Name: AI for Office of the CFO
Uploaded: 2026-01-15T19:16:06.325Z
Duration: 55 min 44 s
Description: AI for Office of the CFO

Transcript for "AI for Office of the CFO": Alright. Hello and welcome to everyone. Appreciate you joining us today for Workday Live. We're gonna get rolling. This is all about artificial intelligence for the office of CFO and how you're able to use it to create more strategic impact and at the same time minimize risk. As we go through the presentation today, we will have a good amount of what's currently in the product, as well as what we'll be delivering in the future, in the near term. And so with that in mind, please do make any decisions on what you're buying from Workday based on what's available in the current product and services. We're recording today, so just know that it will be available to you after the webinar if you need to drop off early or wanna share it with a friend. You'll use the same link that you used to register and to join to access the webinar after the recording. This is live. We're here for you live, so please do ask questions. We have both myself and Ethan as a presenter as well as Chris on for moderating and chat. So take advantage of the opportunity to ask a question. You won't be able to come off mute. If there's time at the end, we'll answer some questions live, but we'll be doing it via chat as well. And please do know that your lines are all muted, but there's a a button that will unmute or mute your audio. So if you aren't hearing me, you probably aren't hearing what I'm saying. But just know at any point, if you click that button and you suddenly can't hear us, that's why. So hopefully, for any of you that have joined and can't hear me right now, you're clicking that unmute button. I am fortunate to be joined by two of our solution consultant experts. I'll just give myself a little intro here. I'm Brandon Smith Daigle. I'm an enterprise architect with Workday. I've been with the organization for ten years, but I've been in the finance and HCM space as a product leader, as a strategist, and as a presales architect, for almost two decades now. So I've seen a lot of different technologies and a lot of different innovations come along over that time. And certainly, we're at a point where that's that's no more new than artificial intelligence and machine learning. So really glad to be with you today and glad that you're here. And with that, I'll turn it over to Ethan to interview FinCEP. Thanks, Brandon. So hey, everybody. I'm Ethan Gelfand. I'm a solutions consultant here at Workday, and I'm a licensed California CPA. Prior to this, I was also at Workday being do doing revenue accounting. So I have lived two lives at Workday. First, as a revenue accountant, second, as a financial solutions consultant. I have used the system. I like to bring those different stories of how we use Workday internally so that way customers can understand the product from a more practical standpoint. Prior to this, I was an auditor at Ernst and Young, and I was a general ledger account at a private company before that. I'm also gonna be joined here by Chris. Chris will not be coming off of mute or camera, but he will be monitoring the chat. So please, as you have questions, just go ahead and ask Chris and be able to answer. He'll answer any questions you have. And I see a chat question saying if they can hear me. Brandon, are you able to hear me? Yes. I can hear you. So we'll. just need to put in that they'll need to unmute themselves. Yeah. Tricky tricky little thing there. Or not unmute themselves, but activate their speaker. So yeah. Definitely. Good. Awesome. Well, yeah. We're very fortunate to have both Chris and Ethan with us, practitioners and and really people that have lived what many of you are doing from day to day. And so that's that's such an important part at Workday is to make certain all of us are very keenly aware and empathetic of of how you all operate so that we design the right product as well as continue to to work with all of you with with expertise like like the two of them have. So today, we've got a packed agenda. We're gonna talk, about why Illuminate, Workday's umbrella portfolio for, artificial intelligence matters for finance teams, both accounting and, FP and A. And then we'll see AI in action with Illuminate. So that's what Ethan will show you. So very, eager to see that. And then I'll talk about trust transparency and how you can activate and enable AI features in your environments confidently knowing you still have control and and security always as a core part of how we approach it. And then we'll talk about how you're able to extend Workday to incorporate your own AI features and and then we'll wrap up. I think we all, over the years, experienced that there are more and more places to get work done, more tools to be able to make that happen. And that at the end of the day, what we're all trying to do is just operate more efficiently to make certain that we find ways to optimize labor, deployment of your capital, as well as technology. But that's an increasing amount of complexity to balance and to ensure you're prioritizing the right things. And also for your stakeholders, ensuring that they have decision information in their fingertips at the right time with the right context quickly. And really what that means is a lot of places to get work done. And for accounting and FP and A more than anyone and some of your line of business leadership and specialists, it means searching for information and spending a lot of time every day doing that. And that context switching, doesn't just cost the global economy, but I think the local economy of your organizations. And so, of course, what would we all prefer to be doing? You know, finding information or taking decisions on that information? And so that's really what we at Workday are crafting our technology to enable you to do, which is allow humans to spend more time on what they can do very uniquely, which is leadership, strategic thinking, engaging and aligning across the organization, and doing that with a copilot, not to load that term, but where you've got intelligent solutions that can help mine data, that can surface risks, that can identify anomalies, and really help you to take those tasks more efficiently. Also, your humans can save seconds, minutes, hours of their day so that they can reallocate that to more strategic work. And nowhere is that more important than the tools that you have at