Powering the Future - AI Bootcamp FROM FASTCO WORKS AND SAP
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I'm Julianne Pepitone and I'm happy to be your moderator for this event, AI Bootcamp, a Fast Company and Inc. series in partnership with SAP. And this session about how AI is revolutionizing finance.

As we're going to be discussing throughout every part of this AI Bootcamp series, artificial intelligence is changing at just about every aspect of business. It seems everyone's talking about it and for good reason. But the finance function in particular has some special considerations.

There's an even higher need to protect sensitive data, to ensure accuracy, and to make sure that finance stays efficient to keep the rest of the business chugging along. So AI, how can AI keep these core finance tenets at the core while also helping finance leaders focus on that human value-driven work? Here to discuss this and more, I'm so happy to introduce our panel of experts.

Today we have Dr. Walter Sun, SVP and Global Head of AI at SAP, Dr. Kevin Jones, Associate Professor of Management at Indiana University Columbus, and Dr. Amy Dufresne, Chief Executive Officer of HR Certification Institute. Thanks to you all for being here. So AI is on everyone's mind, but today we're homing in on finance.

So I'd love to start just broad strokes on this specific space. Tell me about what the major ways are that AI is revamping the finance organization in particular. Walter, if you could begin. Yeah, sure. Thank you, Julianne. There's a lot of manual labor involved in finance when it comes to closing month-end, quarter-end technologies. And so...

In order to close the books, previously people did a lot of work to take unstructured data and process it into ways that would fit the bookkeeping. I think a lot of the AI technology we have today with generative AI can handle unstructured data and find ways to organize and bring it all together so that a lot of the prior manual work can be automated.

That's great. Can you give an example of the unstructured data you mentioned? So imagine if there's like four to five different divisions in a company and a CFO wants to figure out how the books are. Each of the different divisions can handle the information differently. One person could have it in a spreadsheet. The other person could collect data through, let's say, even email. Another person can have just Word documents. And so as you can see, the structured data, which are in spreadsheets or common separated files, you know, values and files, you can actually process more easily.

in a more organized manner, whereas an email or a Word document has information that's not really structured. And so how do you use AI to find ways to organize, extract the relevant entities, extract the relevant dollar amounts and everything else? That's the technology we're talking about using to help improve the process of organizing and collating all the data sets in the same way. Thank you. And Kevin, same question to you. My first statement is data analysis.

Because there is so much data that is available to us today in the area of finance, we have really no choice but to turn to augmented intelligence, a.k.a. AI.

because it allows us to process all this data and also create frameworks for analysis that may be things we've done before, but may help us to identify other tools of analysis.

And that's really one of the strengths we have today is we are not restricted to what has already been done, but we can actually begin to identify new ways of interpreting the data to advance our financial capabilities.

And I'm sure we'll get more into this, but could you give us a quick example of that? You know, the way that maybe things were being done or maybe still are being done today and what AI can unlock? For example, if you're trying to figure out something as basic as return on investment, okay?

Now, in the past, you had different things that you would use to calculate that particular result. Now, because we have something like an AI tool, we can look at some things, experiment with different products,

potentials, and then come up with, as I mentioned, perhaps a new way of looking at something like return on investment. So we're not restricted to the models that we have always used.

We can identify potentially new models, which can potentially be those that give us competitive advantage. And Amy, you know, I'd love to bring you in from the HR perspective, you know, slightly different point of view here. For you, how is AI helping find finance talent who are fluent in AI or potentially upskill the existing talent to hopefully get them there?

Right. So when I think about AI and how it's really transforming the finance function, I'm thinking about how they can work wiser and faster and be very safe with some of the things that they're doing to produce the outcomes of what's coming out. So when I think about the HR implications of this, where I come from is how do you have someone in the finance be able to operate in their zone of genius?

And if they're doing these repetitive tasks over and over again, you're not really getting the most out of your finance team. And so you really want to give them the tools and capabilities to do those repetitive sorts of things so that they can operate, do the analytics, take those things that are more important to the business and

and really make a difference by integrating those things together. So upskilling is all where it's at right now. How are we transforming? I think we're seeing organizations that are asking for people that have AI in their background. Here's the newsflash. There aren't many people that have this in their background right now 'cause we're all learning as we're going right now. So it's really important to be able to give people that safe space to play with the tools of AI,

and to experiment. And that's where they're going to get better in everything that they do, including finance. I love your framework on this too, zone of genius. You know, I think it's a more eloquent way. I think we hear a lot about let AI do this stuff over here so you can focus on kind of the real human work. But yeah, I really just really like how you frame that up with zone of genius. Well, I won't take credit fully for

Coining that term, Gay Hendricks, who's written The Big Leap. It's a little bit of an old book, but I think it's an oldie and a goodie. And he talked about how do you find people's zone of genius? So I think that that's really what HR and all of us as business leaders aspire to do.

