Video: Jo-Anne Ruhl Interview | Duration: 74s | Summary: Jo-Anne Ruhl, Managing Director and Vice President, Australia and New Zealand, discusses the most impactful insights from Workday Elevate Auckland 2026. Ready to talk? Get in touch.Talk to Sales | Chapters: AI and Trust (0s), Go Kiwi (37s) Video: Jonathan Brabant Interview | Duration: 142s | Summary: Jonathan Brabant, Senior Regional Sales Director - New Zealand, discusses the most impactful insights and his favourite takeaways from Workday Elevate Auckland 2026. Resources:Workday for New Zealand Ready to talk? Get in touch.Talk to Sales | Chapters: Introduction & Welcome (0s), Event Atmosphere (12s), Trust and Reliability (47s), AI Agent Builder (93s), Closing Remarks (133s) Video: Matt Lovell Interview - Workday GO Launch | Duration: 37s | Summary: Matt Lovell, Senior Regional Sales Director, discusses the launch of Workday GO at Elevate Sydney 2026. Resources:Workday GO Ready to talk? Get in touch.Talk to Sales | Chapters: Workday Go Launch (0s) Video: Voices of Elevate Sydney: Top Takeaways | Duration: 591s | Summary: Live from the ICC Sydney floor, Geena from Workday catches up with attendees at Workday Elevate Sydney to get their unfiltered first impressions. | Chapters: Welcome and Introductions (0s), Workday AI Implementation (111s), AI Journey Experiences (159s), Keynote Insights (253s), Event Reflections & Advice (302s), Event Reflections (460s) Video: Real Reactions: Inside Workday Elevate Sydney | Duration: 198s | Summary: What did attendees actually think of Workday Elevate Sydney? Karen from Workday listens to top takeaways and favorite moments directly from the crowd. | Chapters: Conference Introduction (0s), Nicks Introduction (48s), AI Recruitment Solutions (87s), Event Outlook (137s) Video: Voices of Elevate Auckland: Top Takeaways | Duration: 660s | Summary: Live from the NZ ICC floor, Geena from Workday catches up with attendees at Workday Elevate Auckland to get their unfiltered first impressions. | Chapters: Welcome to Workday Elevate (0s), Data Foundation Work (76s), Workday Implementation Experience (106s), AI Workforce Transformation (168s), AI Workforce Journey (264s), Trust and Innovation (339s), Planning Agent (461s), Conference Reflections (504s) Video: Opening Performance | Summary: Welcome to Country Performance at Workday Elevate Australia. Video: Workday Executive Keynote | Summary: Executive Keynote with Jo-Anne Ruhl, Managing Director and Vice President, Workday. Resources:Blog: Australia's AI Moment Won't WaitBlog: Leading With Clarity in a World That Won't Slow DownReport: Beyond Productivity: Measuring the Real Value of AI Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome to Elevate (12s), Navigating Complexity (111s), Trust and Values (247s), AI Friction Challenges (336s), Business Readiness Gaps (495s) Video: Workday Innovation Keynote | Duration: 2097s | Summary: Innovation Keynote with David Wachtel, GM - HCM, VNDLY and People Analytics, Workday. Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), The Agentic Shift (35s), AI Guardrails (96s), Workdays AI Advantage (175s), Lawless Agent Risks (225s), Lawful Agent Demo (333s), AI Superintelligence (405s), Meet Sana Interface (477s), Cross-System Integration (570s), Workflow Automation (640s), Workday Agents (829s), AI Learning Agents (943s), Self-Service Agent (1090s), Procurement Intelligence (1287s), Workday Build Platform (1621s), Agent Configuration (1742s), Cross-Platform Integration (1856s), Workday Go Solution (1917s), Closing Vision (2028s) Video: Telstra Customer Story | Summary: Customer Keynote with Niki Rose, Workforce Experience and Capability Executive, Telstra. Resources:Demo: AI-Powered ERP: The Workday Platform Ready to talk? Get in touch.Talk to Sales | Chapters: Working Parent Introduction (11s), AI and Workplace Challenges (102s), Connected by Design (184s), Paradox Implementation Strategy (272s), AI-Powered Learning (442s) Video: Westpac New Zealand Customer Story | Duration: 770s | Summary: Customer Story with Marc Figgins, Chief People Officer, Westpac New Zealand. Resources:Demo: Workday Human Capital Management Suite Software Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), Transformation Journey (71s), People Strategy Pillars (142s), Workday Journey Begins (234s), Implementation Strategy (325s), Workday Impact Results (441s), Future and Trust (623s), Partnership and Success (702s) Video: Assurity Consulting Customer Story | Duration: 988s | Summary: Customer Story with Garth Hamilton, Co-Founder & Managing Director, Assurity Consulting. Resources:Demo: Workday Human Capital Management Suite Software Ready to talk? Get in touch.Talk to Sales | Chapters: Introduction & Welcome (11s), AI-Driven Change (104s), Quality in AI (245s), AI and Human Partnership (331s), Expert-Driven AI (465s), Internal AI Enablement (618s), Why Workday (827s), Future and Closing (933s) Video: HR Strategy & Vision / Demo | Summary: This session unveils a vision for a New Work Day for HR—a fundamental shift from systems that simply track work to those that actively enable it through Agentic HR.Grounded in three core imperatives, this strategy demonstrates how Workday’s Enterprise AI platform reinvents core HR with trusted AI, delivers a new level of business value, and builds for the future through a unified, AI-driven architecture.By leveraging Workday’s unparalleled context—encompassing 75 million users and 20 years of experience—HR leaders can now deploy specialised agents across payroll, recruiting, and performance to eliminate "talent trapped in trivia" and allow their teams to lead with empathy and creativity. Resources: Demo: Workday Human Capital Management Suite Software Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), AIs Transformative Impact (73s), Customer AI Challenges (198s), AI in HR (319s), Agentic HR Foundation (422s), Contextual AI Agents (573s), Workdays AI Strategy (662s), Job Architecture Agent (827s), Job Architecture Agent (998s), Performance and Recruiting AI (1324s), Recruiting Agent Demo (1508s), Candidate Experience Results (1939s), Candidate Experience Agent (2029s), Always-On Candidate Experience (2113s), Automated Interview Scheduling (2189s), Strategic Impact (2285s), Frontline Worker Agents (2351s), Building for Tomorrow (2585s), Agent Ecosystem Investment (2689s), Implementation and Results (2784s) Video: HR Customer Deep Dive | Summary: Join Starlight Children’s Foundation’s Kelly McFadden (Head of People and Performance) and AGL’s Melissa Dorey (Head of People Digital Experience) as they share their Workday journey with Matt Lovell, Workday’s Medium Enterprise Sales Director. Resources:Blog: How Mastercard Builds a Culture of Belonging in an AI-Powered WorkforceDemo: Workday Human Capital Management Suite Software Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introductions (11s), Career Development Challenges (73s), System Consolidation Challenge (169s), Career Hub Adoption (380s), Platform Integration Benefits (593s), Progress Over Perfection (691s), AI Readiness Foundations (773s), Implementation Lessons Learned (905s) Video: Deloitte Partner Lens: What We Can Learn from Healthcare about AI | Duration: 1742s | Summary: Join the CHRO and CFO at HammondCare as they share their Workday journey including how the shape of work is evolving, including the growing complexity of AI in care settings, and what leaders must do to enable workforce capability, trust, and adaptation at scale. Hosted by Deloitte they also explore how the evolving partnership between CFO, CIO, and CHRO is shaping decision-making, value realisation, and workforce outcomes. Resources:Blog: Inside Anglicare's