hand. And so, of course, for those of you that are Workday customers, you know, hey, you've been able to automate integrations with our embedded integration capability. You're able to enable more efficient reporting and, controls over your systems. But now as you think about AI, a challenge that comes on to adopting that is that if you're thinking about, well, should I do things within Workday or, you know, some other disconnected system? What we find is that without the context of the transaction, the business process, and who that user is, AI is really just guessing at what your people need. And so your people will continue to struggle with finding answers. And so all to say what this means to you is as you're at that inflection point of should we jump a bunch of data into some other solution and have it craft answers for us? What we're finding is that that context is so essential and not having to send users to different panes of glass. And so that's really the spirit of how we're incorporating intelligence into the Workday platform. Now most of you are probably an existing Workday customer. For those of you that might not be, and this is a new introduction to you, know, of course, we have our human capital management capability. We have our financial management capability. But importantly, all of that is sitting on top of our differentiated core technology where security, business processes, data model integrations are all tightly interwoven into the platform. And now the same holds true for our Illuminate AI capabilities. Now importantly, I want all of you to take away that Illuminate isn't a product unto itself, but really an umbrella of capabilities within our portfolio. And so across our ERP suite, which has planning, analytics, industry verticalization, spend management, contract management, and core financials, know that the intelligence we're incorporating into that is tightly interwoven to all of the different transactions, your security, the configurable business processes that are available to you. And we're really focused on people and money alone. And why that matters to you is unlike some other vendors and solutions that are just as much prioritizing how well search will operate when somebody asks for a pizza recipe as they are for how to analyze the variance in a forecast. Just know that we're laser focused on those contextual use cases that take your high quality data that you have entrusted within the Workday ecosystem, and we're embedding that intelligence in the experience. All unified with the security and business processes that you configure within Workday so that it all operates and works together in a way that you can trust. And importantly, we continue to rethink our overarching development to say how could we accelerate and improve the experiences. We have over 85 delivered capabilities today within our core financials, our HCM, our spend management, and those illuminate capabilities continue to to grow over time. Now why now? Many of your teams have already been dabbling with AI and ML or you've got data scientists on the team that have been using some algorithms and statistical analyses. So why is this the advantage for your organization and your CFO? Well, as many of you are probably already living, there are fewer and fewer CPA candidates. So you've gotta find ways to automate those tasks and also to improve the lives of your existing accountants so that they feel like they're having a more strategic role and not so much grunt work. And as those individuals near retirement age, you wanna make certain that the new individuals coming into your organization that are accountants or FP and A analysts do less data wrangling and more thinking. And then finally, more and more financial transactions start with documents and ones that can be consumed and digested and automated. And so really whether it's productivity or audit and compliance or insight to action, AI is a way to automate and elevate how your organization can deliver results to your stakeholders. And with that, I'm gonna turn it over to Ethan. Thank you, Brandon. And I'll go ahead and start sharing here. from my side. Alright. Perfect. So, we're commonly seeing these three themes here as the most common for customers to be adopting AI. First is productivity. AI is going to augment your workforce to work and perform efficiently and then as well increase that output. Secondly would be risk. If you have thousands, millions, or billions of transactions, there's just no way people are going to be able to review all that data. So on the other hand, AI, it will be able to review all that data and then reduce your overall risk. Then lastly would be insight. AI can provide faster insights that may have not been initially identified without spending more time creating and manipulating reports versus in the future, you'll be able to just ask AI questions and then be able to understand your data better from just using natural language. So we're going to be showing a variety of different AI functionality in Workday today. The first half here of these first three items are functionality we deliver today. On the second half where we see those light bulbs, that's where we're gonna focus on upcoming agents that Workday will be releasing in the future. So to start, let's go ahead and go into Workday. We'll look at worksheets and our worksheets formula writer. So I'm in Workday now, and we're gonna notice that it's just our typical experience here. And what we also have as part of Workday would be our drive functionality, which allows us to use that for our sheets functionality. So what's helpful here is that you'll be able to go ahead and use that functionality to go and learn about your data using the functions of spreadsheets. So just give me a sec here, folks. Looks like I got logged out. Brandon was doing such a great job speaking to us about our capabilities that Workday fell asleep on me here and logged me out for security purposes. So now that I'm back into Workday here, we can now go into that drive and be able to go and take a look at some of our spreadsheets here that we can create directly in Workday. So the advantage of doing this in Workday is that we're going to be able to keep all of our data in one place. We don't want data extracted into different systems, different spreadsheets. We wanna make sure that experience for the user is seamless. So we have worksheets which can directly take the data from Workday and be able to have