You know, I think you all discussed a few different themes there. You know, we've got zone of genius, talked a little bit about innovation, efficiencies. You know, I'm curious, when it comes to finance in particular, if you had to pick one of these categories, I know it's a little bit of a tough question. You know, where is AI supercharging the most when it comes to finance? Kevin, if we could start with you.

Well, it's data analytics. That, to me, is where the supercharge or superpower of AI comes into play. Because, as I mentioned before, there is more data available to us than ever.

And the idea of people sitting in a room and looking through charts of information or looking at databases of information, that doesn't make sense. It's not efficient and may not be as effective. So our ability to capture as much of the data according to the parameters that we need

and use the agent, the co-pilot, but mostly again, the augmentation of our ability to analyze. That is, again, where we're going. And the other challenge for us is to keep growing with AI as it continues to evolve and becomes a greater part of what we do.

Absolutely. Yeah, that's definitely a point I'm going to want to come back to as well. So hang on to that thought. And Walter, you know, same question for you. If you had to pick, you mentioned a couple of different areas. Is there a certain type of organizational process or kind of a service category that you think AI is supercharging the most for finance in particular? I mean, I think efficiency, like Kevin was saying, is a big area, right? How do you automate mundane tasks? How do you automate repetitive tasks? I think that's a big thing. I think people

I like to be creative. I think Amy was talking about that in her prior answer as well, how the whole idea of you have a lot of things to do in your job and some of it's fun, some of it's mundane, some of it's repetitive. And so if you can use AI to remove the mundane and repetitive, you spend all of your time doing exciting, interesting things.

You get more done and you also are able to be more excited about your job. You come to work, no one comes to work and says, for developers, I'm coming to comment code, right? I'm coming to write code. Right. Obviously, it's part of the job, right? And so it's like, you know, how do I help automate tasks that aren't super exciting? And so you asked a second question about, like, what industries? I think the service industry can be disrupted very well. I think especially customer service, when you think about there are already some bots out there that do basic customer service. And so the idea of using...

AI to help further increase what you call deflection rate, which is the percentage of times that a question can be answered by a machine versus a human. Increasing that can really increase efficiency and reduce the cost. People have to run customer service agencies. And the whole idea is that

Sometimes you're calling a restaurant, you want to know the hours. That can be automated, right? That's just a simple question. On the other hand, if you have a very specific question about like ambience or certain seats you want, you need to talk to a human being. So having an algorithm that helps kind of increase the ability to deflect questions which can be quickly answered by machines, that's kind of where I think AI can add a lot of value. And so...

especially with generative AI, which can even provide very well human-like responses as well. The value is huge in that area, in my opinion. And Amy, I'd love to just shift a little bit from your HR perspective. Walter just mentioned, it certainly seems if you're able to automate a lot of maybe the more mundane tasks and people are more excited to come to work and do the more fun stuff, there's obvious kind of

talent attraction and retention there. But I'd love to hear, you know, a little bit more about that and just more broadly about how HR is helping the finance function to kind of reimagine how they work in this AI era.

Right. I think that HR is being a partner to not only finance, but everyone across the organization, because it's really this mind shift that's taking place. So we did a survey with another organization all about AI research.

And we talked about it on one of our webinars, and we got a lot of feedback from HR leaders who were saying, we're really excited about this. We're really nervous about this. We're really fearful about this. And I think that that's really the sentiment that we're seeing across the board in every function, not just finance and not just HR. So I think it's HR teaming with finance because they're really the backbones of the organization from the backbone.

office of the business, really sort of catapulting the organization forward. And so they could lead the charge in having this culture change happen within their organization. So it's establishing governance structures so that people know what's safe. They're giving tools for people to experiment. We do this at HRCI. We're allowing people to play in these playgrounds that are very safe and protected, but experiment.

See what's open and out there. And I think that it's the mindset that HR and finance need to team up with to sort of lead the organization around this whole transformation of being creative and experimenting and reducing the fear and talking about it. So I think conversations like this are exactly what need to be happening in organizations.

Putting your head in the ground is not the right thing to do right now. It's really being out there and talking about this. So I think this is a wonderful space to be sort of leading the charge and having these conversations. Yeah, I love this idea about these safe spaces to experiment too, because I think AI can mean so many things.

It can seem like kind of this shadowy idea you kind of know about, but I think sometimes it is, you know, fear of the unknown. And if you don't feel like there's a place you can experiment with it, you kind of don't know until you're sort of out of the frying pan into the fire. So, you know, I'd love to stick with you, Amy, on this. You mentioned these kind of sandbox experimental environments. Are there other types of AI powered or AI related products, services?

services, processes that you're particularly excited about in this space? In your case, you know, HR helping the finance function in particular?

