Name: AI in Finance
Uploaded: 2025-12-08T18:16:04.601Z
Duration: 1 h 24 s
Description: AI in Finance

Transcript for "AI in Finance": Hello. Welcome, everyone, to the Real AI at Work Academy. We're so thrilled to have you join us for our session today. We're gonna cut through the noise and focus on how artificial artificial intelligence is delivering real measurable value today. And, we are going to zero in on one of our most dynamic audiences, which is finance. So we're talking today about, everything AI and finance. So just a few quick logistics before we dive in. We welcome questions throughout the presentation, and you can use the q and a box in your viewer, and we'll address some of them live throughout the presentation, and then if we have time, perhaps a few more at the end. But I think you can see that in the on the right side of your screen. If you're having any trouble seeing slides, please use the expand or zoom feature. And for audio, please use the chat feature to let our, facilitators know, and they can help address any issues you may be having. So we'll start out with some quick introductions. My name is Liz Alderman, and I'm the senior director on the product marketing team here at Coupa. Jacqueline, can you go ahead and introduce yourself? Absolutely. Good morning, good afternoon, good evening for those across the globe. Jacqueline Slottman. I'm with KPMG. I'm a managing director, and I oversee our Coupa Alliance. Elsa? Awesome. Thanks, Jacqueline. Thanks, Liz. Hey, everyone. Elsa Hanson. I'm a senior solution advisor here at Coupa, specifically focusing on our AI solutions. So I am regularly meeting with prospective customers and existing customers, understanding their challenges, and mapping those challenges to our AI solutions and and demonstrating how we can solve those using Coupa's AI, which is what I'll be leading us through today. So nice to to see you all today, and thanks for being here. Excellent. Thank you so much, Jacqueline and Elsa. So we're gonna start this presentation out with some, actually exciting news. So, before I I walk us through the agenda, we wanted to share a major announcement and also let the audience know that you are the very first live audience to hear about it. So as of this moment, Coupa has just released its first inaugural Coupa Clarity AI Impact Report. This is our analysis of how organizations are converting AI ambition into real ROI across finance, procurement, supply chain, and IT. Based on insights from more than 600 executives, it highlights critical gaps across strategy, infrastructure, and trust, and the seven major actions that leaders are taking to accelerate AI impact. Communications are going out right now, you know, to customers and and to the market, but we wanted you guys to hear about this first. So you can either use the download link, in the docs tab on your screen, or you can also scan the QR code that's up here now. But I really encourage you to take a look at it, and we're really excited that you guys are the first ones that will be sharing this through, you know, our first, Coupa Clarity AI report with. So I just wanted to walk through the agenda at a high level before we dive in. So we're gonna talk a little bit about, you know, why AI and finance right now. We're gonna talk about AI as the catalyst for finance. Jacqueline's gonna join and talk about the KPMG perspective on the state of AI and finance. We'll talk a little bit more about finance transformation, and then I'll hand it over to Elsa who will give us a demo. And then we'll wrap up and share some additional resources for the audience. So, before we get into, that, I'm actually gonna, pull up a quick poll. So we'll go ahead and put our our answer up here. So how would you classify your organization's AI journey in procurement today? So beginner, we're just starting to evaluate, look into AI concepts. Intermediate, you know, we have a few AI projects underway. Advanced, we're actively scaling AI across all of our finance processes. So please go ahead and weigh in here. We're we're curious to see where the audience is at in their journey. Alright. So it's looking like we have mostly beginners on, the the call today, which is great, and some intermediates. So, you know, please, you know, for both audiences, weigh in here with your questions and insights too because we'd love to be able to surface them throughout the presentation. Okay. So let's go ahead and talk about why AI and finance now. So, finance teams, you know, they're at a turning point right now. We at Coupa, you know, through our research, can see that 82% of global CFOs say that their organizations are actively investing in AI based financial automation, and this is to reduce costs, increase accuracy, and improve compliance. Yet, there's still many that struggle with fragmented systems, you know, whether it's contracts, invoicing, or payments. And, you know, this compounds and delays insights and also erodes trust in numbers. AI acts as that bridge, and it transforms finance organizations from manual and error prone to automated, predictive, and transparent, unlocking better controls and stronger agility. We spend a lot of time talking to finance leaders about these challenges, and, you know, we hear a few common themes, you know, across across these different, areas. So, change management and workforce impact with a limited hiring pool of skilled AI professionals, particularly in spend management, as well as, you know, employee resistance to adopting AI, requires very careful change management. Lack of visibility and control over company spend can result in hidden and even escalating costs, missed savings and, you know, what we call value leakage from poor visibility across different spend categories and business units. Pressure to deliver measurable ROI on AI and digital transformation, you know, can kind of, you know, kind of flood the zone and and lead to skepticism across the organization, but particularly at the executive level. And pressure to adopt AI to remain competitive. You know, you're aware that your competitors are doing it, but moving too quickly without proper oversight can backfire. Moving too slowly also, you know, creates risks and can cause you to lose market share. And then, you know, in the background, the evolving regulatory landscape, ethical considerations around AI decision making, all add more layers of complexity and risk. So without a skilled enterprise wide approach, the risk isn't just overspending. It's losing control of your cost base, missing out on savings, and falling behind your competition. If you're not on the right AI platform, you know, the total cost of ownership, you know, can exceed plans. You know, there's all kinds of different, you know, kind of landmines that you're avoiding, and you wanna make sure that you get it right. So let's talk about, you know, how AI can be the catalyst for change in finance. So AI isn't just a feature. It's a fundamental shift that you need to master for your across your entire spend workflow. For finance, procurement, supply chain leaders, this means moving from being bogged down by manual tasks to being proactive and focused on strategic outcomes. Coupa's AI