it where you can manipulate the data as you need to. Now we have security here, so you can share it with who you need to so only specific users have access to it. So, again, it's part of that security model in Workday ensuring that only the right people see the data versus if I, again, extract it to other systems. Possibly, it's gonna be viewed by others, and it provides risks that we don't necessarily want to face. We can also utilize comments here. If I had wanted to leave comments as part of overall review, thinking about SOX compliance where we need evidence of review, we can leave comments directly in here. And then the advantage again of keeping it in Workday, I can add live data. So as live data is coming in, I don't need to go ahead and extract that data again, do the same pivots over and over. I can just add live data, and I can even see when the last refresh was performed. So I know that I'm using the data that I would expect to as I'm looking at this. And, again, it's gonna function just like any other spreadsheet here. I'll be able to create pivots and be able to manipulate my data as I need to. But, also, let's say as I was analyzing this data here, I wanted to understand the, expense reports for that are over, let's say, 500. And then I wanted to have Vegas in the memo. You know, instead of having to figure out how can I manipulate the data to extract that information, I can just utilize AI built directly in our worksheets, which can then go ahead and describe to me exactly what formula I can utilize to go ahead and get that data and an explanation as well in natural language? So not only do I have the formula to add in to look into that data very quickly, get my insights faster. I'm also able to understand how it's doing it. So that way, again, just makes my experience a lot easier to get the data I need to as I'm looking at this. So this is just a simple example. We'd like to start simple with AI before we get to more complicated complicated use cases on how we can go ahead and make your day to day easier. So here we have our our for our worksheets functionality. Again, the advantage of having this is that your data remains in the ERP for security purposes and ease of updating live data, and then we have AI functionality such as formula builder to ensure a continuous experience and efficient report creating process. Now we also provide AI functionality to automate the cache application process here. So what we're gonna do is go back into Workday and be able to look at this from our accounts receivable and be able to determine how our accounts receivable can be streamlined as well with our AI built natively in the system. So with our cash application process, we think about our day to day. Right? So we have invoices we send out to customers. We eventually get payments that we integrate from our banks into Workday. We, when that in the old fashioned old days, have to have users go in and match those payments to those invoices one by one, taking a lot of time. With AI, what we've done here with Workday is that it will be able to look at the payments that have come in, look at the customers that have outstanding invoices, and provide me recommended invoices to match those payments. So instead of a user having to look at every single payment, look at all the details, look at the invoice, and match those details together, Workday has AI built in to go ahead and determine the patterns that are there for your different invoices and payments that could potentially match and give me suggestions. Now there's machine learning built into this. I have the opportunity to say something is incorrect and dismiss it, and those models will update continuously based on the feedback I give it. So I can say, hey. That's not correct. This payment should not match to these invoices. I can dismiss it, or I can myself just review it and then determine as part of my review it's correct. So here, we'll be able to determine that we have a payment that came in for 78 k, and it's already started to apply all of this for me so that all I need to do is just quickly hit submit rather than in the old days spend a lot of time trying to go and review each payment, review each invoice. AI has already made that match for me. A human stays in the loop, so we ensure that our risk is still something we're comfortable with, and all a human has to do is submit it or say it's not correct. And those models will learn over time based on the feedback it continuously gets from our review here. Now I wanted to just quickly recap here on that customer payment matching. You'll save time. You'll increase accuracy by having AI automatically provide suggestions to match payments to your invoices. And we're often seeing customers automate nearly 70% of their cash application process using our AI functionality here. Now for the last current functionality that we deliver today that's generally available to our customers, we also have that we're gonna talk about at least today is also our contract intelligence. So with contract intelligence, what it does is that we have contracts that aren't just documents. There's data in it. So these contracts have data that can be utilized for decision making, being able to go ahead and optimize the, data that is there so that way we have better decision making by having this, with data. The challenge is that a lot of companies are struggling to access information in the data within these contracts. And so what we've done is that we brought in Workday contract intelligence where you can extract the data from those contracts with our purpose built AI. When I say purpose built, what that means is that it's not a general LLM. It's going to be an AI model that's going to be trained specific on legal documents. So that way, it increases the accuracy of the data extraction and the clauses that are identified. So it'll be able to review those contracts, determine the clauses, and then you'll be able to utilize AI to analyze that data. And so you can also ask questions in natural language or even research on it or report on it as well. So with that, let's move into our Workday product. We'll look at an uploaded scan contract, view that data extracted, and our Ask AI features. So we're now we're in Workday Contract Intelligence here. And in Workday Contract Intelligence, again, we have integrations that are prebuilt for Salesforce, Dropbox, Box, Google Drive, OneDrive, all of the variety of different contract places that we