Move to a Skills-Based Hiring Model Demo: Workday Human Capital Management Suite Software Ready to talk? Get in touch.Talk to Sales | Chapters: Healthcare AI Introduction (11s), Financial Constraints Management (157s), Workday Implementation Benefits (282s), Workday Implementation (569s), Executive Role Convergence (788s), Cross-Functional Collaboration (1042s), Future Outlook (1337s) Video: Finance Strategy & Vision: A Practical Look at AI Agents in Finance | Duration: 3319s | Summary: Hear the latest insights on the state of AI in Finance for 2026, exploring how Workday customers are navigating the shift from simple automation to autonomous agents. You’ll get an early look at upcoming Workday features and releases including Workday Finance Agents, as well as a sneak peek at building a Finance AI Agent. Resources:Blog: How CFOs Can Govern the 'Black Box' of AI in FinanceReport: Realising ROI from AI Agents in Finance Ready to talk? Get in touch.Talk to Sales | Chapters: Finance Track Welcome (11s), AI in Finance (87s), Measuring AI ROI (177s), Data Quality Foundation (263s), AI Training Mandates (403s), AI Maturity Levels (524s), Cloud ERP Modernization (644s), Product Vision AI (781s), Finance AI Vision (918s), ERP Deterministic Platform (1003s), Workday Platform Architecture (1123s), Agentic Finance Vision (1284s), Agent Demonstration Transition (1465s), Financial Analysis Agent (1559s), Cost and Profitability Analysis (1748s), Productivity and Automation (1919s), Contract Agent Review (2105s), Audit Confidence (2308s), ROI and Early Adoption (2785s), Agent System of Record (2936s), Governance and Control (3251s) Video: Finance Customer Deep Dive | Summary: Join Workday's Esther Monks as she leads an insightful conversation with Finance Leasers including: Nicole Ebejer (Group Controller and Interim Global Head of GRC, Bravura Solutions), Thomas Schroeder (Managing Director, Global Workday Financials, Accenture), and Laura Garrett (Senior Manager, Finance Transformation and Cloud ERP, Salesforce). This powerhouse panel dives into real-world strategies for managing risk, driving global compliance, and leveraging data to build a more agile, resilient finance function, equipping you with the actionable insights needed to modernise your own financial operations. Resources:Blog: AI in Finance: What's Holding Australian CFOs Back?Report: Realising ROI from AI Agents in Finance Ready to talk? Get in touch.Talk to Sales | Chapters: Panel Introduction (11s), Career Journeys (78s), Team Roles Overview (167s), Evolving Finance Roles (259s), Accounting Center Implementation (444s), Strategic Finance Shift (594s), Implementation Strategy (732s), Business Self-Service (1144s), Change Management Strategy (1395s), Change Management (1549s) Video: Accenture Partner Lens: APA's Journey to Unified Finance on Workday | Duration: 1717s | Summary: Hear directly from APA's Finance and Procurement leaders as they take you behind the scenes of their Workday journey - from implementation to life after go-live. They look to share how operating on a single tenant with a shared data model has fundamentally changed the way their teams collaborate and make decisions, and why intelligent workflows and automation deliver more value than most expect. Whether you're exploring Workday or already on the journey, this session delivers honest insights, practical lessons, and a glimpse of what's possible when Finance, Procurement and HR finally speak the same language. Resources:Blog: AI in Finance: What's Holding Australian CFOs Back?Report: Realising ROI from AI Agents in Finance Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), Unified Platform Benefits (227s), Implementation Insights (688s), Closing Remarks (1546s) Video: Technology Strategy & Vision / Demo: Accelerating Transformation with an AI-First Open Platform | Summary: As AI moves from experiment to core infrastructure, CIOs are the primary architects of the machine-human workforce. This keynote sets the stage for the IT track, exploring how Workday’s open, AI-native platform eliminates technical debt by unifying the enterprise’s two most critical data sets: People and Money. We move beyond the hype to show how an open architecture allows IT leaders to stop simply maintaining systems and start orchestrating intelligence—creating a flexible digital backbone that turns raw data into measurable business agility. Resouces:Blog: A Better Way to Work: A Day in the Life With SanaDemo: AI-Powered ERP: The Workday Platform Ready to talk? Get in touch.Talk to Sales | Chapters: Technology Track Welcome (11s), Future of Work (94s), Legacy to AI-First (334s), Managing AI Agents (619s), Vertical AI Platform (765s), Capacity Planning Agent (1122s), Candidate Engagement Agent (1479s), Sana Platform (1931s), Third-Party Integration Demo (2153s) Video: Technology Customer Deep Dive | Duration: 1799s | Summary: As we enter the era of the "blended workforce," IT leaders are no longer just managing systems—they are architecting the future of work. Join senior IT leaders from Auckland University and Beca for a deep dive into how New Zealand’s leading organisations are moving beyond basic automation toward an AI-driven operating model. Resources:Demo: AI-Powered ERP: The Workday Platform Ready to talk? Get in touch.Talk to Sales Video: The AI-Ready Enterprise: Customer Discussion | Duration: 1794s | Summary: As we enter the era of the "blended workforce," IT leaders are no longer just managing systems—they are architecting the future of work. Join senior IT leaders from Hungry Jacks and St John of God Health Care for a deep dive into how Australia’s leading organisations are moving beyond basic automation toward an AI-driven operating model. Resources:Demo: AI-Powered ERP: The Workday PlatformBlog: Should CIOs Treat AI Agents as Apps or Digital Employees? Ready to talk? Get in touch.Talk to Sales | Chapters: Technology Track Introduction (17s), Speaker Introductions (70s), Pre-Workday Challenges (124s), Governance and Compliance (608s), AI in Recruitment (786s), AI Use Cases (905s), Lessons and Recommendations (1165s), Final Advice & Takeaways (1539s) Video: KPMG Partner Lens: The Future of AI: What’s Real, What’s Next, and What Leaders Must Do | Duration: 1826s | Summary: AI is everywhere — but beyond the hype, what’s actually real, what’s delivering value today, and what will truly matter for enterprises over the next 3–5 years?Join KPMG for an executive panel featuring CIO’s from Estia Health and Swinburne University of Technology as they cut through the hype to examine the real opportunities, risks and hard truths of AI adoption. Set against Workday’s accelerating AI investments, the discussion will explore governance, operating models and the evolving role of technology leadership, with a responsible AI perspective, joined by Professor Nicholas Davis from the UTS Human Technology Institute. Resources:Demo: AI-Powered ERP: The Workday PlatformBlog: Is Your AI Leaking? How to Audit Your Shadow Agent Risk Ready to talk? Get in touch.Talk to Sales | Chapters: AI Session Introduction (20s), Panelist Introductions (168s), HTI Research Introduction (263s), AI Misconceptions (478s), AI Governance and Controls (681s), Trust and Governance (900s), AI Adoption & Governance (1189s), AI Governance Structure (1299s), AI Implementation Challenges (1469s), Student Retention Case (1611s), Closing Remarks (1776s) Video: Datacom Partner Lens: What It Really Takes to Run Workday at Scale in the Public Sector | Summary: What does it really take to run Workday at scale in the public sector? Join leaders from the Ministry of Health for a fireside conversation on the real-world lessons