provides that speed and intelligence and eliminates the manual work and helps your teams focus, you know, in on really what's going to create impact and move the needle for your organization. So I wanted to walk you through what, AI in action looks like across the Coupa platform. So, you know, kind of starting upstream and working our way down. So Coupa AI analyzes category strengths as well as weaknesses and risks. It empowers procurement teams to build strategic plans with 25% greater accuracy right from the start. You can use AI to model millions of supply chain scenarios, enabling your leaders to quickly mitigate risk and capture massive savings, which can translate, you know, up to 10 to 25% reduction in transportation and in transit inventory costs, which can ensure greater supply chain resilience. And, you know, moving through to to intake, our AI powered summaries use natural language processing to help approvers instantly understand requisitions during that intake process, and accelerates approval cycles by 25% by removing bottlenecks, helping to accelerate approvals. Our natural language AI can also generate concise summaries of completed sourcing events, which gives your procurement teams more visibility, reduces that review time by 40%, and delivers highly actionable insights. Our Gen I capability also delivers accurate instant overviews of complex contract during import or negotiation, empowering your teams to, you know, cut their review time in half, and speed negotiations by 50%, which results in much faster contract negotiation. Our AI driven commodity insights leverage our Coupa community data from our own customers, as well as machine learning to optimize supplier strategies, which can help deliver procurement team savings of 7% on average. And with GenAI and machine learning intelligently extracting and validating invoice data, you'll reduce your finance team's manual entry errors by an incredible 70% and completely streamline your accounts payable process, which leads to, you know, much improvement in AP and invoice automation across the board. Our community powered AI identifies suppliers that accept virtual cards and recommends optimized spend shifts, enabling your teams to increase virtual card usage by 35% and, helping to get more of those rebates in the door. So, you know, really boosting your, your working capital and your your your rebate attainment. And then finally, AI alerts instantly flag any transactions, behavioral, and inconsistent spend risks across your organization, which cuts down on manual auditing by 50% and really helps to shore up, you know, your risk and auditing posture. So the bottom line is that Coupa's platform was built to help you act with both intelligence and speed. And with that, I'm gonna hand it over to Jacqueline, who's gonna walk us through the KPMG perspective. Everyone, really appreciate the time being here today and and wanna talk a little bit specifically about what we're seeing in the market when it comes to AI in finance. I've spent most of my days sitting along both current and prospective clients, and and I'm I I would say the number one question I'm consistently getting asked is, is the AI hype real? Quickly followed by, is the AI hype in finance and procurement actually real? And for those of you that have been in the digital finance and procurement over the last decade, we've witnessed several waves of technological hype. You might remember excitement surrounding blockchain or RPA a few years back. There was a time when experts predicted that these technologies would potentially revolutionize our world and perhaps render human intervention unnecessary. As time passed, many have concluded that those technologies really fell short of the anticipated impact. I think those of you that have been in this space for some time, it is unlikely that you would say RPA transformed allowed you to drastically change the way that you did business. Fast forward to about eighteen months ago, similar doubts were echoed regarding AI. With the evident widespread of platforms like Gemini, Copilot, GPT, it's becoming more and more realistic, and we're seeing how these solutions in AI is impacting us in our personal lives and how transformative it can thus be in our procurement and finance lives. When we look at the corporate landscape, I know that Liz mentioned 87% of CFOs are actively investing in their AI landscape. Our studies show over 99 of organizations at this point are exploring the applications of AI agents. AI agents then are actively being piloted to about 40% of those organizations. Even more telling, over 12%, and this number is rising by the day, AI agents are actively being used across various processes within procurement and supply chain. There is no doubt that the level of engagement and adoption surpasses what we saw with RPA with blockchain, specifically in the source to pay and finance space. The reality really is undeniable. AI has arrived. It's no longer a distant possibility. It's actively reshaping how the source to pay processes manage. As professionals in this dynamic field, understanding AI's capabilities, how you can use it, how you can integrate it, how it's going to modify your workflow in day to day life is crucial. We believe that we will continue to see sustainable change, and we'll see a lot of that change within the finance space. Specifically with what this means for finance, the rapid evolution of AI is leading to a future where we believe and experts believe up to 80% of today's finance activities will be automated in AI enabled. Imagine a world where all transactional activities are managed through automation, generative AI, agentic AI. As each of your organizations continue to embrace that broader adoption and integration of AI at scale, we will continue to witness a true transformation in how daily operations are conducted. The shift is expected to not only increase efficiency, but also open up new possibilities for how we think about the finance role and the innovation that we're expecting to see within finance. As AI progresses, traditional corporate functions will really blend together and eventually, many will disappear entirely. This integration challenges the conventional structure of separate departments and leads to the creation of smaller and more productive teams. We'll talk a lot today about where is agentic AI within very specific finance activities going. The automation is spanning really across the end to end process. The barriers between what historically was front, middle, and back offices are starting to break down, and there is more integration between all of these teams, and it really remits a new scope and responsibility for finance professionals. As we think about AI continuing to be poised within all of your organizations, it's really becoming the modern enterprise operating system. To stay ahead, finance must integrate these Agenstic platforms into all aspects of your operations. Moving beyond just how you historically thought about your ERP and source to pay systems, AI will really dominate the core and be connecting all of these platforms together. The impact of AI within finance is one of the probably the most exciting areas