would expect our documents to be. We have prebuilt integrations so that those documents can come in automatically. Now you'll notice here with this agreement, it's not perfect. Right? There's not perfectly aligned. There's some creases. There's handwriting, but you'll notice here that our data was still able to be extracted. So for example, it'll be able to determine the counterparties involved even though it's not the most perfect, document that's been scanned. In addition as well, you'll notice as well, the effective date. It's handwritten. But even though it's handwritten, our AI was able to extract it so that way it's reviewable and reportable. So that way, again, I don't have the concern of anything being missed. And the reason our AI is able to do this, it's, again, purpose built. It's built specifically and trained on doc legal documents so it knows how to extract the key data in there. We also have it where it can determine the different, clauses in here. So I'm a former revenue accountant. When I had to review contracts for potential revenue accounting impacts, I would have to read each page one by one, taking a lot of time. In reality, I only cared about a few clauses. Let's say, for example, a force majeure clause was something I cared about, I can simply use our technology to go ahead and find that clause, and then it takes me directly to what I care about rather than me having to review it one by one. And you'll notice I said force majeure. There's no force majeure even written in here. So, again, that's the advantage of this being purpose built AI. It understands the intent of the of the term, And then based on that intent, it is able to classify it correctly as force majeure even though nothing in here is written saying that this is in fact force majeure. Now I don't have to just utilize the data extracted or the clauses here and scroll and find information. I can also ask AI questions to get information I need to. So let's say that I wanted to understand the volume rebate breakdown. The reason is is, let's say, that we started recently adding volume rebate clauses in our contracts, and we wanted to understand what potential rebate impacts we have in this exact document. I don't wanna necessarily go through our document and search for it myself. I can just utilize Ask AI, ask in plain language, and it's able to provide it for me directly here in the chat function to make it very easy and efficient. And as well to ensure that our risk is still something we're comfortable with, we'll have the sources of where it's pulling that data so I know exactly how it created its answer, and I don't have to worry about a potential hallucination and it being incorrect and allowing me to go directly to the source. Our Ask AI can not only look at things in this document, but if I had questions for all the documents in our repository, I can also ask questions around that as well. So utilizing Ask AI can go through, search through all our function all our contracts. I can also go into our dashboards and create different reporting. We have that claw contract. All those clauses were extracted. So if I wanted to go through our reporting and say, hey. I wanna look at all our services agreements. I wanna make sure it's agreements that are executed. I can just do quick filtering, and all of my different reporting is updated. And then if I wanted to, let's say, just add in a new, report in my dashboard, it's as easy as just saying, hey. I wanna track termination for conveniences, and then it gets added in here. And I can also say, wanna look at all of my contracts related to termination for conveniences and then see all the different agreements we have. Notice here that we have about 275 agreements with termination for conveniences, makes it a lot easier for me to review versus if I were to remove all of these different filtering, I would notice that now it goes to nearly 16,000. So if I was a revenue when I was a revenue accountant and I had to go and find, let's say, termination for convenience clauses, I had difficulty figuring out where to start, which contracts to look for. Using our Workday contract intelligence, you can find that a lot easier with all of this, with all the filtering that we can perform here. So utilizing integrations, you'll be able to have contracts that are uploaded and data extracted automatically to save time and ensure it's accurate. Then with that data extracted, we're able to review all of that in our reporting or utilize Ask AI to get us the key information and provide better decision making. So I went through that current AI functionality. This is just a few examples of what we have today. If you'd like to take a screenshot, please feel free to do so. We have a lot more AI functionality than what I just showed with you today. On the left, we have the CHRO functionality on this slide. On the right, our a our CFO. And in the middle, functionality that is working across the Workday platform for HR and finance. Again, I showed a couple features for CFO. I showed one that was crossed with our contract intelligence that can work for HR or finance. So, again, the advantage here with AI is Workday is providing you a lot more access to your data and also able to ensure that you have more capabilities, more functionality with your system to make your processes and day to day more efficient. Now that we've discussed some examples of our current functionality, we'll be moving into our future functionality as well. So we'll go ahead and talk about what agents that we're building, and we'll be releasing to our customers, to go ahead and ensure that we can provide, again, more streamlined processes. So for the first example, we're gonna focus on our revenue contract agent. So one quick slide before I dive into that revenue contract agent. What it's going to do is it's gonna take a look at those different contracts we have with customers, and it'll be able to extract the clauses and terms of those contracts, very similar to what we've seen already. So we've already built that functionality to extract clauses and terms in those deals. Then what this agent will do is it'll have a reasoning engine. That's what we're building here. This reasoning engine, based on its training, the training that you will do, will determine how to set up that contract and Workday based on those terms and conditions in the contract. So what billing schedules to make? What revenue schedules? Journal entries. When I was a revenue