So for us, without naming particular organizations, I think it's giving people the tools to have these safe spaces to play around in. For what we're doing and what we've seen work really well is that organizations are talking about this, they're having town hall discussions and highlighting how AI is being used across the organization so that there reduces this fear and anxiety that's taking place.

and really having those conversations about AI and what it means and how it's going to impact your job. And then talking about how exciting it will be. I think both Walter and Kevin said this, but, you know, who wants to come in, wake up in the morning and do these rote things that are very boring and mundane? Everybody wants to contribute and give back. And so I think it's

again, setting up these tools within your organization to run these experiments and try and play. Walter, same question for you. What particular types of AI products, services do you think, are you particularly excited about in this space, especially as it relates to the finance function? What I talked about earlier about dramatically simplifying closing periods. I think

extremely manual, time-consuming, the processes that can require late nights and long hours. And it can be simplified very much with technology. I think employees will be willing to take on with open arms given the fact that it can make their work life a lot better. One of my first jobs in the industry was working in money management.

And unlike quarter-end close, when you manage a fund, you actually have daily close for mutual funds and you have pricing to report the net asset value. Back then, I think 5.30 p.m. Eastern time was the deadline. Oh, boy. So the 4 p.m. and 5.30 is a very stressful manual procedure.

That was repeated five times a week, 52 weeks out of the year. Oh my gosh, I'm stressed just hearing about that. You can sort of see if you can automate it. First of all, I think it makes people's lives better. Second of all, because it's so tough for people to do, I think that people in the industry would be very open to trying it out and using it to improve their livelihood. Wonderful example. Kevin, same to you. I imagine potentially in data analysis, since you see that's where AI is really supercharging, any specific...

AI products, services, processes that you're most excited about? Well, actually, I'm going to take you a little bit different direction because while there are plenty of products that exist, I think an important point to make with regard to what all the products do, and this goes back to our major theme, is creating efficiency. So let's look at processes, organizational processes. And this is what we're trying to figure out is how the work of

Data analysis, finance, strategic planning, all of these things are now changed because of our ability to turn to a informed assistant, okay, aka AI.

which can do something we've always done. We've done modeling in finance. Well, there's new tools to model in finance. There's new tools to look at revenue growth potential versus potential loss, profit loss, and so on and so forth. We go all through the financial terminology, but these tools simplify things for us as

at the same time allow us to access a broader sphere of data to enable us to make decisions that have a greater probability of success. And that is what the tools allow. And now again, we're not replacing human judgment. This is an important point. It is not replacing human judgment.

It is saying, all right, these tools provide us with a way for us to reflect, to think, to make decisions with. And once we use them, we recognize that we have strengthened, augmented our ability to perform rather than take away from our ability to perform.

Thank you. And Kevin, we'll stick with you on this one. You know, from your management perspective, for finance executives who are developing their AI strategy, certainly is going to take collaboration with their tech colleagues in the CIO or CTO offices. What are some of the key questions or, you know, conversation topics they should be broaching with those colleagues? Well, we can start first in the C-suite, okay? How is AI transforming our organization?

How is it transforming our people? How is it transforming our processes? How is it affecting our ability to be competitive? Okay. So these are questions that we, it's a base question, is that we recognize that generically artificial intelligence has been here. But as we go forward, the increased use of AI is present, right?

And also now, as we look at organizational transformation, which I think is key, are we transforming in a way that...

aligns with the culture we are establishing? Or are we needing to now potentially shift our culture to incorporate how the technology, the external driver of the organization is requiring us to be able to meet the changes that are occurring in the external environment? I'm sorry to sound so professionalist on that, but that's kind of what I was saying.

Well, that's what you're here for, Kevin. Walter, you know, same question for you. For folks who are tuning in who are developing their AI strategy, what conversations should they be having with the CIO and CTO in particular or with other business units in general? Great question. I think along the same lines of what Kevin said, I think it's asking the question of what will it take for you to adopt this technology? I think we should build metrics,

and measurement tools if they don't exist already of like, you know, what are the costs for adopting or benefits of it? And so I think if you can have a good metric to say, hey, look, I have a service industry. I have certain metrics I track. Do I see improvements by using this technology? And if so, how much do I save? How much more efficiencies do I get?

How much more throughput do I get? I think that answers the first question. And then you talk about infrastructure. The question is, can you work with engineering teams and say, do we have the infrastructure in place to have everyone adopt this technology? If people want to try out some generative AI, is there a way for us to all use it in our corporate network, if you will?