that most experts believe you are going to be able to gather and really transition from some of these transactional activities to more strategic activities. So let's talk a little bit about what will that ultimately look like. As we look back on the progression over the last several years, many of your organizations have probably already adapted some level of generalist chat platforms. We kind of consider that that very first bucket on the left hand side. These are tier zero supports. This really set the basic stage for understanding AI utility. You maybe have a chatbot today where you're asking questions, what's the status of my invoice, what's the status of my payment, etcetera. This was really leveraging large language models and serving as that tier zero support. The reality though is significant advancements have happened over the last year. The market began introducing true AI agents that are capable now of not only spitting back a response, but both searching for information and executing those tasks autonomously. This marked a pretty significant shift from your information processing to actionable intelligence. Today, as we're really approaching that this new frontier of AI, you'll often hear it referred to as multi agent systems. I wanna highlight Navi within the Coupa platform as a really good example of this. Navi is not just a single AI agent. It's not just a chatbot. It's not just acting and doing one specific activity. It's an entry point connected to a network of agents, each dedicated to distinct tasks. You may have one agent that is going and pulling a report around around sourcing. You may have one that's asking for training materials on how to submit an agent or no. I'm sorry. On how to how to gather, an invoice. You may have one that's assisting with actually creating a sourcing event. This multi agent system, some organizations referring to as AI companions, will continue to take place in the procurement and source to pay Coupa landscape and ultimately likely connecting with agents that you have in the back office as well. Navi's design really creates a seamless experience where multiple agents are working collaboratively to enhance the ultimate effectiveness and streamline your operations. It brings forth a really interesting paradigm in which AI is not just a supportive tool, but it's an integral aspect of strategic operations. As we continue to move forward, it's vital for us to stay informed about these developments and really understand how multi agent systems can be integrated into each of your own processes for optimal impact. What does this really mean then if you are someone sitting in the finance space today? What is where are the key use cases for AI? As we are seeing AI continue to evolve, we think about some of these traditional roles. You've got your AP analyst or an FPNA analyst. An AP analyst, if we were to consider even several years ago, 80% plus of their job was likely in those first two buckets, invoice entry and payment processing. Someone was manually processing invoices, manually processing all of your payment runs to ultimately get get payments out the door. As we think forward though, that transactional processing is being heavily automated. Integrating AI into these roles, you're empowering your finance professional to focus on those activities on the right hand side. More time, which is more strategic, actually executing with DSO management, actually acting as a commercial advisor, supporting and working with Treasury on what does capital and cash management look like. Similarly, on the FP and A side, that role is drastically evolving. These analysts are likely to move away from traditional data gathering event driven tasks to become more strategic advisors to the business. This transition allows your finance teams to make more informed and impactful impactful decisions. In a moment, you'll see Elsa give a demonstration of Navi. If we think about how does that fit into these couple of roles, it's a great example of AI's transformative power. Navi can handle spend visibility requests nearly instant. So that bottom bucket of FP and a a analyst where they're spending this time gathering data, cleansing that data, understanding that data, what traditionally involved hours or days or even weeks of gathering that data is now being completed within seconds or minutes with these agents. This kind of efficiency not only saves time, but it also enhances the accurate accuracy and responsiveness of your finance teams. The ultimate goal is continuing to move to that right hand side where these roles begin to shift into more strategic commercial advisors and intelligent advisors working collaboratively with your front office and with the business. If we double down on that briefly and you think about what this means within your GBS organization, A typical GBS organization is likely consisting of these several buckets. You've got your source to pay activities, your order to cash activities, and your R to R activities. And similar to what we had showed on the previous page, a lot of this today is manual processes. The assumption today is those different activities that you see in gray across all of today's GBS finance activities, they are going to become automated over the upcoming years, many of which will be done with the agentic AI capabilities. In terms of actually manually in processing invoices, manually matching POs, manually looking at p card receipt verifications, etcetera. So that AP analyst starts to shift to what we talked about and becomes an exception analyst. Many of you who are already on your Coupa journey, you are actively seeing this today. You are no longer manually processing a PO, an invoice, or receipt. You're taking the exceptions, and those are what's getting flagged, and your AP team is really working on set exceptions. And this provides all of us on this call with a really unique and interesting place. When we think about what does tomorrow's finance activity look like, what you see here is really where we believe these organizations are shifting. They are going to be doing more error handling, more strategic activities, and that requires a new thought process from everyone to really understand what the new skill set of each of our people need to become. This transition really comes with expanded scope of responsibilities. So as the number of automated tasks reduces overall, the additional capacity is realigned to focus on these activities. Increased efficiency and value creation are going to be the core benefits of this redefined role. I wanna really conclude that, and I'm sure everyone is is antsy and excited to see the actual demo from Elsa. As AI capabilities continue to integrate deeply within our processes, I just wanna refocus and and make sure that everyone understands they will it will evolve to become more strategic partners in driving efficiency and value creation for the organization. So by embracing these changes, we position ourselves to really harness the full potential of AI within our finance operations. It's exciting for us to see platforms like Coupa who are making significant investments to enable your people. This is a shift. As you watch this demo of