accountant, we had integrations which are rigid. Right? If you wanna make changes to those integrations, it is not necessarily easy. You have to build bring in consultants. Typically, then I would just say, let's just use the standard integration to bring that contract from Salesforce into Workday, and then I'll make manual adjustments in Workday based on terms conditions I have read. In the future, the Workday revenue contract agent will take those contracts, extract the terms and conditions, make the adjustments for you. It'll with based on that reasoning engine, based on its training, it'll make the changes for you, and then revenue accounts like myself would just review what changes occurred. So I can save time by instead of going into the system learning how to make those manual adjustments with this agent, I am now going into the system and I'm going to review the changes that have been made, and now I'm making this more I'm turned more into a high an an analyst rather than a per data preparer. So that way, I'm still being being a human in the loop, but I'm gonna be instead focused on high impact tasks like analysis, ensuring that our contract terms were appropriately captured in the system. So let's go ahead into Workday, and I'm gonna show you just a very simple example of our contract intelligence and how this agent can work, for us here. So we're now in the Workday, and we're gonna be able to go ahead into that contract intelligence, and we'll be able to say you wanna filter in for our specific customer that we were reviewing the, contracts for. So let's just say it's my, I woke up in the morning. I was reading one of the contracts that came in. And instead of me having to determine what actions to take in Workday, we have it where revenue contract agent is able to look at the agreement and able to add in the terms automatically like customer name into Workday itself and as well be able to take things like effective dating right here and be able to determine what the effective date of that contract is, all the different hot header information level here. So this is a simpler example. Right? We have it where it's just very simple terms in here. But we also are starting to see a little bit more functionality added where, like, we have a net 30 clause, and that's being added in and updated here. In the future, as we continue to build this agent, it's gonna be able to look at more sophisticated clauses such as termination for conveniences and determine what type of actions need to be taken as a result. So you may have to remove revenue from your backlog, for example, and that's something's account has to do manually. What this agent will do is it'll automatically know to do that based on its training. And then, again, as a user, I would go here and I would see that already performed for me. We like to start off with a simple example where you have the simple terms and conditions, but in the future, we're gonna make this agent more and more sophisticated sophisticated so so that way, you, the users, can just focus on analyzing here. So that was just a simple example of how revenue contract agent will be able to generate the agreement based on the document itself. It just ingested the document and then populated the contract data in Workday, then it would create billing and revenue schedules, journal entries, and all of this will lessen your risk on potential human error and less reliance on rigid integrations and then streamline that overall contract review. So next, now that your transactions are in, you need to begin getting insights from your reporting. Typically, means you have to create reports that you need and also manipulate it to find information. What we will be doing is releasing ask Workday where you can now use that to go ahead and learn more from your data rather than you having to create reports and manipulate it yourself. So let's take a look at an example of that ask Workday feature here. So we're going and taking a look at one of our, reports here. Right? We have it where we're seeing our different variances for our operating expenses, and we want to go ahead and understand our data a little bit better here. So this is where we can utilize features like our ask workday ask workday functionality here. And so what we can do is that let's just say that I'm an executive. You know, I don't have time to necessarily to understand all the ins and outs of this report. I just wanna know what's the quick summary of it. I can now use ask workday to get that information. I don't need to go to my analysts or managers, take their time to go ahead and learn from this. I am able to utilize AI where it can provide me a key executive summary where I can learn more about this data. So it'll tell me key points like the travel and entertainment, how that was against budget was a massive variance from what we expected here, and which we're even also able to verify that directly here in our reporting. So, again, I can feel comfortable that it's not hallucinating because I can even trace the data myself. And as I'm looking at this, and I would say this is pretty interesting, this is helpful, but I also wanna understand more than just the summary here. I may wanna get into the details. Let's say as I'm reviewing this, I'm looking at it and saying, okay. Travel and entertainment had a lot of different variances, but I also wanna understand what offices are driving this variance in office rent. So we have a 12% variance. It's not significant, so it's not caught in our executive summary, but that's something that I've been trying to track. I, as an executive, want to go ahead and lessen the amount of rent that we have on our different offices. I wanna go ahead and learn more about it. I can utilize Ask AI, and I'm able to see all the office rent broken down here where it'll say US was our main rent versus other offices where basically no barriers from the budget. So that's good. That's what we expect. We may even want to know and say, okay. With The United States, we're gonna go ahead and try to lessen the amount of rent by moving into different buildings. But the point is here, you don't need to learn how to drill into your data. You don't need to go to analysts and say, create me more rent related reporting. You can just use Ask AI and get that information right away rather than having to, again, wait for different reports, figure out all the drilling, figure out the UI. You can just use plain language to get the