Name: Unlock the Potential of Agentic AI
Uploaded: 2025-02-19T03:16:13.079Z
Duration: 1 h 4 s
Description: Unlock the Potential of Agentic AI

Transcript for "Unlock the Potential of Agentic AI": Good morning. Good afternoon to all our viewers across Asia Pacific. My name is Sian Moorthy. I'm the chief technology officer for Asia Pacific at Workday, and I'd like to welcome all of you to today's amazing announcement. Our customers so far have enjoyed Workday's AI innovations in assisting and accelerating how they work and how they're rethinking their business processes. The fundamental shift that's happening is having software powered by complex AI models, which have the autonomy to assist, accelerate, and transform how tasks are done given an outcome or objective. A change from software as a service to service as software, if you will. The natural evolution of this is the rise of the digital employee role working alongside our full time and contingent workforce. This is a step change much like the Internet, the mobile phone, the cloud, and big data brought to us in the past. As Workday brings this digital workforce to life, we see agents being made available by our partners and other vendors in your portfolio. The need to manage them effectively becomes more and more important as the sprawl gets bigger and bigger. What are they authorized to do? What can they access? How and where are they deployed? Who is managing all of them? And do we have an audit trail? This is where we believe Workday is uniquely positioned as we already provide the single pane of observability and control for the people in our organization. So we're delighted to announce our agent system of record to bring this amazing experience and risk management to all the digital workers you will bring into your organization. Now I'm sure you have lots of questions around what this means for you and your organization. We'll be happy to answer these. Post your questions, and I'll be back to answer them. For now, to hear more about this, let's cross to David Summers, our chief product officer at Workday. This is an incredible time for Workday. We're talking about AI. This is the most consequential technology I've seen in my lifetime. We're on the cusp of something truly special in the world of AI. Hello, and welcome. I'm Buree Shafer, vice president of Connected Experiences at Workday. I'm excited to talk to you about what feels like one of the hottest topics in the world of work, Agentic AI. We'll be diving deep into what Agentic AI is, why it matters, and how Workday is leading the way in helping organizations harness its power. I'm joined today by my friend and Workday's vice president of experience platform, Katie Holden. Thank you, Bure. Agentic AI is all the rage right now, and for a good reason. For those who are new to the term, Agentic AI refers to a new class of AI that can enable users to interact with enterprise software in a much more natural and intuitive way. You can provide the AI with an outcome or a goal that it can then independently solve for. So it's not just about automating simple tasks anymore. These AI agents can understand complex requests, reason about the best approach, and even take action on your behalf. It is truly a game changer. Agent eight k I has the potential to revolutionize how we work, making us more productive, efficient, and ultimately, more fulfilled in our jobs. So recently, Workday unveiled our new Workday's agent system of record and our vision for how the workforce of the future will be managed in the world of agentic AI. We also showcase some of the incredible innovations we're working on, and we're giving you an all access pass to the highlights and key takeaways from our announcement right here. Let's hear our CEO, Carl Eschenbach, talk about the transformative power of AgenTic AI. Take a look. Please welcome Workday's chief executive officer, Carl Eschenbach. Good afternoon. Today's an exciting day for Workday. We're doing an exciting launch of both technology and products. As I look around the room, many of you have been in the industry for quite some time. And we've all experienced major tectonic shifts over the last twenty or thirty years. Whether it was cloud, whether it was mobile, whether it was big data. We don't even have social on here. We don't have distributed computing. And they all drove massive gains in productivity. But today, we're talking about something fundamentally different. We're talking about AI. And I would venture to say that AI has the potential to have more impact than all tectonic shifts of the past in aggregate. And there's three different ways we're applying AI when we think about illuminate. First, we're leveraging generative AI to help accelerate how people work, to work faster, to work smarter. We're leveraging co pilots to assist people in their daily tasks to make them more productive. And last, we talked about transform. How do we leverage AI to truly transform your business? And when we talked about it, we launched four different agents at rising. And those agents, some of them are in the market and are already having major impact. We're here today not to talk about the assist or accelerate, but really talk about how do we truly transform business through the power of AI. And we know it's all gonna be about agents. We're all excited about agents and the potential impact it can have in the enterprise. That being said, everyone's talking about a lot of agents. In fact, there's some people out there who are talking about we're gonna have thousands of agents coming into the enterprise. Not a agent, literally thousands. This is exciting because of the potential. At the same time, I said I would talk about risks. Who's onboarding these agents? Who's managing them? Who has governance, control, access rights over these agents? Today, what we're seeing, they're coming into all different organizations and all different functions. That's a risk. Many of you remember