these capabilities, I encourage each of you to really be thinking about what does this mean for your typical finance role? How does their day to day change? How does their role change? How do we make sure that we're thinking about utilizing these capabilities to ultimately change the way that we conduct our day to day jobs? Again, wanna wanna thank everyone for being here today. This is a conversation that we are having with all of our current and prospective clients. How do we get the most out of AI within our finance applications? So excited to to see the rest of today's conversation. Fantastic. Thank you so much, Jacqueline. So I am, I'm standing between, the this and the demo, so I will move forward because I know everyone's very excited to to hear from Elsa. So, I just wanted to double click into finance transformation, you know, coming off of Jacqueline's, great content that she just shared to talk a little bit about, you know, kind of the tangible, you know, before and after coupa.ai, you know, and and how finance is kind of seeing this innovation play out, in real time. So, you know, where we started with disconnected manual processes across all, you know, diff disparate systems, limited visibility, and delayed reporting, you know, Coupa really comes in to unify the the operation side. And with the connected platform, our customers are able to access real time insights and have that end to end control that can help, you know, increase visibility and improve the speed of decision making significantly. You know, we hear you know, and we know that manual contract reviews add a lot of time to decision making. They're labor intensive. And, you know, another area that, where there's a lot of manual work going on is within invoice processing. So, you know, both of these areas come together to, you know, create significant risk and error rates that take finance kind of out of that more strategic work that they'd rather be focused on. And so what Coupa is able to do for these teams is to really automate, the tasks across contract analysis and invoice processing to help mitigate those errors and free up your teams to help focus on more strategic work. You know, an example of that is that our AI dashboards, you know, can identify savings, you know, automatically for these teams so that they're able to act on it, quickly. Budgeting and forecasting based on spreadsheets with historical snapshots, you know, inaccurate and slow. And, you know, this can really be, from a forecasting perspective, compounded by, you know, highly manual inefficient work flows, you know, that kind of restrict access to information easily and add a lot of, you know, time and effort to that. So what Pupa can unlock for these teams is a much more precise forecasting and budgeting cycle, and we're able to implement, you know, really powerful recommendations based on our $8,000,000,000,000 worth you know, dataset based on transactional data. And, you know, this helps reduce manual errors, you know, reduces data entry substantially, you know, freeing up time. And, you know, one area that, you know, a lot of our customers are laser focused on is around fraud, and making sure that, you know, compliance is adhered to, you know, that spend policies are enforced. And, you know, we know that our team spend a lot of time monitoring this, you know, looking for duplicate payments, invoicing errors, things like that. And a lot of the time, that is only discovered after the fact, during audits or reviews, which could take place, you know, months after the actual, you know, payment was made. So what Coupa can do is leverage our our, AI dataset to be able to identify suspicious transactions, any noncompliant, you know, transactions, duplicates before the payments go out the door. This is a really powerful tool to help prevent errors from, you know, occurring and also reduce the amount of effort it requires to be able to analyze, you know, payments and and try to find them. And then finally, you know, we know that innovation is really challenging in an environment where there's a lot of different tools and systems being used. And not only does that, you know, prevent innovation from happening, it also introduced a lot of security risks and increases the cost of integrating, across, you know, a complex tech stack. So what, you know, what then what Coupa does here that provides a huge benefit is by having a connected end to end platform, it really helps accelerate that speed of innovation because finance, you know, can iterate and and play around on a connected system with a shared pool of data, you know, where, you know, where information moves seamlessly across the platform, you know, which provides that interoperable AI framework. So I wanted to, you know, just quickly dive into Adjenic AI, which, you know, is obviously a huge area of focus and innovation, for for Coupa. So, you know, we're we set the pace for AI. We have over a 125 AI capabilities to date, and we add hundreds of new capabilities each year. And that extends to our portfolio of AI agents, you know, that work really closely with our finance customers. So because of this immense proprietary dataset that we have, we're able to build meaningful multi turn conversational agents that provide accurate prescriptive actions based on $8,000,000,000,000 worth of transactions. So I share this because I want you to keep this in mind when you're evaluating agentic capabilities, you know, from other providers, in other parts of your business. And consider that, you know, summary or content analysis agents are likely less action oriented and, you know, add kind of questionable value to your organization. So our team of Navi dot ai agents, and Elsa's gonna, you know, share some of this quite shortly. They act as a team of specialized digital teammates. They can do complex end to end tasks with minimal human intervention. And there's a few examples of agents on here that I wanna call out, that are especially useful for finance teams. So our Navi analytics agent, analyzes data faster. And I know Jacqueline was talking, you know, about, you know, how AI can come in and and do this work, you know, almost immediately at the speed of thought, and that's how we think about it. So you can generate custom charts and reports literally at the speed of thought. It it analyzes data so quickly. Our operational reporting agent, you know, this really helps, you know, cut down on the level of custom reports and the work that goes into that for finance teams. So this agent can do advanced skills such as custom data table generation. It can do real time spend and transaction reporting, multidimensional filtering and sorting, and all types of export and sharing capabilities. And this one is really tailored particularly for finance analysts and any procurement professionals who need to be able to, you know, access and build fast, accurate, customized reports. And then I I also wanted to highlight the request creation agent. This agent converts unstructured contract information into service requisitions very quickly. So this is invaluable, if you wanna ensure that POs and invoices against these services contracts are completely aligned with the terms of