And on top of that, finally, I guess it's just looking at the opportunities, saying, look, you know, there's new technology all the time. And I think Amy was talking about experimenting, trying things out. I think that having an opportunity to say, hey, we can even beta test this in one division. Let's say we have four different finance groups. One group could try it out, see if it works. And if it works out well, then we can roll out to everybody. So I think that the whole idea of what's going to take to adopt technology and can we have a rollout strategy to bring it through the whole company.

And Amy, you know, from the people perspective, at the end of the day, this is about people coming together, having these conversations, asking the right questions for finance and kind of the CTO office in particular. What should folks keep in mind? Right. So a couple of things I think that they should keep in mind. First is you want to dream big around this, but start small. You take the most time consuming process. You look at that and chunk it down. Use AI to help with those barriers.

those small wins at the beginning don't start huge. The second thing that I think you need to talk about and make the decision internally is as you're evolving your technology, are you going to evolve existing technology that you have? Are you going to license that or are you going to build it? Those are the questions that you need to have organizationally onto how you're going to evolve your tech stack from a financial perspective and what does that look like?

I think you want to make sure that whatever the third point is to be safe and make sure that everything that you're doing is private because this information can get out there. Everybody has started to hear some of these horror stories so that experimentation needs to be done in an environment where things are safe and private. And then make sure people are monitoring and interpreting what they're seeing and coming out of AI and adjusting accordingly.

to the outcome of what it is that they're trying to do. So those are really the four points when I think about sort of that CTO, CIO discussion and CFO and sort of what should be going on in the C-suite. Those are those conversations that

the C-suite should be having. Thank you. And finally, briefly, I would love for you all to look ahead a little bit. I know, again, it's a bit of an unfair question since AI is changing so rapidly. You know, where we were a year ago, three years ago is very different. But, you know, in the somewhat near term, as far out as you're comfortable, you know, looking ahead,

How do you see either AI finance solutions evolving or how do you see the finance function evolving over the next few years in this AI era? Walter, we'll begin with you. Yeah, I think there's a lot more process efficiencies. So in the old days, you get a bunch of papers by hand. You can digitize that quickly with OCR, right? And once you have the technology digitized, you have, as I mentioned earlier, talking about aggregating unstructured data into structured data, having it all put into a format that's easy to consume.

And then having finance workers feeling comfortable speaking and communicating with machines using natural language. One of the biggest parts about generative AI is the fact that instead of having to know how to write code or how to do anything in a very sophisticated technical manner, you can use what's natural to you, which is

spoken language, English or whatever language you prefer to speak in, talking to a machine and saying, hey, give me a report, give me the projections for the next six months. What's the month-to-month spend? What's the run rate? All that kind of information can be done by humans talking to or communicating with a machine versus knowing how to find the right document, finding the right application, opening up, training someone and explaining to people how to use it. I think a lot of these efficiencies will be handled in this manner.

Amy, same question for you. How do you see either AI finance solutions evolving or perhaps, you know, from your perspective, the HR and finance relationship in this era of AI? I think firstly is I'd like to echo what Walter was saying about the use of natural language and really catapulting the functionality of finance. I think that's key to really transform finance from being bean counters to really being those

future focused, really helping with the business. And I think that's what I think finance wants to be more strategic and focused on the future, as well as HR does too. So I think those two functions continuing to walk arm in arm with the rest of the C-suite to move these efforts forward around AI, they need to continue to walk arm in arm and move forward. And Kevin?

I agree with both Amy and Walter. They're right on target and the NLP in natural language processing is going to, well it is already, and going to be even more a game changer. Think about meeting prep. When you go to your meeting, how are you going to perform or prepare, I should say.

Yes, you will still read, but at the same time, you'll take your digital assistant and you'll speak with your digital assistant. You'll run scenarios. You'll talk about what do you think the anticipated outcomes will be of the meeting. You'll plan before you go to the meeting with your colleagues.

Then in the meeting, not only will you be speaking with each other, but when things come up, you'll refer to the AI and talk to the AI and then talk back with the AI and then talk with each other. And then you will make decisions. In other words, AI will be in the room with you. Now, we're not going to talk about robotics.

We're not going to get over there right now. However, we are talking about using a digital system in a way that interacts with us, not just something we have to go onto a computer screen and look up, but we can ask the question of it and it can respond not with some random data, but from data that we know is accurate and also useful. Long story short,

The future C-suite basically includes AI. Well, I think that is a great place to leave it. And that is our time for this session. I want to thank each of our panelists. Thank you all so much for sharing your expertise. And thanks to our audience for being here. We really appreciate you joining us for this session on finance and for participating in this AI Bootcamp series. On behalf of SAP, Fast Company, and Inc., I'm Julianne Pepitone. Thanks for tuning in.