Unlocking the Power of AI: Essential Skills for Finance Professionals

Megan - 00:00:30: Today, my guest is Monica Proothi. Monica is the global finance transformation leader within IBM Consulting. She has over 20 years of finance transformation experience split between consulting and industry roles. Monica has built a reputation for driving hyper growth and productivity by optimizing finance operating models through human centric transformations integrated with ERP modernization, intelligent operations, data strategy and enablement through technology. Monica is a people champion and has been instrumental in codifying the culture of her practice and in driving diversity, equity, and inclusion, awareness, and engagement. Monica, thank you very much for joining me on today's episode of CFO Weekly.

Monica - 00:01:48: Thank you. I'm very excited to be here, Megan.

Megan - 00:01:50: Yeah, I'm super excited about our discussion today and the opportunity to be having this conversation with you, given your background and your current role. And today we're going to be talking about the latest trends and challenges facing finance leaders, particularly around generative AI. And I'm excited to learn from your experiences. So let's get started.

Monica - 00:02:12: Right? It's everyone's hot topic.

Megan - 00:02:13: Yep, it certainly is. And you've had a fascinating career trajectory that spans over 20 years in finance and consulting. So can you share just a bit about your career journey and then perhaps a pivotal moment within that journey that shaped your approach to finance transformation?

Monica - 00:02:32: Absolutely. So Megan, I think that that pivotal moment is right now. I truly believe we're living in the pivotal moment in time where this is fundamentally going to change how work gets done. I think a few years back, I lived in that pivotal moment with blockchain and how this technology can play an important role, but it didn't quite create the same impact that we were hoping to see with finance. But I really think right now is kind of how we are shaping that approach for finance transformation in a whole new way than I've seen in my over 20 year career.

Megan - 00:03:06: Yeah, it seems like technology is just like a hockey stick. I'm not even sure I can imagine where we'll be in three to five years.

Monica - 00:03:14: Yeah.

Megan - 00:03:15: And you have a passion for promoting diversity, equity, and inclusion in your work. So what personal experiences or values have inspired you to prioritize DEI in your professional life?

Monica - 00:03:28: So I love this question. I think I've taken a lot of the best of what I've learned and a lot of the worst of what I learned, kind of the challenging experiences and put that into kind of how I've been growing. I will say. You know, one of the most inspiring things that I learned from a mentor of mine over 10 years ago was to lift while you climb. And, you know, what that means is as you're moving up, you're bringing others along with you. And so as you're climbing up the ladder, you're lifting folks along. And I can give a great example here. So a lot of times, especially in our client meetings, there's a whole team that's working on these materials that are going to be presented to senior finance executives and C-suite CFOs. And I go in there and I can talk about the finance strategy. And I know I do a great job, but my colleagues, kind of my right hand, they're not going to learn or get the same opportunities unless they also try and do it. And I can be there for support. I'll bring, you know, a consultant with me or an associate partner, and they'll have an opportunity to also present because they DID the work. And so maybe I can do it better, but it doesn't matter. Someone's got to learn, and this is how they're going to learn and grow. And that's kind of one of the big values that I took with me from moving from one company kind of to the next to the next. And I've oriented and found myself, those leaders that I look up to and that I aspire to be like, and I hope to kind of bring those values with me. I think the other thing I just want to touch upon is this is a finance sector, and it is predominantly male dominated. I will give a lot of kudos and credit to IBM's finance organization, which actually has an incredibly strong female leadership team. Which is inspiring, and it's a testament to Jim Cavanaugh and his leadership style. But typically in a finance organization, it is male dominated. And so being able to kind of bring women up, my team is more than 60% women. It's more than 70% diverse. And I love seeing those numbers. And I love seeing how, you know, last year we had partners who were promoted and it was 100% diversity on my team that got promoted. And so, you know, I'm just trying to make sure that it's an equal playing field for all. And that people have sponsors, because this is the other thing that I think, especially with women, women always talk about all the mentors that they have. And I used to do the same thing. I was like, I have, you know, 10, 20 mentors, but unless you have a sponsor and an advocate, a person who's going to really go and fight for you and advocate for your career, I find that less and less women and diversity candidates have sponsors. They've got a lot of mentors, but not someone really being the voice in the room for them.