that agreement with your supplier. So with that, I'm gonna hand this over to Elsa who will bring all of this to life, with her demo. Awesome. Thank you, Liz. I'm excited to dive into the demonstration and actually see a lot of these capabilities that we heard from from Liz and Jacqueline live here. So I'm just gonna go ahead and share out my screen. Awesome. And as I go through this demo, continue to to submit your questions through the q and a. Our team's monitoring the the q and a, and we'll pull up questions that make sense to answer live as I'm I'm going through, and we'll we'll make sure we follow-up with anything we're not able to answer live. Awesome. So looks like you all can see my screen today. So I mentioned I'm a solution advisor here at Coupa, working very closely with both perspective and existing customers and understanding their challenges and and then applying AI to solve those challenges. One of the the number one challenges and and reasons that customers, especially folks in finance, come to Coupa is really a lack of spend visibility. You know, today they're they're hindered by manual processes. They've got data living in disparate systems, maybe spreadsheets, and it's very difficult to get an accurate picture of your spend, let alone know how to action that spend and and drive strategic outcomes. K. So this is changing, with AI and specifically with Navi. You just heard from Liz on how we can start to use our Genetec AI agent Navi to pull instant insights off your data. Right. So I'm gonna go ahead and ask Navi to build me an analytics chart of approved invoice spend by invoice month in 2024. Natalie's Navi's tapping into all of your spend data in Coupa, pulling the relevant filters and dimensions, and putting together a visual chart by your request on that invoice spend by invoice month. It's also asking me or guiding me to go ahead and navigate in to Coupa Analytics where I can see exactly how Navi came up with this report. I can see the filters, the visualizations that Navi applied. I can then ask Navi to further edit this report. I can save and schedule this report out to land in our executives email inbox, or I can add this report or chart to an existing dashboard or start an entirely new dashboard. But to the, you know, earlier point of finance teams are are burdened with a lack of spend visibility due to these disparate processes, manual systems, one of the key challenges is not just getting insights off the spend but actually consolidating spend so that Navi or a user, has a clear starting point. So with Coupa and with our AI spend classification solution, we can actually, take spend not just from inside of Coupa, but also outside of Coupa. So maybe spend coming from third party systems, maybe multiple ERPs, maybe multiple business entities. And we can consolidate that data using AI, cleanse that data, and then normalize that data so that you actually have an accurate picture of all of your spend on day one, on the time you go live with Coupa, whether or not that spend originates in Coupa or external. Right? So we're looking at one of the standard outputs of our AI spend analysis solution, a dashboard that's ultimately showing how we've normalized all your spend data. So in this case, we can see that you're operating out of three different companies. Maybe today, this spend lives in three different systems. We've used AI to bring that data into Coupa. We've gone ahead and normalized your over 18,000 suppliers down to nearly 14,000. And then we've pulled out and normalized key spend categories, subcategories, your spend by period, as well as the spend on contract and spend with PO. Right? So we're giving you a actionable, clear, and accurate starting point with your spend the day you go live with Coupa so that you can start to then operationalize this spend, drive strategic outcomes in Coupa to influence this spend. For example, if I filter this spend by my normalized supplier, Microsoft, I'll do a quick search here for Microsoft, and I filter or refresh my dashboard here, I can see that Coupa's AI Spend classification has taken what was give me just a moment here what was for separate suppliers, for separate instances of Microsoft, again maybe over multiple different systems or maybe just slight differences in naming conventions which is a common pain point amongst supplier masters today. We've normalized used AI to normalize those four different suppliers down to one, and then are giving you a clear picture of your spend with that normalized Microsoft supplier across all of your companies, across all of your categories by period as well as on contract and with PO. This is one of hundreds of different reports and dashboards that your teams can take advantage of on day one, again, using AI to cleanse, normalize that data, giving you a clear and accurate starting point. Now we have clear visibility into your spend, but how do we actually protect that spend and ensure that spend is within policy, and is free of any fraud, or or potentially misappropriation? Right. So you heard both Liz and and Jacqueline speak to Coupa's AI driven fraud detection or spend control solution, SpendGuard. So I'm looking at our SpendGuard dashboard. This is a solution that drives instant value for our customers. There's almost no implementation timelines. It's available today and can be turned on very quickly, and then it can instantly start to monitor mass amounts of spend. So this solution is looking at your spend holistically. It's looking at spend across your suppliers, your employees, so expense report type spend. It's looking at requisitions, orders, invoices, sourcing. So really a holistic spend control AI fraud detection solution. Since we're speaking about finance today, I'm gonna drill into our invoice bucket. We know that duplicate invoices, fraudulent invoices is a a very ripe area of of business fraud. And with advanced technology, technology like AI, this is only becoming increasingly more risky for organizations as fraudulent behavior or, you know, modern day fraud schemes are very, very difficult for the human eye to capture. So starting with duplicates, SpendGuard is taking, you know, standard duplicate detection a step further. Of course, any system, any technology can look for things like the same dupe or the same invoice number, the same supplier, the same amount. Spend Guard takes this a step further and is not just looking at is the data the same, but is there similarities between two different invoices that potentially could be the same? Right? So in this case, a different invoice number, but the amount's the same, the line description's the same, invoice date is the same, and the invoice number is similar. Right? So this is taking a step further from what the humans can review alone, and this is looking at holistic invoice, data across, you know, your organization, not just at the time a supplier submits an invoice. We can then review, resolve, or or even, reject this invoice at the time of submission if we find that it is truly an a a duplicate invoice. We're also analyzing or our SpenGuard AI fraud detection solution is also analyzing things like unexpected invoice numbers. So, again, very challenging