information from a reporting as you need it. So that is an example of how ask Workday is going to go ahead and change how you review reports. You'll be able to find information you need by using plain language, asking direct questions, and then just giving you another tool to analyze your data quickly and easily. Now for the last part of my demo here, we're, let's say, at the very end. Right? We've already we've done the revenue contract agent, brought in all our documents, created all the transactions. We asked Workday about questions and reporting. Now those auditors have come in. The auditors have come in and said, we wanna see some samples, and we wanna go ahead and have your users pull these samples for us, which can be time consuming. I used to do this as an auditor at Ernst and Young. I used to ask questions and say, I need certain samples. Then as a Workday revenue accountant, I also needed to go and get these samples for auditors, which took me away from strategic tasks. With Workday Financial Audit Agent, you're gonna lessen the burden on your accounting team by being able to bring those documents swiftly by just utilizing our agent here. So as an example of our agent, we're, let's say, now in our financial test suite. And, again, that request came in that we need to go ahead and bring in new samples as they need to. So let's just say that the questions I got was gonna be our AP cutoff. They had specific accounts payable supplier invoices that they were looking for. If you think about your process today, you have to go to your accountants and say, go ahead and find all the samples these auditors have asked for. What in the future will be is you'll use this AI agent to say, here are these different samples they selected. It'll automatically pull it. I can review it if I want to, be able to understand and make sure that this is what I expect. I would say, yep. That's good. Those are the invoices I expect. And, also, they'd say that there was also parameters requested for that reporting that they need to. I can say, yep. This is the correct parameters that the auditors need. And just with a couple clicks of a button, this agent has made that process from gathering all those samples, gathering all the different reports, and being able to do it all in one. And I got it here just within a couple clicks, giving it some context and information, and I've completed my review. And as well, we always want an audit trail of what we've performed, what the agent has done. That will also be tracked with our audit requests. I'm able to ensure that I can go back and say, hey. Here's the sub request I already completed. Here are the samples. This, again, just to ensure that I'm able to always have an audit trail of everything I do with my agents. It's not something an agent does in the background, and then I have no idea if it ever did it or not. Or if, let's say, I quit and somebody else took over, they'll be able to just see that that what the agent did previously and then who reviewed that. So with our financial audit agent, we're gonna be able to save time, no longer have to go and pull those samples manually so your accounting teams can focus on more strategic tasks. So this goes back to that overall theme of our illuminate drive value drivers. We're seeing customers adopt AI in Workday for a variety of reasons, but these are the three most common. Productivity. AI is gonna augment your workforce to work and perform efficiently to increase output. Output. We saw examples of that with our formula writer and then more sophisticated examples with our agents. Then secondly, risk. If you have all of these transactions in the thousands, millions, billions, there's no way for a person to review all that data. AI, on the other hand, will be able to review all that data and reduce your risk. So think about that cash application insights, how it was able to review all the different payments, all the different invoices, and then suggest which ones to apply to to, each one for. And then lastly, insight. AI can provide faster insights that may have not been identified initially when you were reviewing a report. But as you saw with our ask Workday functionality, you're able to just ask in plain language questions about your reporting and get more information directly from that rather than, again, waiting and having to create different reports, manipulating the different data points here. So with that, I will be stepping aside here and letting Brandon take over to drive us home for the remainder of this presentation. Yeah. Thanks, Ethan. So so valuable to have someone that has been a practitioner to share that experience versus, I have never been an accountant and, couldn't couldn't speak to that, as well as you did. So thank you for that. Great. Alright. Well, we will cover the last few things here starting with how you can adopt with confidence. So I've been watching the chat, answering some of the questions. Hopefully, I'll also answer many of them verbally as well. But the first part is is really about how do you know how all of these features operate? How can you understand how they've been, trained? What kind of models they use if they use models? And how you can activate them, understand, and have transparency around their operation. And so that really starts with our approach to responsible AI. We are the data processors. You are the data controller. And as a result, what that means is we're putting in place all of the tools, technology, and processes to make certain our software is configurable by you, transparent, and secure so that you all can be confident using these capabilities in the same way you might, use a feature that has no intelligence embedded at all. So just know that within Workday, our what I would call, AI secure software development life cycle now is really anchored around a set of principles where humans are always in the loop on decisions within your software and your transactions. We have put in place different risk assessment frameworks on even new features that we are considering to decide where does it fit within that risk assessment and and how might we proceed. Sometimes we might say let's not develop that feature just because we're not certain that we want to proceed with it. And then other kinds, we we understand, hey, very low risk. It's not really in the the the part of a transaction that is critical in a way that our customers will be concerned. We consult with many of our customers, our