Megan - 00:06:08: Yeah. It's so important too, to have a variety of voices at the table. It doesn't do a company any favors to, you know. Have a bunch of just clones. Can you talk to us a little bit about your role with IBM and what it is that you do and you're responsible for.

Monica - 00:06:26: Yeah, absolutely. So I lead our global finance transformation offering and practice. And what that means is I'm looking at everything from end to end finance. So from CFO advisory, operating model, shared services, BPO, ERP modernization. So things like SAP and Oracle implementations, anything that touches a finance function, I forgot about data and AI as well. Anything that touches a finance function in a finance domain. So that's like records report, order to cash, procure to pay, FP&A tax and treasury. And you look kind of across end to end. And now it's kind of breaking down those barriers and we're actually going beyond finance. And we'll get into it a little bit later, I'm sure, but how that role of the finance organization has really shifted and that we're extending kind of across into technology and operations and business partnering as well. So my role is global finance transformation leader. So it's anything that kind of touches that finance organization.

Megan - 00:07:19: And IBM recently conducted its 2024 CFO survey. Can you discuss the findings of that survey? And what, if anything, surprised you about the results?

Monica - 00:07:29: Yeah, absolutely. So I'll give a little bit of a background about the survey first. So the study captures insights from 2000 plus CFOs across 26 industries and 24 locations. And it kind of reveals the compounded tensions, what our finance leader is thinking about, what challenges are they facing. And then specifically this year is the impact GenAI will have on their organization. So we found that CFOs ranked technology modernization as the most important enabler of competitive advantage over the next three years. The findings also show that there's an even greater opportunity for CFOs to kind of use their influence to advance innovation, underscore kind of those crucial roles that these leaders play in driving that competitive advantage. There's 72% of, I've got the study here. I don't know all the percents off my head, but 72% of the top performing CFOs identified that the CTOs is actually super important to be partnering with and critical to their success. However, only 35% of the finance organizations actually said that they're engaging in early IT planning with the tech leaders. So they understand the importance, but maybe not fully putting it into practice yet.

Megan - 00:08:40: So given that, how can CFOs ensure that the finance function is closely involved in the development of business cases that pertain to technology investments?

Monica - 00:08:50: I mean, that's a great question. They need to stay close to the business case. They actually are accountable for the ROI of the company. So not just stay close to it. They actually own it. They have to understand you don't have to be a data scientist, but you need to understand how to derive the value that the technology can bring. And that's kind of the new role that a CFO is playing with this technology and all technologies. So I'm seeing personally seeing a lot more of business partnering and IT partnering and ops partnering with my finance leaders that I work with and my clients. So I do think that there is a shift. It's kind of that where that CFO study was coming from is kind of the early part. So a lot of times you'll see the CFO brought in as towards let's help me with the business case, but not so much in the beginning of the early planning, which is where they need to be involved.

Megan - 00:09:42: And you touched on this a bit, but the role of CFO, it hasn't historically been viewed as innovative, but how can CFOs use their influence to advance innovation and drive advantage in a rapidly evolving landscape?

Monica - 00:09:56: Yeah, I mean, this is great. The role of the CFO has completely changed. They're no longer reporting on the news. They're actually business partnering. They're sitting in the driver's seat. I like to say that they are the stewards of investment capital and responsible, as I said, for the ROI. So that's everything from tech, even sustainability. So it's like, now you have to learn all of these different things to drive the value out of it. So the role that they're playing is much more around of a strategic advisor. So even things like storytelling and communications have become much more prominent skills that we see from the senior finance executives. And it's still the number crunching. You still have to have the foundation of finance and accounting, but you've got all these additional skills on top of it. And they really need to use their influence and kind of lean into the risk, like making strategic data-driven decisions. And data is going to be a huge part of this because data is going to help you derive the insights, which is going to help you make those decisions. So I think they weren't seen as innovative before, but they're now seen very much in the driver's seat. And oftentimes we even see like CFOs kind of becoming the next CEOs as well.

Megan - 00:11:00: And how do you see generative AI altering the finance landscape in the next, let's say three to five years?