for human eyes to catch alone. Right? In this case, the AI has determined your supplier proactive, invoice numbers always follows the same pattern, and suddenly, we receive an invoice that deviates from that invoice number pattern. Right? Maybe this is not fraudulent behavior. Maybe, you know, this is okay, but, ultimately, your team needs to to take a look and review before proceeding. Right? So this is essentially giving you a real time live auditor across your organization, not just for invoices, but really holistic spend in Coupa and allowing your teams to manage by exception, allowing AI to find those needles in the haystack, surface those needles, and that's where your team focuses their attention. Coupa customers like CBRE and Clorox have both saved over a million dollars in invoice it or in spend, just by detecting duplicate invoices with Spend Guard instantly. Right? So they turned on on Spend Guard and they were able to identify over a million dollars of that duplicate invoice, invoice spend automatically or or instantly with Coupa. So can pay for a Coupa deployment in itself just by having Spend Guard fraud detection turned on and evaluating your spend. Alright. So we have visibility into our spend, whether that spends in Coupa or external. We've got a clear accurate picture of that spend. We're able to pull insights off that spend and protect that spend using AI fraud detection. But how do we start to take actionable or proactive strategic steps, within Coupa that can ultimately influence this spend in the right direction? Right. So I'm gonna drill into our community intelligence or community AI insights. So drilling into insights here, you heard Liz talk about our proprietary data of over $8,000,000,000,000 in growing of our customers contributed secure and anonymized spend. So we're using that $8,000,000,000,000 to essentially make all of us smarter, all of us more effective. So as you transact on Coupa, Coupa is going to, classify your spend across key KPIs. KPIs over a 100 KPIs around savings, efficient efficiencies, and usage. And then Coupa's gonna benchmark your spend against leaders in the industry and then provide specific actions or AI insights, guided actions you can take in Coupa to influence that KPI or influence the outcome you're looking to achieve. So for example, if I want to increase my invoice processing efficiencies, reduce my invoice cycle times using Coupa, I can drill into our community AI insights and take a look at what is my current invoice approval cycle time. In this case, I can see it's just over a day. I know that, our goal is under five days. So the green is indicating we're doing well against our goal, training well against our goal. And we can also see that the benchmark best in class is over what we're achieving today. So we can pat ourselves on the back and know we're doing a a very good job with our invoice approval cycle times and and essentially keep up the good work. But assuming that this was not the case, maybe we're under our goal or under the benchmark, we can then use these AI insights to dig a level deeper and really understand what what can we change, what can we, impact here, or what can we influence to, turn a better impact. So if I drill into the second KPI of the average number of invoice approvers based on the spend volumes, I can actually see how many levels of approvals am I requiring at various spend volumes versus what is normal or average, or I'm sorry. But versus our goal and versus what is normal or average amongst the community. So I can actually see maybe I have too many levels of approvals for large spend invoices when really best in class is is just over one and I can actually make some tweaks to our approval workflows, drill in for get guided steps to take to tweak those approval workflows, to drive approvals quicker, streamline these approval workflows. So that's one example of many on ways we can use these community benchmarks and AI insights to influence our key KPIs or the metrics that matter to us. We can also see Coupa's AI bubbling up the top prescriptions that are gonna have the biggest impact on our specific spend goals. So right at the top is our number one opportunity for savings. There's over 1,700,000 of potential savings here by just reviewing early pay discount insights and enabling essentially more of our suppliers to offer early pay discounts as well as to use a solution like Coupa to automate the invoice processing, streamline the workflows, and enable us to take better advantage of early pay discounts when they are offered. So I'm looking at my early pay discount AI insights. I can see how much our finance and accounting teams have saved today by capitalizing on those discounts. I can also see that there's a lot of room for improvement or opportunity to take advantage of far more discounts based on the discount suppliers are offering today to us as well as the discounts these suppliers are offering to other Coupa community members. Right away, I can see what are the top five opportunities by supplier. In this case, we have a lot of potential opportunity if we can process Microsoft invoices a bit quicker and take advantage of those early pay discounts. We can also start to use Coupa and Coupa's AI insights and process insights to streamline our invoice processing further so that we're actually able to capitalize on those potential early pay discounts. Right. So going into our invoice processing insights, this is how I can see AI is categorizing or tracking how long it takes us to create invoices, to review invoices, as well as to approve invoices. Looking down at the AI prescriptions, we can right away see that we have opportunity to further automate using AI, that review process, and again ultimately streamline the invoice review cycle times. So in this case, one of the top, AI prescriptions is to automate tax code entry for VAT invoices as well as to automate billing account entry for non PO PO invoices. So if I drill into the ability to automate tax codes on our invoices, we can again see that AI surfacing what is the percentage of automatically coded tax lines today versus benchmark, what other Coupa customers are able to achieve, and what can we save in terms of efficiency savings, processing savings by automating this further? We've even leveraged AI to suggest exactly what tax automation rules we should turn on in Coupa to start to automate this processing further, streamline cycle times. Alright. So that is one of several examples, and we could probably spend an entire hour on just going through AI insights and how we can start to essentially continue to streamline, automate the end to end finance process. But I'm actually gonna take a step back here and and start to, start with the the beginning in mind. So we we can start with the end in mind here, spend visibility. But how are we actually applying AI and using Navi to streamline the end to end transaction process that ultimately drives your spend visibility, your reporting, and your AI insights. Alright. So with that, I'm gonna, start diving into the end to end procure to pay process. And I'm gonna start with our AI, Navi powered intake solution, which is gonna be available soon. And