learned. Hear how Datacom has implemented Workday alongside Datapay to make payroll powerful, embed HR platforms, and deliver lasting operational impact well beyond go-live. Resources: Demo: Workday Human Capital Management Suite Software Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introductions (14s), Team Introductions (137s), Catalyst for Change (269s), Platform Selection Process (463s), System Impact & Results (757s), Implementation Benefits (1103s), Implementation Challenges (1192s), Implementation Challenges (1399s), Rapid Fire Insights (1526s), Implementation Advice (1635s) Video: Adaptive Planning Strategy & Vision: Shape the Future with Workday Adaptive Planning | Duration: 3487s | Summary: In unpredictable times, unified planning builds resilience. Discover how agentic AI drives smarter, faster decision-making across finance, HR and operations. Resources:Report: Workday Adaptive Planning: 5 Innovations Redefining Modern PlanningReport: The Total Economic Impact™ of Workday Adaptive PlanningFree Trial: Workday Adaptive Planning Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), AIs Workforce Impact (374s), AIs Dependencies (480s), Automated Planning Workflow (622s), Data Foundation (1101s), Data Foundation & AI (1305s), Planning Agent Demo (2059s), Adaptive Decision Intelligence (2522s), Live Product Demo (2847s), Closing Remarks (3374s) Video: Adaptive Planning Customer Deep Dive | Duration: 1735s | Summary: Join Fraser Bearsley, General Manager, IDX and Antiona Scorciapino, General Manager – Finance Business Partners, Mission Australia, in conversation with Vince Randall, as they share their journey and success with Workday Adaptive Planning. Resources:FP&A Customer StoriesBlog: The State of AI in FP&A Right NowFree Trial: Workday Adaptive Planning Ready to talk? Get in touch.Talk to Sales | Chapters: Speaker Introductions (11s), Pre-Adaptive Challenges (166s), Pre-Adaptive Challenges (282s), Business Case Success (354s), Reporting and Integration (475s), Reporting Transformation Results (583s), Adaptive Reporting Benefits (755s), Forecasting Flexibility (884s), Reporting Surprises (1041s), Scenario Analysis Power (1157s), AI and Future Plans (1265s), Cultural Change Management (1443s), ROI and Self-Service (1539s), Cost Savings & Future (1630s), Session Closing (1717s) Video: Tridant Partner Lens: Transformation from the Inside | Duration: 1684s | Summary: Real decisions, live lessons from one of Australia's leading fintech platforms, Hub24 is a platform business built on the promise of smarter, more connected finance for its clients. Now they're applying that same ambition internally, transforming their own FP&A function with Workday Adaptive Planning. Clinton Wells joins us to share what that journey looks like right now, the complexity, the breakthroughs, and what finance leaders at any stage of transformation can take away. Resources:Free Trial: Workday Adaptive Planning Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introductions (11s), Trident Introduction (93s), Introduction to HUB24 (208s), Hubs Finance Vision (267s), Reporting First Approach (404s), Streamlining Reporting Processes (698s), Business Metrics Evolution (1106s), Conclusion and AI Future (1290s) Video: Student Strategy & Vision | Duration: 2458s | Summary: As the higher education landscape evolves, the shift from fragmented legacy systems to a unified platform has become a strategic imperative. This session explores Workday customer outcomes and our latest product innovations designed to meet the unique needs of modern institutions.We will dive deep into Workday Student, showcasing how a cloud-native student information system (SIS) transforms the student and administrative experience. Furthermore, we will discuss why a unified data core is no longer just an operational advantage but the essential foundation for leveraging Artificial Intelligence. Discover how integrated data empowers institutions to move from reactive reporting to predictive insights, ensuring agility in an increasingly complex academic environment.Resources: Webinar: The AI-powered Student JourneyBlog: Rethinking Tertiary Education: Preparing for an AI-Powered FutureWorkday Student Quick Demo Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), Higher Education Growth (236s), Higher Education Adviser (434s), Student Growth Metrics (643s), Product Capabilities Overview (837s), Personalized Student Experience (1009s), Student Administration Agent (1314s), Transfer Credit Skills (1438s), Academic Requirements Skill (1746s), Student Data Insights (1890s), Early Adopter Institutions (2063s), Student Experience Demo (2126s), Closing Remarks (2321s) Video: Student Demo | Duration: 1359s | Summary: Watch Workday Student demo live and uncover common challenges such as recruiting, student journey's, paperless request forms and our AI powered capabiliites. Resources:Webinar: The AI-powered Student JourneyBlog: Rethinking Tertiary Education: Preparing for an AI-Powered FutureWorkday Student Quick Demo Ready to talk? Get in touch.Talk to Sales | Chapters: Introduction and Setup (11s), Student Mobile Experience (93s), Student Journey Navigation (199s), Profile Management (283s), Workday Recruiting Solutions (411s), Credit Transfer Rules (597s), Request Framework Demo (932s), Closing and Next Steps (1139s) Video: Student Customer Deep Dive: Leader Panel | Duration: 1243s | Summary: Join us for a powerhouse discussion on the sector's biggest pain points and lessons. Michael Johnston will be joined by Australian tertiary leaders, including Mark Erickson, Registrar at the University of Sydney, and Connie Merlino, Secretary and Academic Registrar at RMIT University for a quality panel. Resources:Webinar: The AI-powered Student JourneyCustomer Story: Pensacola Leverages Workday Student and ExtendWorkday Student Quick Demo Ready to talk? Get in touch.Talk to Sales | Chapters: Panel Introductions (12s), Panel Introductions (104s), Value of Degrees (139s), Regulatory Challenges (416s), Predictive Model Impact (600s), Student Experience Vision (751s), Lifelong Learning Models (953s), Post-Graduation Outcomes (1082s), Closing Remarks (1192s) Video: Student Customer Deep Dive: Pensacola State College | Duration: 2515s | Summary: Hear from Michael Johnston of Pensacola State College who will share their transformation story, discussing the "why" and "how" behind their Workday Student implementation journey which drove a 43% increase in full-time registration over two years and saved over 40K+ paperless requests. Resources:Webinar: The AI-powered Student JourneyCustomer Story: Pensacola Leverages Workday Student and ExtendWorkday Student Quick Demo Ready to talk? Get in touch.Talk to Sales | Chapters: Welcome and Introduction (11s), Legacy System Evolution (216s), Student Recruiting Module (318s), Student Application Process (679s), Paperless Student Processes (1022s), Request Frameworks (1188s), Johnnys Journey (1302s), Student Risk Assessment (1518s), Advising Cohorts (1751s), Student Journeys (1874s), Faculty Workload Management (1994s), Dashboards and Analytics (2230s), Closing Reflections (2435s)