Monica - 00:11:08: Yeah, I mean, I hope it alters the landscape in the next two years. It's clearly that the rise of GenAI has had a profound impact on organizations and leaders. In my conversations with CFO clients globally, so one thing I didn't add is that my role is also global and cross industry. So I'm covering all of the industries here. The focus has really shifted from if AI should be part of the business strategy to how can we harness that AI for efficiency and for growth. So it's no longer an if, it's not a plus AI, it's an AI plus. That's the shift that we're seeing now. And I think in the next kind of few years or immediately, we're seeing a lot around kind of low hanging fruit where you can get quick wins and immediate value to really just show this technology is making a difference. It's like augmenting yourself. You're having like an analyst. It's not being replaced by a robot, but you've got something kind of helping you. So you can look at a lot of these low hanging fruit things like collection, and reconciliation. But then in over the next three to five years, I think what you're going to see is a lot more where we're going to leverage generative AI for something like FP&A. So really the strategic finance part of the business and not just the core finance part of it. And so I think the landscape will look very different, but it's like everyone's basically going to have these agents and assistants like on their desktop that they're constantly using. It's something that I do every day. I use our own IBM Consulting Advantage assistants all day. And I find that I get hours back into my day.

Megan - 00:12:40: And what specific ways can generative AI enhance operational efficiency within finance teams? And what early examples are you seeing in your role at IBM Consulting?

Monica - 00:12:50: Yeah, GenAI can help CFOs navigate a complex risk landscape. It can make people feel more confident in investment decisions. So things like mergers and acquisitions and divestitures. And most importantly, it helps to increase that accuracy of reporting and forecasting. So if you think about kind of like, what are the major outcomes that a CFO is looking for, it's going to be around things like control, accuracy, productivity, profitability, growth, and cost takeout. And those are all ways that GenAI can help enhance, not replace, but enhance to help with decision making. So companies that are using AI in their finance functions, they're reducing costs by automating some of the critical tasks like financial planning and accounting and procurement. AI adoption has already really helped reduce sales forecasts. And we've seen this in one of our IBV studies, reducing sales forecasting errors by 57% and reducing uncollectible balances. And then cutting the month end close cycle time by 33% and heading more towards this continuous close that clients are always asking me about. But I think the biggest area, and I think I mentioned this before, is really FP&A. And if we can get more towards like a zero touch forecasting or as close as possible to that, that's then going to put finance in a position where they are driving marketing and they're driving sales and they're driving supply chain. So it kind of puts them at the front instead of at the back, where they've typically been in terms of reporting on historical news.

Megan - 00:14:23: And I'm curious, I know like IBM had Watson way back in the infancy of AI. What has that evolved into? And what's next for IBM?

Monica - 00:14:33: That's a great question. For IBM, we still have Watson, but it's watsonx. There's watsonx.ai, watsonx.gov, watsonx.data, watsonx.orchestrate. So orchestrate is really like that's kind of the assistance behind there. Or orchestrate is like helping you taking over different parts, tasks of your kind of job that you don't have to do anymore. And you can now focus on kind of these strategic tasks.

Megan - 00:14:57: I guess that's the goal. I mean, we all want to get rid of the...

Monica - 00:15:00: Yeah, it's like goodbye busy work, right? You don't have to worry about all the small stuff, and think about how much time, especially in a finance organization, somebody spends like 50% of their time in spreadsheets. I mean, it would be amazing to just take 10% of your time and learn how to prompt. I mean, you don't have to go build the LLM or build the agent behind there, but you just need to know how to kind of use it. So really, that's more around the assistants and the agents and kind of automating some repetitive tasks and how to simplify those complex processes. I think the other really, really important one is around data and Gov. Making sure you have governance around your data is going to be incredibly important. I think that's kind of one of the biggest risks that I'm hearing is how do I even trust this? How do I trust the data that's there? I'm putting my shareholders' trust in this, but this is how we scale. It's around kind of managing and monitoring your AI using this single platform of WatsonX. So that's kind of what's new with.

Megan - 00:16:02: And with your emphasis on human-centric transformations, how is it that organizations can integrate generative AI while still ensuring that human judgment and ethical considerations remain at the forefront?