I'm starting here because we know that to really automate AP, accounts payable, to really drive cashless processing for accounts payable, we need to ensure that we're capturing accurate information upstream, that we're capturing the the accurate purchase details, the GL coding, any budget checks, we're getting that spend approved so that when an invoice comes in it simply matches up to that purchase order to any contracts. All the information has been approved upfront and that invoice can be auto approved or once again your team is simply managing the exceptions, that aren't matching that purchase order. Alright. So how can we start increasing spend audios, capturing accurate purchase information, coding finance detail upfront prior to the invoice being received? Let's start with making it super easy for the end users to submit their information. And and we do this by enabling Navi powered intake in Coupa. Right. So I'm logged in here as Rebecca, and Rebecca is an independent end user in Coupa. Right. She's certainly not a a purchaser or somebody who knows a lot about finance or GL coding. All she knows is that she needs to submit a new purchase request for some software. Alright. So she's gonna go ahead and tell Nav what she needs and in case she needs 50 Figma licenses. She's gonna start a a conversational chat with Navi who's asked her if she has any sort of a supplier contact and provide their information, if so. Navi's invalidating if that supplier and supplier contact exist in the supplier master. Master, it's also asking Rebecca if she can go ahead and attach or submit any supporting information. In this case, Rebecca has a draft contract or an SOW that she can easily upload into the chat. Navi's gone ahead and reviewed that attachment, extracted the key details, validated the policies specific to your organization, and has automatically created an intake request on Rebecca's behalf. Now, intake, one of the the benefits of intake is that we're able to simply use a conversational interface or clearly guided, guided intake process to capture relevant information from the user. And then based on your policies, our intake solution or Navi is gonna kick off the relevant processes, often parallel processes from there. We can see the actual purchase request details. We've got all the the software information, the commodity details, the quantity, the price, and we're automating or or AI is automating the GL coding, the budget checks, and the reviews based on this information. We can also see that the supplier was not yet an onboarded supplier. So So Navi's gone ahead and kicked off the supplier onboarding process with the relevant supplier onboarding teams. And we can also see that a contract is needed to get in place. We need a new contract. So Navi's gone ahead and in parallel kicked off the contract review and authoring project process with the legal teams. Right? All of these processes have been kicked off without Rebecca knowing what the policy is. Again, all she knows is that she needs to purchase new software. Alright. So that is guided intake, which again streamlines that invoice process as we're capturing all the accurate information upfront. The invoice comes in. It's matched against the purchase request, against the contract, and is auto approved. But how can we start to guide more of a proactive supplier management and supplier onboarding process for finance teams, maybe when we're not capturing an intake request like this? Alright. So now pivoting into how we can streamline the supplier onboarding process, whether or not, you know, it's coming from a a guided take request or your finance teams are just proactively managing that supplier's information. Alright. So we can see we've received a notification in Coupa logged in here as a supplier master that a supplier's risk, profile has changed for a key supplier. Right? That notification is taking us into your supplier three sixty where you're able to manage the all of your your onboarded suppliers. You've got visibility into things like your top suppliers by spend, suppliers by risks, as well as any key alerts that Navi's AI has alerted your teams to. In this case, there's been a tariff increase detected on one of our key manufacturing suppliers in China. Navi is now prompting the supplier management team to consider alternative suppliers using community intelligence and are over a million plus community suppliers in Coupa. Navi is just asking a couple of quick follow-up questions of your team. What is the subcategory most impacted by the supplier? And do we have any preferred geographic regions for potentially, alternative suppliers? We'll indicate Taiwan and Canada Canada here. We're also gonna let Navi know that we have some specific requirements, certification or compliance requirements around ISO 1,900. Navi's then taking those requirements as well as reviewing the community intelligence, our our community of suppliers that have been pre vetted with other Coupa customers. And it's gonna recommend, in this case, three relevant suppliers that we may be able to move the supply to. The first is an internal supplier, so supplier we already have onboarded in our organization. And when we drill into that onboarded supplier, we now have an updated supplier three sixty, a very clear view where we can proactively manage the supplier relationship. We have visibility into actionable to do's for this supplier so notifications for things like the supplier's certificate is expiring or their w nine's expiring. Maybe they have a contract coming up for expiration that we can start to action here. Or in this case, maybe supplier risk has changed. We can also see any processes or workflows that were currently, in process with this particular supplier. So in this case, supplier has recently sent in their tax information, which is now pending approval. They also have a business profile submission and CSP pending approval. Right. So giving you a clear real time look at your holistic relationship with this particular supplier. And maybe with this clear view, we we actually wanna go ahead and onboard a new supplier. Right? So we're gonna go ahead and ask Navi to onboard Northstar component, one of our community suppliers here. Navi's supplier onboarding agent is going to take that supplier profile, fill out any relevant information that Navi has access to, and then submit that onboarding request into the workflow. Once this workflow is approved, suppliers are gonna be notified to then go ahead and provide their information and we can even further automate this process asking Navi to maybe invite that supplier to an RFx event and even have Navi create that RFx event on behalf of the supplier. Alright. So supplier is now going through the onboarding process. How do we start to digitize the end to end supplier relationships and actually apply some of this AI automation to the supplier side as well? Right. So moving into the supplier side, we're looking at the Coupa supplier portal, whereas of r 44, our January release, we're now enabling Navi to be available to all of your suppliers in the Coupa supplier portal. Alright? So right in the Coupa supplier portal, now suppliers have access to