Transcript for "Technology Strategy & Vision / Demo: Accelerating Transformation with an AI-First Open Platform": Right. Good morning, everyone. Thank you. Thank you. I haven't even started speaking yet. Right. Welcome to the, technology track. Now you guys are in for a treat. There is actually a Australia exclusive that not even some of our workmates have seen that you're about to see. But this is where we get really deep into the technical stuff, and we we start playing around with some of these, concepts. It's gonna be better than the finance and the HR track. So if you if you have friends over in the other track, just make sure you remind them that they was way, way cooler than what they saw. Right. So, I'm gonna find the clicker. Clicker. One second. Thanks. So by way of introduction, Sean Mote, loser of clickers, and, also chief technology officer at for APAC for Workday. I'll be joined on stage shortly by Emma Thortzen, who is our principal technologist for platform and AI for ANZ. And we'll be taking you through, some of the strategic concepts that we're driving, that's driving Workday's AI future and also demoing some of those concepts as well. So before I begin, I'll be talking about things that's in the development pipeline. So there are unreleased things and Australia exclusives that you're gonna see. Please make your purchasing decisions based on features and capabilities that are in the market right now, not based on the world exclusive demo that you're about to see. So the topic for today is about the future of work and more importantly, the role of you as IT leaders in this future of work. We'll define what happens in this future of work, like how how the workplace shapes up. And then we'll finish with my favorite topic, which is lawlessness in the in this future of work as well. And we'll have some fun with that. As AI continues to gather pace as a board level topic of conversation, CIOs and IT leaders like you folk, increasingly situated as the AI architects of the enterprise. You're no longer just technical implementers. You can tell that to your friends now. We're not just implementing this stuff. You're expected to research this and evaluate the AI landscape. Now if you're anyone like me, you will get hundreds of vendors calling you on a daily basis saying, you know, I have this new AI feature. So hopefully, by the end of today, you can go away with a framework to discern what is real future work enabling AI and and what is noise. So as you as you navigate this, you also have to understand how that adoption results in real ROI as well because we're beyond this experimentation stage. Last year, we were given permission to experiment. And, unfortunately, only 5% of those experiments according to surveys have gone to production. So now this year, the the the onus is on us to take these experiments and put them into production. And in order to put them into production, there is some real world requirements that need to be met. So AI is elevating CIOs further into their strategic leadership across that organization. So if ever we wanted a seat at the table, we've got it now. Our voices are being heard, and we need to be very clear on what we say. As as this shift in remit is driven in large by this acknowledgment that the future of work is going to be a human and machine collaboration. I just wanna pause for a second there. You in this room are the last generation of people who are going to be managing a purely 100% human workforce. Every single person that comes after you, their norm is going to be an AI and human workforce. You're the transition stage. Right? Like, you you are going to be learning how to do this, but every generation that comes out of you, after you, is going to take that as a new norm. So in the past, we've used GenAI to generate insights, and content. And you've used natural language assistance to prompt recommendations and quick information gathering, for example. But this is only the beginning of how humans collaborate with AI to transform how work gets done. And IT leaders like you are positioned as the architects of that transformation. Now at Workday, we work on this hypothesis that AI or AI agents in particular is not just another application. It's not a new class of application. It is actually a new class of employee. So you got full time permanent employees, you got contingent employees, and now you have digital employees. And learning to manage that is something that you have to do. And when you master it, you have to teach it to the rest of the organization so that they can master it, and every generation after you can master it as well. So, you know, bit of load on your shoulders. Thankfully, we're also moving away from this whole concept of legacy ERP, which is all, it's static and siloed to an AI first platform that is dynamic, intelligent, and very importantly, open. So definition of legacy ERP is they're, fundamentally transactional systems of record. They result in data fragmentation with limited AI capabilities, which are disconnected from the flow of work. You can recognize it because it's based usually on a database and, you know, you sit there wondering whether you can layer your LLMs on top of this database. The the approach from an adaptable future ready ERP, a future ready platform is different. It's a system of action. So this is not just data, but it's also context that allows you your AI agents to act on that. It's open by design, allowing seamless integrations and delivers real time AI driven insights. And it allows for extensibility through APIs, local tools. It should give you things like MCP servers. It should give you access to agent to agent protocols so that any AI agents that's built built on that platform can interact with agents outside the platform as well. And it helps you reduce that technical debt by being in that open, being that open architecture. Now I know standing up here and talking about open architecture sounds new because in the last twenty one years, Workday has always been seen as a closed platform, and there's a reason for that. We wanted to make sure we had the right quality and the right, experience for our customers. But in this agentic world, we have to be open. We have to fundamentally be open as a platform so that we can interact with not just or you can interact with not just our own agents, but agents that you build off the platform can interact with us as well. So this future ready approach is reflected in the in the Workday platform, and we can have a look at this now. Now you've probably seen this slide a few times today. Yes. I can I can tell from the smiles on your faces that you have seen this a few times today? I'm gonna remove these words, deterministic and probabilistic, and I'm actually gonna replace it with words that my four year old uses. So I had an epiphany when I when I was talking to my four year old. She she said a statement. She said, dad, you're really tall. And I was like, oh my god. Someone actually thinks I'm tall. But it comes down to context. In her context, I'm really tall because I she's like this big and and I'm this big. So for her, I am tall. One day, she's gonna meet a basketballer or an AFL player and she's gonna go, dad, you're not tall anymore. And that's because her context has changed. Now what she's done is she's formed opinions based on what she's seen. Right? So because she's only four, she's only seen me. Her context window is quite small. So she thinks I'm the tallest person in the world. As she grows up, she's gonna see she's gonna experience more context and she's gonna form different opinions. And this is where Workday is truth and AI is opinions. I think that's the words that we should be using. If your AI is exposed to fragmented truth or if it's not exposed to the right truth, it is going to form opinions, but those opinions are gonna be pretty bad opinions. If you want that AI to make up or to come up with educated opinions, well informed opinions, you need to have a platform that gives you a source of truth that is solid. So that's what Workday, brings to the table. So by design, Workday is deterministic, which means we protect the truth. It's consistent. It's got audible