the old adage, shadow IT, and how we want to bring control back into the CIO's office to make sure we were protected in the enterprise. For me, I remember almost twenty five years ago a technology called virtual machines. Virtual machine machines were powerful. They could be spun up in literally seconds. And because of the power then, people started to use them very quickly, and you had VM sprawl. What we want to focus on today is how do we avoid agent sprawl. That's what we're talking about. The question is simple. Who will you trust to bring these agents into the enterprise? And we believe at Workday, we're well positioned to do that. Carl really set the stage for our announcement. It was also fantastic to hear from our cofounder and executive chair, Anil Bushiri, and his powerful insights on AI's potential. Let's take a look back at what he shared. Anil, welcome. I'm just gonna take you on the journey that, we went through in getting to, the announcements we're gonna make later today, and it's it's also part of a personal journey in terms of learning about AI, because it is very, very different than anything I've ever seen in my my career, going back to, I don't know, too many years. I won't talk about how many years. But let's so let's just dive into it. AI was not as easy to understand as every other computer science, technology I'd ever seen in my life. And so I really decided to learn from the masters, spent time with founders of the AI companies, including Dario at Anthropic and my friends at Google. And, it kind of opened up a, you know, a new lens into what's happening in the world. The number one thing, Carl talked about this, it's the most consequential technology I've seen in my lifetime. And the reason is, is because it's trying to mimic the human brain. It's trying to reason, it's trying to, use intuition to make decisions, and use pattern recognition, and that's not what any technology, we've experienced in our lives has ever done. We were all excited when, the GenAI technology showed up with OpenAI and Anthropic, but really it was about generating content. At Workday, we used it for things like generating job descriptions or filling out procurement forms, but those were not truly impactful for for the business. They were nice to have, but they really didn't change the way companies operate. And then along came the agentic model, where agents act independently, they achieve goals, they learn, they adapt, they make decisions. And to us, that felt like that that's very enterprise centric, and and it and it kind of relates well to what an employee does. I'm really excited about where this technology can lead us, and especially for all of our customers. So not to spend a lot of time in this, but but why do we think that we're, in the right place to be a leader in AI? We have the largest data set, in particular in HR, the single largest HR data set in the world. I think at this point, 70,000,000, employee records. And we've been working on AI for a decade. Started out with machine learning. We've been doing it. We've been learning how to use the data, and this is just the next evolution. The unique knowledge we have, if you think about agents and think about them as employees, and that was a big insight. If you're having an agent do work and it's tied to roles and skills, so you have a set of skills, and and we cap capture that with the skills cloud. A set of skills combines a role. A role is an employee, so at the end of the day, these agents are effectively digital employees. Well, a digital employee, like an employee, needs to have an identity. They need to know where they sit in the organization. We we are the only company that has the org model. Right? So you need to know what security privileges that agent has. You gotta onboard them, you gotta off board them. So the HR system ends up being the right platform to manage the agents. So not just the workday agents, but third party agents as well. And hope for the customers in in the audience, you trust us, and that's a really important part of doing this the right way. We're gonna continue to earn that trust and do it the right way, But we hope that with you, we can figure out ways to deploy these agents in a very safe and secure way. Anil really laid out the vision for how Agentic AI will reshape how we work. In this next clip, David Summers, Workday's chief product officer, introduces a groundbreaking new solution, Workday's agent system of record. It's a centralized system for managing an organization's entire fleet of AI agents. Let's watch that moment. We're on the cusp of something truly special in the world of AI, And that brings us to why we're all here today. And as Anil introduced the Workday agent system of record, this is a game changer. Imagine having a centralized command center for all of your AI agents. So why manage all of these agents in Workday? Well, when you look across the key capabilities that are needed for both employees and AI agents, the needs, they're surprisingly similar. You need capability around life cycle management, workforce optimization, governance, and compliance for those agents. And Workday is focused on keeping humans at the center of all of this. Always using AI once again to amplify their potential. This human to AI interaction is important now and it's imperative in the future. So let's take a minute. Let's dive into the three major components that make up what we call the digital workforce management. Within the agent ecosystem of itself, you will find those native agents that I just mentioned that are built by Workday. Also, we fully expect all of you, our amazing customers and partners, to build agents as well. We also have plans in the near future to allow you to take the agents that our product teams build and allow you to extend those agents yourself to meet your specific needs. And finally, we welcome third party partner agents into the mix, and into the ecosystem. And that's when the