Monica - 00:16:15: The main thing is people are still at the heart of this. It's not about being replaced by a robot or AI, but how to augment your job so that you can do more strategic work and not get caught up in the repetitive tasks and the details in the spreadsheets. You know, as companies are kind of racing to discover all these incredible new things GenAI can do, business leaders need to think about the conversation about what it should do. They need to foster a culture around AI ethics and, you know, aiming to optimize AI's beneficial impact when reducing risks and the adverse outcomes for all the stakeholders. And that's really in a way that prioritizes human agency and well-being. So in regards to kind of ethics, I know I touched upon the whole lots of next.gov, but that's really key there. I mean, that's how you can scale. It's how you've got responsible AI and make it transparent, explainable. I mean, all of these are really important. It's a tool, but human intelligence is always going to be there and it's always going to remain crucial. You will always have to have that kind of human plus AI element to it. It's just going to be more about integrating it into our everyday life, into our work. Innately, like human skills are still going to do those things, like be creative and question and problem solve. Because a large language model is like a toddler. You have to teach it, right? It's not always going to be right. And that's part of it too. It learns and it can't learn without the human element there.

Megan - 00:17:37: And as GenAI becomes more prevalent, what new risks do you anticipate emerging? I know you touched on it a bit with talking to your clients about how can they trust this, but how can organizations proactively address these challenges?

Monica - 00:17:51: Yes. So this is great. So if it's developed in the wrong way, it can be dangerous. It can also just be wrong. And that's what I was saying. It's like a toddler. It could completely hallucinate or produce like toxic results. And I'm going to give you an example. I have a colleague who was putting together a presentation for a client in Europe and he had asked the model, can you tell me the five specific to audit, like the five audit companies that do X, Y, Z in this country. And it's like spits out this report. And he was like, can you do a comparison of them? So it spits something else out. And he's asking it all these questions, right? So that he basically can come in with like, here are the top five companies that you should be looking at with this audit initiative that you're trying to get to. And the very last thing he asked was, can you please send me the sources? And it said, I made three of them up. And he just sat there. I was like, I was ready to use this information. And it just told me, no, I cannot send you a source because I made up three of the companies. So that's where you kind of get a little bit scared of like, oh my God, how do I know? So this is where you have to ask questions. So, you know, I think it can be highly believable. It can be super well-structured responses. It can just sound really, really smart. And then it might just be wrong. So without that subject matter expertise that you still need, I think that's kind of the biggest risk. And then I'll go back to my data and my Gov around there because that's where you need to put those guardrails around that.

Megan - 00:19:22: At least it was honest.

Monica - 00:19:22: I know. I know. I mean, look, you have to have a workforce that knows how to deploy AI. You can't just have anyone do it. And that's how you're going to improve those organizational efficiencies, that it's also going to be ethical and reliable.

Megan - 00:19:35: And as companies deploy AI, do you see the workforce changing at all? You said that you can't just have anybody deploying this. So what kind of skills are the future of the workforce around AI?

Monica - 00:19:49: I do see quite a shift here. I think that you're still going to need, especially in finance, those fundamental skills, those finance and accounting skills. It's actually easier to teach a finance person how to leverage the technology, at least I think it would be, than to teach a tech person about finance. And so skills will change. I think the makeup of the organization will also change. So if I look at our own organization internally, we have data scientists who now sit in our finance function. It's not that everyone's a data scientist. We have some. So I think it's this kind of diversity in skills is what's going to be really important. So you've got to have people who know how to do that. And then you still have to have people who still understand kind of the deep finance expertise. I think the landscape will change. You may have more one Persona than you would have had today or less. And then you upskill people in different areas. And this is where I went back to the spreadsheets. It's like, okay, you have 50% of your time spent on spreadsheets. But now you're going to spend 10% of your time just on prompting to get the same, same materials that probably took weeks to put together. So think of like a CFO playbook that you're trying to put together or a management report. But then you've got 40% of your time free. So now it's 40% of the time to focus on more on the insights and more on how to strive my overall goals and kind of strategic visions of the companies. And we've seen that what came out of this IBV CFO Study. 40% of finance roles through 2025, 40% of financials will either be new or significantly reshaped due to technology, you know, to adapt the CFOs really need to be able to evolve finance skills and mindsets. That's the biggest thing is changing mindsets, empowering teams to contribute strategically to that broader organization. And they need to upskill. As I said, you have to upskill to harness technology and they need to implement things like employee training on data, understanding the usage. And all of that kind of comes out in our study as well. There's a whole focus on the change of, you know, what types of skills that you would need there and the mindset behind it.