auditable outcomes, and we have the enterprise rails. AI, on the other hand, opinions. It reasons, it predicts, and it recommends. It's when you bring these two worlds together that it that brings this opportunity, and it's one that only work they can do. The people in your organization deserve a platform that can manage the truth as well as Workday can so that you can then run AI on it to form opinions that is world class. And it's this hybrid future, trusted systems of record with AI built alongside that we propose as our future. Now you might be asking why Workday? Why not one of the other enterprise applications? Like, I know in my career, I, at one point, don't tell Nicky this, but I at Telstra, I was managing 3,000 applications. The truth is most technology leaders currently only have two categories of software to manage, AI agents. You either have an HRIS system or an ITSM system. HRIS, human resources management system, and ITSM, IT management system. But unfortunately, AI doesn't quite fit into these two perfectly. So for example, if you make the assumption that an AI agent is an application, how would you traditionally do that as a as a software system? You would bring it in. You would do some testing. So normally, what you do is centralize the whole application. You do testing of 10%, 20%. If you're good, maybe more. And then you basically assure that the other 80% that you haven't tested will work the exact same way. AI doesn't work that way. It it does action a and action b and then results in action c today. But as it learns and evolves, tomorrow it might do action d. So you need a 100% testing all the time. So our traditional IT practices doesn't necessarily scale, which means when you manage it as an IT application and an ITSM system, it doesn't scale either. On the other hand, if you put it into an HR system, well, think of it this way. If you try to put an AI agent in an org chart, it doesn't fit cleanly because the same AI agent in a different can be deployed across multiple teams. And in multiple teams, it'll have different skill sets that it uses. Different teams will train and reinforce it in different ways to act differently, but you've still got the one agent. So how do you actually manage that in an HR system? As a person, you can't you don't go across multiple teams and you don't do multiple you you don't exhibit multiple skill sets. So it's not a clean fit into an HR system either. So AI exhibits both the characteristics of a person, but also characteristics of a software as well. And so managing AI agents is this new paradigm that falls in between managing people and managing software. And Workday is the only platform equipped with the ability to do that. We're the only vertical AI provider. So, one of the terms that you'll hear, more and more increasingly is this notion of vertical AI and general AI. So general AI is your co pilots, your anthropics, your open AIs because it gives you a general platform, and you can build anything on it. You just use the LLMs to, or the the the you prompt your way into building whatever you can imagine. Vertical AI, on the other hand, is something like Workday where we give you 80% of the capability. So it gives you the the business context around how how to manage a person, the business context around how to manage your finances, how to do planning for example, and then you focus on the 20% on top to build out your company's IP. It's very different proposition to your general AI. So we're the only vertical provider with a system of action on which people and AI agents from other vertical AI, like Salesforce, Adobe, and so on, And provide and agents that you build on general AI providers can all act on. We're the only ones where you can do all of this. So if you look at the tools on the market today, they each attack a slice of the problem, but they widen the gap value in different ways. The ecosystem specific, assistance like Copilot, they're pretty easy to roll out. I mean, you press a switch, Office three six five license gets you there, and you drive that personal productivity. But they can't run your core HR and finance workflows. Enterprise search tools like Lean, for example, it'll find documents and it'll answer your questions in chat, but they weren't built with an agentic architecture to take actions. And then automation platforms like ServiceNow or ticket centric tools, they're powerful, but they're expensive, brittle, and slow to deploy. They weren't built for an AI driven, agents that learn and adapt. And the one that's close to my heart, building in house now we do this because that's what that's our business. But if you were to build agents in house, sure. It gives you the flexibility, but it costs you a fortune to maintain. Lots of CTOs are currently coming out saying they've blown through the entire year's budget of tokens in four months because that's how fast they've consumed it. It gets very expensive once you start putting all those things into the context. The common thread, none of them give you none of them give your agents the deep business context and end to end execution and the governance that they need to that they need to do real work. The governed platform for agents that we're building is made up of three things that need to come together. Grounded context, configured compliance, and scope execution. So this is where I'd ask you to test any of these notions in the industry that you that you might have heard around. Just put an LLM on top of your data and you're good to go. Right? We've all heard that story. But what you need to ask is, can it actually guarantee that these three foundational things that are necessary for running HR and finance are enabled in the platform? If not, it's just not ready for the enterprise. Now in the future, we're confident that humans will work alongside, agentic teammates to accomplish massive goals. And we've introduced already the notion of this agentic teammates and the different personas of agentic teammates that you might have, seen in the previous talks. As we reinvent HR and finance, our focus is in a few places. The first one is we're turning systems designed for record keeping into systems optimized to advise your senior leaders. That turns a system designed to follow simple workflows to a system designed to act creatively. For example, if you have a 100% manual workflow that requires human authorization, if that person is asleep or is on leave, when it gets to that point, it comes to a grinding halt. But with AI, with an agentic system, you could have the agent analyze that person and go, wait. There's someone else in this team who has the same delegation of authority. Let's try them. But if you didn't have the right context, it would go to anyone in your organization. It's only when you have the right context to go. This person is also allowed to do that approval. So that's the bit that you need. So it enables you to reach outside the system when the standard process fails. This is that creativity that AI brings to the table, but you need to mix it with the guardrails. And lastly, we're design we're designing these agents to be always on, autonomously scaling and meeting the needs that you have when you have them. So put those three things together. You've got agentic systems that advise, act, and are always on. And we'd be crazy not to believe that HR and finance won't be transformed. Our customers can rethink the bottlenecks in all of your business processes. So as you may as you may have noticed, these agents come in two flavors. One, they can act on your behalf where you delegate authority and access and and authorization to these agents, and then