magic actually starts to happen. Your custom built agents, as customers, and those third party partner agents actually interacting with Workday native agents all inside of Workday. This seamless collaboration is powered by the second key component of our digital workforce strategy, something we call the agent gateway. That was phenomenal. I love how David highlighted the benefits of managing AI agents within Workday and the tools and the controls that the enterprise needs to navigate this exciting world of Agentic AI. Absolutely, Katie. Agent system of record provides that centralized control, streamlining agent onboarding, ensuring security and compliance, and giving organizations the visibility they need to manage access in this ever evolving landscape. It's all about striking that balance, empowering people with AI while also making sure it's done responsibly and ethically. This also opens up a whole world of possibilities for how businesses can leverage AI. But don't just take our word for it. Winston Weinberg, CEO and cofounder of Harvey, shared his insights on leveraging role based AI agents to boost productivity while ensuring ethical and compliant practices. One of the largest problems with enterprise adoption of AI agents is not actually going to be the reasoning ability or the capabilities of the agents, but actually making sure that they have the correct access to all of the applications, software, and permissions that we do as humans. So if you think about legal, say you're building an agent that will check all of the different compliance regulations in multiple countries against your employment contracts. You need to make sure that that agent not only has access to all of the regulations and all the statutes and the case law, etcetera, but also needs to have access to all of those employee contracts, and you don't want every single person in your business to have access to to everyone else's contracts. As these agentic systems get better over time, they're not just gonna have to access documents across different cross functional teams, but they're also gonna have to access a bunch of applications and have the correct controls to access those applications. And Workday is in the perfect position as the largest system of record to make sure that in a single centralized way, the agents are not accessing documents that the human using that agent wouldn't have access to in the first place. The main advantages of Workday's system of record is it allows folks that are creating agents to actually register them and make sure that all of the agents' actions are in compliance with the rest of your enterprise. If we get this right, role based agents can supercharge productivity. Workday is already the trusted system of record for over 60% of the Fortune 500. They're in the perfect position to manage your digital workforce going forward. It is so inspiring to see companies like Harvey innovating in this new era of agentic AI. And now to help us unpack all of this and dive deeper into Workday's vision, we're we're joined by a very special guest, our chief product officer, David Summers. David, welcome to the show. Thank you for having me, Burey and Katie. It's great to be here. So, David, we're really excited about Workday's announcement for our agent system of record. But we also announced four agents. And I'd love to hear a bit more about those before we get into it. Can you tell us about the agents? Sure. Before we jump into that, I wanna remind everybody as well, we now have a total of eight agents. We actually announced four role based agents at Rising, including our recruiting agent, and we've seen a ton of success with that particular agent. We have now 1,600 recruiters over 71 customers leveraging that live, and I think it's processed 700,000 job reqs reqs at this point. So pretty impressive stats for that particular agent. And, yeah, we announced four new agents. Our policy agent, our payroll agent, our contracts agent, and our financial auditing agent. You know, one of the ways to think about what's coming next, and we have a lot more coming down the line when it comes to agents, is if you think about where those roles in Workday and Workday is that system of work for those roles, that is where Workday is going to truly build our native opinionated agents. Oh, fantastic. I think that makes a lot of sense. We have so many people in Workday working day in, day out. And agents, just an enormous opportunity for us to deliver those best in class agents right there. Okay. So then to take us to agent system of record, with all these role based agents in the workforce, we know customers are gonna need that place to centrally manage them. Tell us a bit more about the agent system of record announcement. Yeah. And, I mean, you hit on something key there. You know, we see in the not too distant future where you're you know, all of our customers will have lots of agents, not just agents built by Workday. And like I mentioned, you know, we have a long list of role based agents we believe we have the right to build, but they'll have agents that they build as well, on third party systems. And then, of course, we have partner agents. And so there will be a proliferation of agents across, an organization, and you gotta have a place to manage all of those. So just like you do for your employees within Workday, where you're able to onboard them, bring them into the system, give them specific roles, control access, that is exactly what you're gonna need to do with your AI agents, and we believe Workday is best suited to help you do that. So, David, you mentioned bringing the same level of oversight and control to your digital workforce as you have for your human work force. Can you tell us more about that? Yeah. I mean, Workday provides that type of governance for an organization's employees today. A matter of fact, we do that for over I think it's 70,000,000 employees at some of the largest organizations in the