Megan - 00:21:58: So let's talk about data analytics and how Gen AI can enhance these capabilities for CFOs and what types of insights should CFOs be prioritizing to drive strategic decision-making?

Monica - 00:22:10: So before we even get into insights, I want to go back to the data part of that. And, you know, as I said, data is kind of the I like to think it's the lifeblood that you need behind everything. So data is you've got to get your data right before you can even derive insights, because if your data is wrong, then you're just adding like AI and analytics onto tool, right? And then it just provides some insights on something that might not be right. So there's this framework that I think of, it's called DID. So data kind of derives insights to help make decisions. I think the success will depend on how quickly finance can turn the data into actionable insights, which is where GenAI can deliver the most. A traditional AI can only recognize patterns in financial data and GenAI can then identify key themes and trends and highlight an organization's strengths and weaknesses and really uncover those hidden market opportunities. So by using GenAI, finance teams can be freed from tedious tasks. They can unleash a kind of torrent of productivity and have more strategic contributions, but data is really the foundation behind that.

Megan - 00:23:14: And in your experience, what have been the most significant barriers that you've encountered when implementing GenAI and finance operations? Is it people's unwillingness to change or messy processes? What's the biggest challenge?

Monica - 00:23:28: I mean, the biggest challenge is people. I'll tell you that. Like, that's what we see. I think the biggest challenge is people. There's also, you know, around like there's a gap between kind of a business strategy and technology. So I think it's kind of aligning finance to the business, to technology. So 65% of all CFO surveys, they said their organization's under pressure to act to accelerate the ROI across the technology portfolio. But less than half say that their finance functions are actually closely involved in the development of this. And this goes back to the technology business case, right? Getting and being kind of involved from the beginning. So I think there's kind of, like I said, two things. One is making sure that it's that business partnering and really taking that new role. But the big. Biggest thing is going to be around people and changing hearts and minds and mindsets and setting that example from the leadership at the top.

Megan - 00:24:16: And last question, and I know you've touched on this a bit throughout our conversation, but as the finance function evolves with Gen AI, what skills do you think are going to become essential for finance professionals? And how can companies work to upskill their employees to have these skill sets?

Monica - 00:24:35: So finance is actually experiencing a shortage of skills right now, kind of at this crucial intersection of technology and domain knowledge, because the balance of having both. And like I said, you could, you can have teams where someone is more tech focused and someone's more domain focused. My team now is comprised of, I've got finance domain knowledge. I have consulting knowledge. I have operating model shared service. And then I brought on someone who is much more focused on data and technology and platform transformation and how it relates to finance. And that person isn't necessarily a deep expert in FP&A, but understands how technology can help enhance. And so I think it's very difficult to find kind of the unicorn of someone who has all the skills. And it's much more about making your team the unicorn with the diversity and skills. So through 2025, 40% of those finance roles are either going to be new or significantly reshaped. Like I said, just because of finance technology. And that was one of the findings that came out of this. So it's got to be that balance of two. And it also has to be willing to learn, like learn how to use the technology so that it helps you so that you can get the value out of it. And that's things like learning how to prompt. It's not saying go build a large language model or go build an agent that's going to help you with reconciliation. Someone else can be there to help you build that where you give them the inputs that goes into it. I think some leading CFOs, one of the other things that maybe I'll end with this, that came out of the study was investing in upskilling to harness technology. And they are implementing employee training on data understanding. And the usage is 63% more than their peers. I know it's a kind of a piece that I used before, but that's a big one. And there's a quote that I love around CFOs needing to now be the guardians of stability and the agents of transformation. And that balance is really, really hard. And that requires a lot of different skills to be able to do that.

Megan - 00:26:26: Monica, thank you so much for being my guest today.

Monica - 00:26:29: Thank you. I really enjoyed the conversation. Thanks, Megan.

Megan - 00:26:31: Yeah, me too. And thank you so much for finding the time to be here with us today to share your knowledge. And I wish you and IBM all the best. And to our listeners, please tune in next week. And until then, take care.