they carry out actions for you as you. Or they can run-in the background always on even when you're asleep or when you're on leave. The best way to understand this, however, is to see one in action. So I'm gonna hand over to Emma, who is going to do a demo, to show us what both of these agents look like. So, yes, as promised, we are gonna have a look at two different types of agents that Workday delivers. The first one is an agent that gets activated by you invoking the agent. So what we're looking at here is we're pretending to be a financial analyst. We're doing some capacity modeling for the year ahead. This is not something that we do all of the time. This is not we don't want a capacity plan that is constantly fluctuating and telling us to hire people at any point in time. It does tend to be that we're going to go in and we're going to plan for the year ahead. Using the agent we're going to ask it to look at a couple of different segments and a couple of different data sources. Now this is traditionally done in Excel and Excel works really well, we all know that, we all love Excel, But once you want to make a change to your capacity model, if you want to add a new segment, that's something that can take days or weeks for the poor financial analysts to actually implement that change in their spreadsheet. So we're going to have a look at how with an agent it's simply a sentence. So the first thing we're going to do is we're going to ask the agent to build us a capacity model and we're going to specify the data sets we want. So we want from Adaptive Planning and we want from Salesforce as well. The agent is going to go and connect to the two data sources and then it's going to ask me some clarifying questions. My prop was pretty light in just build me a capacity model. So it's asking for some clarification. I'm going to give it the required clarification and then off the agent goes to build my capacity model. You can see here it goes through a couple of different reasoning steps and then it has an observation here. It's noticed that there's a productivity variation and do I want to see a full breakdown of this? Yes indeed thank you so much. Lovely agent, I would very much like to see a full breakdown of this. This graph that we've generated here has not been pulled out of Adaptive Planning or Workday. This is not pre built. This is the agent creating the analytics in the situation as I've prompted it to. So it has given me some insights and then I want to drill into the HR segment of this graph. I can either type break down the HR segment or I can click on the graph. So this is a hybrid conversation with the agent. I can prompt it using text or I can prompt it by clicking on the analytics that it has created. So we're going to drill into the HR domain area and here we can see that the agent is telling us the volume is the driver. So it's not our workforce that's underperforming, we are just experiencing an increase in demand. So we're going to ask the agent to create a projection for fy 27 headcount numbers. The agent will go through and create the projection for us which we can see again it is creating the analytics and underneath the analytics we've got the deltas around how many headcounts does the agent recommend that we add. Then we can go and ask the agent to yes we would like to break it down by customer segment. Now the agent is going to come back and tell us it actually doesn't have customer segment in the data set but it's going to offer up to make an estimation based on what we know to be the most commonly used practice and we agree to that suggestion that is a great suggestion from the agent. And here we go it's now created the breakdown by domain and segment which as we know would be a slightly more time consuming activity had we done this in Excel. We are asking the agent to take it a step further. We know that we need some more HR analysts in the payroll space and we would like the agent to create these requisitions for us. So we've gone through and pulled the data set from two different data sources. We've built the analytics, we've drilled into a specific area, we have created a headcount projection for f y twenty seven and we have asked the agent to create the requisitions that it can then create inside of Workday. The requisitions in Workday will always have a tie back to the decision point that the agent has created in this headcount. This is an example of an agent that does sleep. Just, just on that. So as you as you saw Emma go through that, None of those UI elements were actually pre rendered. Right? So they're all rendered on the fly. So just to go one level of geekiness lower Alright. Let's go. What we're here for. Alright. So what we do is we have a library of UI elements for basically communicating, or rendering the Workday front end. And we make that available to our AI agents using an MCP server. Right? So internal MCP server, which we make available to our, AI agents, it can then go in and use that library and go, okay. Based on the context that I have for this kind of data, I'm gonna render it as this. One of the other things that you also saw was where it offered up an estimation. Mhmm. Now this is what happens in a normal business process. That process would have just come to an end. I don't have the data. That's the end of that conversation. But because this agent has got that additional context, the business context that we bring to the table, it's able to offer up a next best estimation that can serve as a proxy. That's the level of intelligence that you normally wouldn't get or you would have to program it yourself. Now think of all the edge cases that you have to think of to in order to prompt that into existence. But this, out of the box, there it is. Thank you. Trust. Keep going. That's all good. So that was an example of an agent that does sleep. It comes to life when you invoke it and you start prompting it. An example that we have of an agent that never sleeps is our candidate engagement agent. So we're on the job hunt now. We are on a careers website, we're having a little peruse because we're thinking of maybe doing a bit of a career shift. Now as we enter this career site I could do a traditional search for roles where I could simply view the open roles, I could go through the normal filters. Instead of doing that I'm going to engage with our engagement agent, our candidate engagement agent also known as Bolivia. Olivia compared to normal recruiters never sleeps. So Olivia Some recruiters don't sleep. Some recruiters don't sleep. I hope your recruiters sleep and to allow them to sleep we've got Olivia who can filter questions and help candidates throughout their hopeful employment journey. So I am gonna engage with Olivia, I'm gonna have her help me find a job and apply for the job. The first thing that Olivia is going to prompt me to is to review the terms and conditions because if you know one thing about Workday's approach to AI, it is responsible AI. So we want to make sure that the candidate who engages with Olivia is okay with her collecting information on behalf of the company, and I am surprised surprised very much okay with that. Now I could let Olivia prop me through this process, but I'm going to be very specific. I want a customer service job in Melbourne sorry Sydney but I enjoy fickle weather so I'm going to look for a job in Melbourne. We do enjoy the fickle weather. Layers is my friend. Here I've got a couple options. I am gonna take this customer service representative. I can click into the job application and I can view more about the role. I'm going to choose to apply now. In a standard process this would be the