world. You know, we just talked about the proliferation of AI agents within an organization. You're gonna want that same type of control with AI agents that you have with your workforce. And they're actually very similar at a high level. So things like life cycle management, think onboarding and offboarding, of employees and agents. You're gonna want to have workforce optimization. How are you best utilizing your people and your agents? And then finally, governance and compliance over those agents. Yeah. David, that is a great point. I mean, Workday is already the system of record for all of your employees, the roles. We already feed all the downstream systems for what they should have access to, whether that's data and applications. And IT CI leaders are absolutely going to need that same level of controls for the agent workforce, which uses broad goals and many different steps to accomplish something. So I think that really hits home. Let's talk a bit more about the ecosystem side now. Okay. So the system of record, will it be only for agents built by Workday? No. I mean, I I hit on this earlier. We see that, you know, proliferation of agents being a problem. You need to be able to manage all agents, whether it's native agents built by Workday, whether that's, once again, agents built by our customers. We plan on having the ability for those customers to even extend the agents that we've built. So taking those agents and actually adding new skills, to those agents that, our product teams build. And then finally, once again, third party partner agents will be managed within the system of record as well. When you look at the digital workforce management ecosystem, it's really made up of three major components. There's the agent ecosystem itself, which we've talked a lot about here today. So Workday agents, customer built and extended agents, and then finally, our partner agents. Then there is another key component, which, Burey, you're very familiar with, is the agent gateway. And that's actually how third party agents will interact and communicate with Workday agents inside of Workday. And then finally, there's the agent system of record itself where you can register those agents and, like we talked about, manage all of those agents in one place. And, David, can you talk a little bit about the user experience side, the experience with Workday Assistant? How will that help employees interact with all of these different agents that they have access to? Yeah. Then that's a great question. And you hit on it. I mean, I think one of the big things that we're working on, and I think it's super exciting, is leveraging a known capability in Workday, Workday Assistant, and really taking that to the next level. And the idea there is to not make it confusing for the end user when they're in Workday. So they can go, say, to any place within Workday, ask a question within Workday assistant itself, and get an answer. Even if that answer requires multiple agents on the back end, right, providing those answers, What the user doesn't see is all the complex orchestration underneath the hood that happens to get the right answer to them, and that's exactly what we want. And how do partners fit into all of this? Yeah. This is really where the Workday marketplace comes in. We think it's gonna be a thriving ecosystem, not just for partner agents, but also even Workday agents where they can register, any and all agents that they have available. And our joint customers can go out, browse, understand what agents are available, and with one click, easily download that capability into Workday, and it's that easy. I love that. I think the idea of a marketplace discovering role based agents for every facet of your enterprise is just sorely needed in this very fast moving agentic landscape. David, thank you so much for sharing your insights with us. It is clear that Workday is at the forefront of what is coming with agentic AI. And to our viewers, we encourage you to learn more about our vision for AgenTic AI and Workday's agent system of record solution by visiting our website, workday.com/agenTicAI. Thanks for watching, everyone. We'll see you next time. Wow. What a game changing announcement there. And it's based on a very simple concept. Skills make up a role, and a role is filled by a digital agent. The digital agent is then able to add new skills as time goes on and has the autonomy to fill that role over time as well. At the end of the day, there's always humans at the center of this, and we can, start managing it using the the digital workforce management, pain, where you can look at life cycle management, workforce optimization, governance, and compliance, which is basically clear boundaries, rules, and responsibility frameworks just like we apply to our people. We're also able to deal with the the large number of agents that we foresee, being seen by enterprises, whether it's Workday agents that we provide, customer extended agents using XtendPro, third party agents, and that can come in two flavors, either the ones that are registered only or the ones that interface with Workday itself. So let's cross to some questions that you've put up in the chat, picking the first one. From Workday's perspective, does the rise of AI agents represent a fundamental shift in how enterprise software is designed? Well, as you might have heard from Anil, AI is not a new concept, and it's something that we've been working on for about ten years more than ten years. What has fundamentally changed is this difference between, and I would call this consumer grade AI versus enterprise grade AI. If you look at what's been in the market, we 70% of APAC businesses expect vendors to to have AI based capabilities. But so far, we've been playing around with generative AI. And and while there is some utility in the in the workplace for generative AI, the real ROI, the the value generation, the the benefits, are realized from moving to an agentic AI