that price points on AI are still high, and the mid-market models needs to work economically. For them, it's more of a balance of where do they invest in selectively where there's a good payback for AI.  

[00:13:29] Melissa Howatson How are you seeing AI change the role of CFOs in large organizations?  

[00:13:34] Rajat Bahri We tend to wear multiple hats, right? The old traditional CFO role used to be very narrow and siloed. The new CFO role is we tend to be strong strategic partners of the different functions. And our point of view is in every decision that's made in the company. How do we go to market? How do we select our suppliers? CEOs are looking to CFOs as strategic partners. And that's transformation with AI is actually getting even stronger because the CFOs, as I said, you know, it's all about, AI is all about insights into business. And the CFO role has been around insights around data. So the fact that that role of strategic transformation being more strategic to the company, that role is becoming even more important with AI. And that's very exciting times from that perspective.  

[00:14:30] Melissa Howatson How do you balance the promises of AI with the realities of legacy systems and maybe fragmented data?  

[00:14:38] Rajat Bahri Yeah, so that's why whatever AI solution a vendor sells need to be fully integrated into the systems that the company has. And if you have just an AI tool that doesn't have the integration capabilities, it'll be very difficult for that AI tool to get adopted in the company. So the key is that your solution, how is it integrating into the system of the company so it can apply the AI capabilities on the whole set of data sets. So that integration becomes very important in this landscape. And again, companies are not going to change their legacy systems overnight. I mean, that tends to be a four or five year process. So that's why the vendors have to make sure that they can integrate very well in the company and start providing those benefits faster time to value. That becomes very importantly in this new world.  

[00:15:34] Melissa Howatson How should companies be thinking about upskilling or re-skilling their finance team members in the age of AI?  

[00:15:42] Rajat Bahri I kind of struggle with that in my organization as well. I mean, there's so many tools that exist. It's a mindset shift. First of all, it's educating your finance team as to what exists out there. There are so many tool, so many vendors. So first of all you need to say, what is available? And then picking a few and start using that in the company and even having objectives and goals around how each function is going to uh, use AI and then having some targets on productivity, you know, how you're going to measure it. Is it hours saved? Is it, you know, better quality of information? So it's a whole new mindset that you have to take very seriously and bring people along from enabling the people to making sure there are proper objectives in the company that are set so you can measure progress along the way, and it really needs to stop from the top. Don't needs to come from the talk from the board, from the CEO, from the CFO that this is important. And we are embracing it, and we're enabling you, and we are going to measure performance. So you have to do all that because the benefits are tremendous. And you cannot be behind, you cannot left behind on this journey.  

[00:16:52] Melissa Howatson And I couldn't agree more. I think the tone from the top matters a lot here. And both what we're doing by leading by example and also being clear about what our expectations are for employees. I think it's also, it's counterintuitive for us as finance people where we have to get the right answers, limit mistakes. We're really looking for a high bar when it comes to getting things right. And yet when it comes to trying AI, building that first agent or tinkering with it, you have to be willing to fail in that not all the things you embark on that are totally new to you are going to pan out, but that's part of the learning journey is you have to be willing give it a try, start playing with the tools, seeing what they can do, invest in it, and we can hold ourselves back by not being in that willingness to experiment with things. And so as the CFO and finance leaders, I think we have to even set that tone that it's okay and not every agent that somebody might sit and spend a bit of time building is actually going to end up being the one. But giving it a try and sharing the successes and also the learnings of what didn't work so that amongst the team, people are starting to get more of a collective confidence that comes. I'm curious your thoughts. A lot of companies have started putting out an AI strategy or a strategy memo where there is one of the efforts to make it clear what the tone from the top is. They address some of the common uses or how they're thinking about it. Are you seeing that happening in a lot of large enterprises or even when you thought about it within your own organization, is that an approach that you and your leadership team took?  

[00:18:47] Rajat Bahri Yeah, so talking about us, we are definitely seeing that tone. And it comes from the board, which board members every quarter, for example. This is about tone from the top, want to know every function, how they're using AI, and what benefits it's getting. And when that tone from top comes, people know it's a priority. There's also security implications of using AI. So how do you pick the AI tools? There are so many AI tools. Where do you make the right type of investments? Also, there's a whole framework that goes with that as well. How do you pick the tools? Where do you make right investments? How are you going to get the payback on those investments? So there's a whole approach that needs to be defined. For example, we have engagement with our customers, and the security element and the data element is coming up more and more. They want a platform that's secure, works in the security side of things, it's trustworthy, it's faster time to value. So, we are having all those discussions with our customers as well. And different customers at different stages but i would say there's definitely increasing conversations around that around that whole area.  

[00:19:59] Melissa Howatson What advice would you give to CFOs who are new on their journey in terms of adopting AI?  

[00:20:06] Rajat Bahri What I would say is focus on three things. One is there's so many tools out there. Every vendor has a tool. Really get educated on what's out there and the benefits of that. Second piece is there is significant opportunity for automation. And automation really enables you to focus on value added things. So it's nearly not about reducing jobs, it's about focusing your team on value added activities versus things that could be automated. So really focusing the organization towards more business-driven decisions versus doing routine stuff. And the third, which is very exciting, is data. Focus on data, get better and better insights, which will lead you to make better business decisions. So those are the three things. Understand what's out there. Make sure you automate a lot of things, you can focus on value, and third, drive better business decisions by use of data.  

[00:21:04] Melissa Howatson Rajat, thank you so much for spending your time with me here on the show, sharing your insights. You've had such great experience with this topic, especially across large enterprise. Now, whenever we do have guests on the show, we have two rapid fire questions that we like to ask. So are you ready?  

[00:21:22] Rajat Bahri I am ready, let's go!  

[00:21:23] Melissa Howatson First one, what is the hallmark of a mature finance organization in terms of how it operates?  

[00:21:31] Rajat Bahri Strong business partner involved in every aspect of running a business is a sign of a strong, mature organization, fully integrated into the business decisions.  

[00:21:43] Melissa Howatson You must have listened to other episodes of the podcast because my heart is singing hearing you say that because we talk a lot about how important that business partnership is. So couldn't agree more. The second one is what is a book that has had a big impact on you in your career?  

[00:22:00] Rajat Bahri Seven Successful Habits that came by Stephen Covey, that came, I think, seven or eight years ago. So really helped me focus on, you know, key things that matter. And that really helped me become more effective in what I do.  

[00:22:17] Melissa Howatson That one is a classic, I feel, even though it's maybe not that old. It's certainly becoming a classic. It's a great recommendation. Again, thank you for joining me. Really enjoyed this conversation with you today.  

[00:22:29] Rajat Bahri Thanks for having me, Melissa. Me too, really enjoyed it. Thank you.  

[00:22:34] Melissa Howatson If you've enjoyed this episode, we'd love your support. Follow the show and leave us a rating or review on Apple Podcasts or Spotify. It's one of the best ways to help more finance professionals discover us. For The CFO Show, I'm Melissa Howatson. Until next time.