place where the candidate would get prompted to go and create an account. Now does anyone want to guess how often candidates will drop off at the point of creating an account? It's a relatively high number. One of our customers, Chipotle, who has deployed the candidate engagement agent has seen the completion rate of their application go from 50% to 85% means that half of the candidates, half of their pipeline was completely dropping out of the race before even submitting their application. I'm going to give Olivia my name also so that you all remember that my name is Emma Towson in case you didn't remember that from the introduction and then Olivia is going to start prompting me for some questions. So I'm going to give it my email address and then I'm going to give Olivia my real phone number as well because because why not? No it's not my real phone number please don't text me. Just that little caveat. I'm gonna agree to both email and text message. We do respect what the preference is of the candidate and then Olivia is going to connect to Workday recruitment and all of the questions that I get asked as part of this process Olivia has pulled directly from Workday recruitment. Some of these questions will be mandatory, I have to complete them, some of them I will have the option of skipping and maybe coming back to my application at a later stage. Obviously this is a configuration decision for you. I am gonna skip uploading my resume, but if you think about how different this application process is from our standard complete a form, have your account, It is a completely different and this could be done on the mobile device as well so we're not restricted to simply, desktop. Now Tripathi as I've mentioned before has taken up Olivia and, does anyone wanna guess what they've renamed her? Because you don't have to have her name as Olivia. Chipotle has their engagement agent is called Ava Cardo. Clever. So lucky me I have already gone through the screening process and I am now on to my interview round. So Olivia's already proposing a few options for me. I'm gonna go yes I want to do the twenty seventh at 04:15AM because I never sleep when I'm looking for a customer service job. Now imagine how long this would take for a normal recruiter to have to coordinate their times, the hiring managers time back and forth with the candidate instead everything is coordinated through Olivia. One of our customers that's taken up Olivia they saw their scheduling to go from days down to seventeen minutes for candidates to actually book in for an interview so and a significant, optimization. What Olivia can also do other than simply helping you go through a recruitment process, Olivia can also ask questions. So again it can be hard for candidates who are interested in your organisation to actually engage with you. The career site tends to be a bit of a blocker. If they've got questions about say if we want to know what it's like to work at TMS, I'm going to ask Olivia what's the vibe at GMS because that's the kind of thing that my generation would say because we're very we're generation very young over here. What's the vibe? The feels? What's the vibe? What's the feels? And Olivia will then be able to interpret that question because she's a smart gal and she knows that by vibe I mean what is it like to work there and she offers me information about the culture at GMS. So those initial questions that a candidate might have that typically they would have to send off to some shared inbox for your recruitment team to then have to work through when they have a spare moment and they do not have a lot of spare moments, those for recruiters. Instead, Olivia is always available to answer those questions because Olivia never sleeps. We keep saying that. But one cool thing about this is imagine you you run you're in the health care business or you're in the, you know, the the services industry where people are doing shift work, for example. When they finish their shifts, the recruiter is not available because they've clocked off for the day. So imagine how hard it is to line up an interview and and, you know, make sure your timings all match up and everything. So this is a game changer for for those industries where your your services are available to your prospective employees when they want them to be, not when you want them to be. Correct. Cool. Thanks for that, Emma. So what we also saw was yes. Of course. Of course. So that was that was a demonstration of not just the the AI capabilities, but also the speed at which you can get things done. Right? So when you turn a synchronous process into an asynchronous process, or when you turn that process into something serviced by an AI agent that never sleeps. Always on is what we call it. Never sleeps. You know, what if you could combine Workday's trust and certainty with that predictive power and speed? And this is where the magic happens through Sana. So you would have heard about Sana a couple of times today. Sana is to Workday, what Gemini is to Google. That's the easiest way I can explain. It's both the platform on which Workday builds, orchestrates, and runs our AI models, and and agents, And it's also the experience that your that your employees will get to engage with in entirely new ways. By embedding AI directly into your organization's workforce data, financial structures, policies, approvals, and regulatory obligations securely and reliably, we can give AI the guardrails to operate with superintelligence and also certainty. So if we drill deeper into the services where Sana appears, Sana is, accessible through its own web app. Now the keen eyed among you would have noticed that, Emma was actually using a UI that was relatively new. So that's the Sana web app that that, she was demonstrating. And it also will feature inside Workday as well as the new AI experience and in the interface for the, core Workday platform. Now on the last column, you'll also see Sana will start appearing inside other business applications as well. Like, if you look at the logo in the top corner, that's Salesforce. So where you actually embed Workday into third party applications we call them third party, but your other applications in your end in your enterprise portfolio, you can start interacting with Sana through those widgets as well, and that's coming soon. Ultimately, this AI sprawl reality is what we're trying to simplify. Instead of having one set of tools for research, another set of tools for chat, one set of tools for automation, another set of tools for content generation, and each one of those having its own permission and blind spots, Sana consolidates all of that into a single AI experience within where employees get agents to find, act, build, and automate. Instead of managing a dozen AI vendors, customers like you will get one platform with one set of controls and an audit trail for all of them. Sana lives inside Workday, so every agent inherits your roles, approvals, policies from day one. You don't have to do a massive integration project anymore. And speaking of integration projects and projects in general, I think the age of transformation is coming to an end, hopefully, thankfully. We've all seen digital transformations. We've seen big data transformations transformation transformation. AI, I don't think you if you're gonna wait around for an AI transformation, that's not gonna happen. I think you're gonna have to step into this world of continuous evolution, continuously reinventing the the business workflows using AI. So it is only when you start leveraging tools like this that you can actually continuously improve and iterate on what you have. So Asana