experience. And we're seeing a lot of reports and studies that come out with, saying that the businesses expect a doubling of productivity, by 2027 by employing agentic workflows, not just generative AI. Next question. Can you elaborate on the concept of role based agents and how they differ from task based agents? What are the key advantages of this approach? So a role based agent has some level of autonomy. It is given policies, laws, governance frameworks around it, but it's also given freedom to figure out what is the most optimal way of doing something. A task based, agent on the other hand is is very deterministic. So basically, if if action a happens and then action b happens, then action c should follow. Whereas a role based agent is given the skills and the context and memory and learning over time to adapt its approach, for to discover new and more optimal ways of doing it. Now that needs to be counterbalanced by very clear governance and and rules, to make sure that it works within the the the parameters that the the organizations expect. How does Workday's agent system of record ensure responsible and ethical use of AI agents within the workforce? So one of the things that you've seen is the the the digital workforce management, concept, and that's where we can then start applying those, responsible AI practices. We can monitor the agent performance. We can track costs. We can ensure that there's alignment to organizational values, ethical value, for example. We can make sure that there's move away. We can monitor the bias and so on and adjust them as time goes on. Just like we would give feedback to people, we should be able to recalibrate those agents as well. And next question, what is the alignment between Workday SKUs and access to Workday delivered agents? Is there a ready guide on what agents are available with specific SKUs? Now the SKUs is is something that we are still working on. The the the bit that you would have heard in in, the announcement there is that the the management. So the agent system of record is actually included as part of the work they're offering, but as time goes on so there's already eight agents that, that have been announced. One of them, you can already interact with in, in the recruiter agent. How are you differentiating between skills and tasks? Is the agentic AI completing tasks or demonstrating a skill? I would say an agentic AI is expected to gather skills over time, and and one of the concepts that we have is we'll be able to add more skills to that agent over time as well. As we add more skills, that agent is expected to be able to complete tasks in a more efficient way or more complete slightly different tasks, and perform in slightly different ways. When when are the first four agents, recruiting, succession, talent, mobility, and optimization agents being released? So the recruiting agent is, already in the hands of about 74 71 customers, and we're getting some really good feedback on that. And succession talent, mobility and optimization is going to be fast followers. We should expect that in the next half year. Is there going to be an AI agent inside Workday community or an AI agent to help troubleshoot issues and errors? An AI agent is for Workday administrators. Yes. That's a good one. So this is something, and, ironically, maybe something that should go into the Workday community as a as a, a request and that that our community can vote on. My we we still we have a backlog of agents that we're working through. As as you might have heard, there's the eight that we've, announced already. But as the community comes up with new and new ways of doing it, we can add that to the to the list too. To unlock the potential of agentic AI, will we need to utilize Workday Assistant, or can it be seen experienced as well in other areas of functionalities? So the the experience itself, so as you may have heard, David talk about, a lot of it is based on the assistant because it comes into that flow of work. The expectation is we we don't want our users to have to learn to interact with all the different let's say, for example, there's a thousand agents that your organizations have signed up to, we don't want a thousand different ways for you to have to learn to interact with those agents as well. So we want to streamline those experiences into a handful of ways. The one that is, the most intuitive is through the Workday Assistant. But you'll also see some of those, any features that are powered by Illuminate. So Illuminate features, you should be able to have some interaction with those agents or at least see the result of the agent acting on something. What checks are there on agents' quality of output? Now this is something, that is will be part of the the the management, pain, where you can see the performance, how they're performing, and what what the results are, whether they match up to the expectations of the organization, and so on. How does Workday's approach to AI agents leverage the company's existing strengths and data assets? Okay. So this is a good one. AI is is fundamentally a a difficult thing to do because it is reliant entirely on the quality of data that you have at hand. If you have poor quality data, it results in in hallucinations and and all sorts of strange outcomes. One of the key differentiators that Workday has as a platform is that we have a very strong and very structured data model, and we have 70,000,000 users on that on that one data model. Just remembering there's only one version of Workday that's used by 10,500 customers around the world. So that that data model then provides a very rich training ground for us to develop our AI models on as well. So when we when we have AI models that are that are trained on very strong data models, we then, have AI agents that leverage those models to deliver predictable and, quality outcomes. Whereas AI models that are trained on patchy data or there are bits of bits missing and so on, the