internal counsel, and we have policies in place to make certain that we are governing our development life cycle, our design, our rollout, our architecture. And what that means to you is that you can look at these features, decide what you wanna adopt, you have transparency into how they operate, and you can know that we have ISO 42,001 security sorry, certification. We're aligning the NIST standards to EU standards. That QR code at the bottom right will take you to a collection of resources because we know that it's not just you in a vacuum. You typically will have a governance council or teams that need to evaluate these features and understand how they function. And so one of those key steps is being able to share that resource with them. Put a lot of information into our SOC two type two reports that we release annually. And in addition to that, on Workday Community, every one of the features you saw and forthcoming features will have a fact sheet. Now some other vendors will call it a model card. We call them fact sheets, but what this will provide to you is a detailed overview of what the value of the feature is, how does it function. And when I say that, I mean, what are the inputs to it? What are those, potentially de identified data elements to train the model if it needs to be trained? So importantly, just like every tool in your tool chest is for different tasks, know that we don't have one model to rule them all. So in some cases like journal insights, that's something that is a private model to each of your organizations trained and tuned on your data alone. There'll be some other use cases where we say, well, we can use a publicly trained large language model to provide a response back. We don't need to train on your data. We don't even potentially need to send you any data other than the question the user asked. So just know each of these operate slightly different. And so this fact sheet is your go to place. As you saw what Ethan demonstrated and you might say, hey. I'm really interested in that, worksheets functionality. This is the place to go. Go to the fact sheets. You'll find information and links to how do I set it up as well. So just know we're providing that transparency inclusive of things like if it needs bias evaluation, how do we approach that to mitigate bias? If it's learning from anything like your user does, how is it learning from that? And so just know that's your resource. There were questions about history and training. And so, for example, journal insight needs about twelve months of of history. So you would start to understand, okay, this is how it's getting that data, how often is it using that data to learn from. And other things may need no history whatsoever and like I said, not necessarily training at all on your data and not needing to. So each tool and each use case will be a little bit different. Same holds true for some of those questions about the adaptive and ask workday capabilities. So I'll talk about road map and I'll also talk a little bit about the commercial aspect of these things. Some of those questions that came up were things like, well, is this in my product today? Importantly, no, for all of our customers, you either need to be, have signed the innovation services agreement or beyond the universal master services agreement. That's how you get that first step into being able to enable, these capabilities. But beyond that, just know some of them are separate subscriptions. So what, Ethan was showing with contract intelligence as an example, that would, be our contract intelligence subscription. Whereas the, capability he showed in worksheets, that's something that's available to all Financials customers. So all of that information is available on community and other resources as well, but, just want that to be clear. So where are we headed? Pardon me. Let me get my slide. So you saw some of the experiences that Ethan was showing and in particular about, say, ask Workday in Workday adaptive planning. And so we see a future where, accountants and FP and A teams, line of business leaders don't just ask a question and get a single response, but that these agents in the background are able to also anticipate and communicate with each other to surface even more information. So, just know that that's really where we're headed from a design paradigm so that someone might ask a question about a variance, but also start to get even more information, say, about the contract itself that seems to be the underlying source of information. So, that smarter and intelligent workday for you all really means just streamlining flows, still someone in the decision flow, but reducing the time and the steps necessary to get information to take action. Now we have a variety of agents available today. So if you have friends on the HCM side, they may or may not know we have a recruiting agent, a talent mobility agent to help actually score candidates. Never move them forward. Never make a decision for someone. But imagine for your professional workforce where it's helpful to know, well, who's a candidate that's very, closely matched to someone we've hired already so that you could rank them a little higher in the process and reduce the amount of time to source individuals. And you saw from Ethan the contract intelligence agents and the contract negotiation agent. In addition to that, we have a variety of capabilities, some of which you saw from Ethan that are an early adopter. So big question that came along was when's ask workday going to be available? That will be in the spring release. That's our plan, safe harbor. So that would be our twenty six r one release. But the capabilities that surface within that, like the self-service agent or like the financial audit agent or the BP optimization agent, those may surface in different time frames. So we are intending for the planning agent, the ask workday that Ethan showed to be a part of that spring release, whereas our business process optimize agent will be in the fall release is where our plan is. So just know, keep an eye on community, on work day rising, on our dev con, on our announcements for when things enter into early adopter, and then finally into general availability. So you can see we've got a lot that we've delivered from a feature perspective, in our calendar '25. We've got a lot more coming in calendar 2026. And so just know those features typically are gonna be included in your subscription. As I said, you just need