Navi. Right? They can easily ask Navi any questions they have about leveraging Coupa, about onboarding, about updating their information. In this case, how do I set up payments in Coupa? And they'll get real time answers. How do I create an invoice? Right? Essentially, your suppliers can start to use Navi in lieu of picking up the phone and calling your teams, calling AP. And, of course, in this Coupa supplier portal, they get access and visibility into all their invoices, all their payments, all their purchase orders. Right? So really eliminating the back and forth, and the manual phone calls that often APN and finance teams are fielding. Alright. I know I'm coming up on time, so I'll quickly close this out with one of our most exciting advancements, in AgenTic AI. So we saw a lot of examples of Navi agents today. Again, Navi is an ecosystem of agents, and we we really barely scratched the surface. And to Liz's, earlier mention, right, Koopa is continuing to innovate with AgenTic AI. We have over, 11 agents being released in our January release of loan, so r 44. And as part of r 44 early access, we're starting to get, access into what we call our agent studio. Right. So this is essentially a workforce of agents or the ability to manage your workforce of agents. You can think of it like a control tower for all of the Navi agents that are live. You can easily turn those agents on, turn them off. You can also bring in partner built, marketplace partner built agents. You can bring in your own built agents. And you can even create your own agents using drag and drop no code configuration directly in agent studio. Right? So we'll close out with a a custom agent example. Let's assume for my organization, I need a custom Navi agent that's gonna help validate my supplier's information during supplier onboarding. So I've gone ahead and told Navi what this agent's going to do. And now in the creation of this agent, go ahead and add any knowledge specific to this agent from my organization. So maybe I have some specific direct materials policies that I'm gonna upload into Navi that Navi is gonna ultimately validate during the onboarding process. Navi is even suggesting potential tools or steps, skills, or or even actions that this agent should take based on the description and the documents you've uploaded. I'm gonna go ahead and add all the tools, making sure that this agent can check document requirements, validate document completeness, flag any missing documents. I'm gonna have this agent run on a daily basis. And then Navi's gonna make sure that we test this agent before it goes live. So it's asking me to provide an example supplier. It's gone ahead and ran a test to identify required documents and it's found that the test is noncompliant, but ultimately found that this agent is now working as expected. So I'm gonna go ahead and save this custom created agent specific to my business. And now we'll see a few days later has passed. You're continuing to onboard suppliers. And now we can see during the onboarding step that real time AI compliance validation agent and the outcomes of compliant or noncompliant being ran at the time of onboarding. Okay. So this is, again, one of of several examples of ways that we can start to use agent studio that, again, is going to be available in early access in our January release, really acting as your your control center for all of your Navi agents, your your custom built agents, as well as those partner built agents. And like I mentioned, this is really only scratching the surface with AI at Ooma. So I'll turn it back over to Liz to close us out and and talk about, you know, where we're headed next. Thank you, everyone. Great. Thank you so much, Elsa. I will go ahead and, Elsa, I'm so sorry. Can you share or unshare your screen, please? That's okay. There we. What Everyone can you know we're live, people. Figure yeah. Yeah. Okay. Great. So I'm gonna wrap this up really quickly because I know we're almost at time. But where I wanted to start is just calling out that there are a lot of benefits, for the folks who are able to join us on this call today. So we're gonna have a poll shortly. But if you select, the option on the poll, that we're about to put up, one lucky customer will be selected for a real AI digital workshop, where we'll work with you to clearly measure where you stand today and benchmark your KPIs against best in class standards to get actionable insights, recommendations, and really a data driven plan, to be able to turn AI potential into measurable business outcomes. And I think given what we learned in the beginning that a lot of the folks on the phone are kind of at the beginning or early stages of their AI transformation, there's a lot of value here. So I just want you to, we're gonna put a poll up now, and I would like you to complete it, please, but also, you know, make sure you pick that last option, if you are interested in this workshop. So, let us know if you'd like us to contact you for a one on one demo, if you'd like to be entered to win that complimentary AI workshop. And, also, if you're interested in having the recording and any supplemental academy materials sent to you and your team afterwards, please go ahead and and let us know in the poll. Okay. So, unsurprisingly, the complimentary AI workshop, is is quite popular and also thrilled that folks are wanting us to have this recording and also some more materials. Okay. Excellent. Okay. So I also we're gonna share here. If you do want to, receive the or if you're a Coupa customer and you wanna be entered into the workshop, please also scan this QR code as well, and there's some additional information that we'll capture from you. So, very quickly, I mentioned in the beginning of the call that this is the first live audience to hear about our new AI impact report, so wanted to give you all an opportunity to download that, one last time before we wrap up. And so, you know, we'll go ahead and and and end here, but, you know, the world that you're in as a finance professional is challenging at this point in time, but there's also so much opportunity, and AI is that catalyst that will enable success. So I'd like to offer some guidance based on what we hear from customers. So, you know, be clear on what is needed to be successful in the short term. You know, be realistic. You know, take a, you know, crawl, walk, run approach to it, but, you know, be very clear right about what you're trying to accomplish. Innovation, data, and people are the critical levers to long term success. And community engagement and collective learning, you know, very similar to what we're doing on this call today, will really enable you to evolve your AI maturity at speed. So that brings us to the end. I'd like to invite Jacqueline and Elsa to join me up on stage, to, close us out. And thank you all again for being a fantastic audience. Lots of great questions that I see in the chat, so we'll get through those, and we'll follow-up with you if we don't. But thank you again so much for joining us today, and thank you, Jacqueline and Elsa, for rounding out our panel. Thank you, everyone. Appreciate the time. Thanks, everyone. Enjoy the rest of the the Monday.