results will be unpredictable. So in that sense, we actually have a very strong base to build our AI agents on. How would Workday agents be licensed, and what would drive the costs? Now this is something that is still to be, worked out, but as we as we mentioned, there is the the the registration of those agents and the management of the agent in Workday itself is is part of the product. But the agents themselves, we just need to we need to go allow time for those to be developed. Is the agentic AI model trained in other languages? Now we're starting out with Latin languages, so any anything that's based on the English language. And as time goes on, we will be adding more languages. We already have models in Workday which do which do operate in other languages, so it is only a matter of time when those AI agents are also able capable of leveraging those models as well. How does Workday's approach to AI agents leverage the company's existing strengths and data assets? So this is a is a fun one. If you can, I'd like you to picture a a wedding cake. You know, they usually have multiple tiers. So at the bottom, you have a large language model or a a a base tier. Now this can be something like translate a picture to a text or translate from one language to another. It's a very generic model that does a generic function. On top of that, there is another layer, which is the the the domain layer, and this could be something like take a resume and parse out the job history from that resume. It's very specific to to a task that's been done, and it's a skill set that's learned. Now on right at the top of that is the the the key layer, which is the customer data model. So that thing that layer basically influences things like tone of language, specific keywords that you might use, certain parameters that you prefer over others, and so on. So if you what we do is we layer those models one on top of the other. So we take a large language model, we then have a set of frameworks and standards around just that use case, which is the domain. And then lastly, it's personalized using the customer data. So we train that last model, the the last mile on customer data, which means that the experience that is delivered by that agent is uniquely trained to your data model. Is the agentic AI being compliant to Australia a voluntary AI safety standard or any global AI ethics policy? So this is actually a very quick question. So one of the one of the benefits of, Workday being a global organization and also Workday being one version that, is run across the entire world, we actually have to be compliant to all of the world's AI standards. So there are regulations that are coming out of the European Union. There's regulations that are being developed in in individual united, in individual states in The US, and there's regulations that we're working in Australia as well. Australia is actually quite proactive when it comes to, to, AI, policy, AI related policies, and it's something that we're actually working quite closely with the government, and and making sure that we are compliant with those policies. What timeline do you have on bringing on to bring non HCM tasks to Workday Assistant, such as procurement, project related tasks, and approvals. So there are those eight, Workday agents that we've we've discussed. Those are the priorities for this year, And as as we develop those, we will then release further timelines as well. Does Workday have a measurement or scorecard for the efficacy of the agents both pushed out by Workday and by third party providers? Now if it is based on a registration only, policy, then, the efficacy of those agents, may not be accessible. But if, definitely, if there is an integration into Workday, then that is something that we can do. The efficacy of our own AI agents, on the other hand, is something that is intrinsic to the, to the to the agent, and that is something that we will make available as part of that, the management, pane so that you can performance manage your agent at the end of the day. What are the key capabilities of ASR that enable organizations to effectively manage and deploy agents? So the biggest thing is we basically have realized that digital agents need the same structures around them as our own employees do. And while we have an organizational structure that supports, people, whether it's onboarding, offboarding, whether it's performance management, whether it's, feedback and so on, and and also we we provide them with governance and and, policies, we realize that it's the same things that need to apply to our agents as well. So the ASR then effectively allows you to observe and and apply all of those things to an AI agent. How does Workday envision the future of work with AI agents, and how will ASOR contribute to that vision? So this is an interesting one. When we surveyed our customers, they they predicted in by 2027 that there'll be a doubling of productivity by using in APAC. There'll be a doubling of productivity, by 2027 by using agentic experiences. So we, predict that, this agentic AI will become a fundamental part of everyday work. It will automate some of those mundane tasks, allowing people to focus on the the more creative work, for example, and, more things that require human touch. And I think this is a it's a it's a nexus moment or a game changing moment for us because we we we are staring down the precipice of having AI agents working alongside our people, augmenting how they work. And this is something that is only possible on a platform like Workday because it we bring together the people and the technology in this, working space. So with that, I'd like to thank you all for, joining us on this webinar. There's exciting times ahead. There's a lot of news coming, soon as well. And I'm sure you'll have a lot more questions. Please post them online, and and and we will get back to you as well. But thank you again for joining us, and, hope to see you soon. Thank you.