to have that universal master services agreement or UMSA or the ISA in place. Other capabilities of agents and skills may not only require the, those agreements to be in place, but also either a separate subscription to our contract intelligence or Eversort, functionality or what we're calling our flex credit model. And that's where you would have an entitlement of flex credits and then you would consume credits as you use these features. But I think what everybody hopefully takes away is that you're gonna be able to preview these in non production free of charge. So you do have to be on the universal master services agreement and the flex credits, but you'll be able to preview things like that financial audit agent in nonproduction. Make sure it's right for you, and then it's only when you're in production that you would consume flex credits. So, we are evolving our way of just giving customers the ability to preview things that prior to that, you might have had to subscribe to it. Now what about building your own agents? Of course, we, Workday, are focused on building capabilities and embedding those, but we know that you all are imaginative folks and your teams will have unique use cases and saying, hey. I I wanna put AI to work, but I'm gonna do it in my way. And so Workday build, another umbrella term, not a product unto itself, is a collection of capabilities to help you build both agents, extend applications, as well as, going forward, interconnecting with other data clouds more efficiently. And then our partner ecosystem where our partners are developing capabilities and then helping your developers be successful with a thriving community of individuals and events and, resources to be able to do that. But what does that look like in terms of building people and and money agents? Well, across our platform, we are investing in those Workday agents and intelligent features that you've saw from Ethan. In addition to that, we're providing tools in the next few months here to be able to build agents yourselves on the Workday platform. So think the Flowwise agent builder within Workday extend. So you'll be able to get hands on with that at DevCon in the spring if any of you attend that. We also have our Sona acquisition where Sona will incorporate agentic experiences and conversational in ways that you'll be able to interconnect your documents and workday and other solutions to be able to ask questions. And then finally, our partners are building agents on top of our technology solution so that you have a seamless experience and the ability to automate and save seconds, minutes, hours of the day as well by using those as well. And then finally, have customers that are actively building their own intelligent experiences on Anthropic or on Google Cloud, on Microsoft three sixty five Copilot. And so our agent gateway paired with our agent system of record will be the way for you to interconnect those agents and govern them and provide access to what you want to give them access to within your Workday ecosystem. And in addition to that, to be able to see which agents are interoperating with your Workday environment, analyzing the amount of activity and usage, and then, of course, as needed, handle that life cycle of perhaps retiring an agent or, shutting it off for a while. So, that's all coming in this, spring release, in fact, the agent system of record. The agent system of record will be a part of your financials and or HCM subscription. There's no charge for that. Same thing. You ought to be on the universal master services agreement or have signed the, innovation services agreement to get access to that. And last but not least, what's on the horizon? So you saw Ethan show some of that ask Workday capability within Workday adaptive planning. But even within Workday's core capability for reporting, you will have the ability to ask questions about your data and allow your users to do that as well and get that narrative response that's going to help analyze the data in a way that you know remains secure to what that user has access to, that it still has all that auditing and transparency and control that you come to expect from Workday, but in a way that gives your users faster access to information and certainly for those individuals that are a little bit less data savvy or less comfortable with information. And so that can be less time for your finance teams having to answer routine questions from leadership and know that it's still on top of your trusted Workday data. So with that, I just wanna leave you with, you know, over the last twenty years, we have been partnering and collaborating with you, our customers, to make certain that we're putting in place mechanisms, validations, capabilities so that you can all trust that your data is clean and that our embedded AI is going to surface the right type of relevant results so that your users are more efficient, effective, and your leaderships retain that high trust in the data and the results. And as your system of record for HR and finance, for your people and your money, we take that trust very, very seriously. And and so, again, the fact sheets, the, the trust center, all those places are in place so that as you have been piqued in interest in activating these capabilities that Ethan showed today, you know where to find information on those capabilities, share those with your security team, with your, governance counsel so that you can start moving forward with adopting them, so that your teams are more competitive, able to focus on strategic work. And, of course, beyond what we showed you today, if you wanna see more, we have videos here. You can use this QR code to access all of those prerecorded videos of the agents that Ethan showed, but even more than that on both the finance and the HR side. So hope you scan that and share that amongst your your teams. And just a reminder, this is recorded. The the recording is available with that same link that you used to access the webinar today. So if you missed anything or wanna go back, please please use that link. And with that, we wanna just thank you so much for the opportunity to share where we're headed with Workday Illuminate and all of our AI features. And I think we've had a really active chat, so appreciate that. And thank you Chris for popping up that link as well there. So with that, I think we will wrap up for today. Thanks so much. Thank you, everybody. Appreciate all of your time. Yeah. Thanks, Chris.