will connect into Salesforce, ServiceNow, Slack, Gmail, and hundreds of other applications. So this is thanks to, acquisition of Pipe Dream in part. So you actually have access to up to 3,000 applications in Pipedream. We'll see that shortly. So a single workflow in your enterprise can actually span your entire stack. So Sanae is both your front door for your employees as well as one governed orchestrator underneath as well. So speaking of connecting into other applications, Emma is gonna do one of the most things. This is like walking a trapeze line. She's going to actually do a connection into not work day, but a third party application live on stage. So no pressure. Take it away. No. It'll be fun. So we've done two demos so far today, and we haven't actually been in core Workday. So I thought I'd I'd spend a moment in here just for familiarity. And we are in as everyone's most beloved Logan McNeil because you couldn't have an Elevate with no Logan action. Now the Workday UI is not going away. Obviously, you'll still have finance administrators, HR administrators who will be spending a lot of time inside the Workday that we already know and love and have invested so heavily in throughout the years. But what about the more occasional use of the I need to see my payslip, how much leave do I have left? Do they want to learn more software, do they want to have another application, I mean we heard the lovely story about the 3,000 applications at Telstra, employees don't enjoy learning new software in case you were wondering after on a poll, trust me. So what we are providing is an alternative to that and that alternative is Sana. Now from the Workday interface I can simply access Sana or I can do it from when I'm in our Workday sauna environment I do it through my Octa tile or you can go directly to the hyperlink as well. So there's many options of accessing sauna. This is a simplified access to Workday so right now Sana has access to Workday, and we can interact with Workday through conversations. So what if Logan wanted to get some information about her team? She wants to have a list of my team, their goals, and their learning items. Now you might tell me, Emma, that is so simple. I know how to get that information in Workday, and correct that is exactly what Sana does. Sana activates the Workday agent to go and retrieve that information. Now do you have that already pre built as a single dashboard for Logan to easily access or would she have to navigate into each of her team members worker profiles to get that information or go to your HR administrative team and ask them to pull that information from her in one report. Instead through a simple prompt she can get that information through Sana, easy as that. Now we mentioned before the ability to connect to third party systems. So the first cab off the rank is connecting Sana to your Workday environment but we're not going to stop there. You have many more applications in your tech stack than just Workday and this is where the acquisition of Pipedream comes in. As Sian mentioned this gives us access to more than 3,000 certified connectors to various enterprise applications. Logan's already been in and connected her sauna to her Outlook calendar and her Outlook email. Today we are going to also connect to SharePoint. As an end user I have full control over which applications I'm comfortable with connecting Sana to. So today I'm going to connect Sana with us through to SharePoint which is is done through the pipe dream connector. I simply select do I have the right password? Pretend like this didn't happen and we are gonna go back into the user settings and we're going to continue on with our chat like we just connected to the kartheem and that worked and like Emma didn't have the wrong password. I'm glad you didn't have it on a post it note on your screen or something. It's like posted it out to the world but what Sana can also do is Sana can take action and Sana can take action into all of the systems that you have connected it to. So say if Logan has had a bit of a rough morning, she came to work and there was a wet floor and she nearly fell and that was an unpleasant experience for Logan. So Logan is thinking this can't be right. I nearly slipped due to wet floor in the office this morning. I think I should raise a workplace safety safety case. Now once she's asking Sana to do this, now Sana will then consider is this a workplace safety case, how to identify the system that's appropriate. Sana will go to Workday because Workday is responsible for workplace safety. To create the case slippage incident is the title and the detailed message is I nearly fell and it was awful. It was a rough morning. Now Sana will keep prompting me for more information so it will go to Workday and see what does that workplace safety case need for information and make sure that it has appropriate information for me to then go and submit that case. Now I can do all of this through just conversation with Sana rather than me having to know the exact area of work there, which menu, where do I go, how do I submit it and now work Sana has created the case for me. I can then always go into core Workday and view that safety case that I've created, but what I can also do is I can have Sana because this has been really rough for me so create an out of office to tell everyone I can't work as I nearly slipped. So we're not restricting ourselves to just interacting with the Workday system we've connected it to Outlook which she is telling me and by the way my sauna is female you can say what sauna is for you but yes draft it. I could then have Sana create that email for me which it could then go into Outlook. Now it's important to note here that Sana will respect the security parameters of the system it's accessing so you can't prompt your way to do something in a system that you don't already have access to. So here we can see the Outlook email that Sana has created and I can then set that to activate in my Outlook because I had a workplace safety incident. But if I'm going into Workday for instance I can't prompt my way to give myself a pay increase, not that I would have ever attempted that, but Workday knows that that is not within my parameters of access and it will block me if I try to do that. So Sana will always respect the system that you're accessing and the limitations you've set for each user. Wow. So, yeah, normally, we we would connect this to SharePoint and If you have the right password. Would yes. If you have the right password. So sign up would basically go into SharePoint, retrieve the policy documents, and go based on this policy document, you can raise an incident. That's the bit that we didn't show you. But, never nevertheless, the the fact that you can now interact with hundreds of other applications mean you don't you you don't have to train people on how to do all these things, and they're always gonna be compliant because they're always gonna be using the latest and greatest version of that policy. So instead of your onboarding being a one week process where they mindlessly stick you know, press next on the compliance training modules, you could just say go to Sana and ask it to do whatever you need to do. It will follow whatever policy is current at that time. It will guide you step by step through these processes so your error rate comes down. Your compliance level goes up. Thanks, Emma. And thank you for trying to break the law as well by trying to give you a raise, which is a great segue to my favorite, part of this thing, which is around lawless agents and lawful agents. Thank you. Right on cue. Gotta have some fun. So give a lawless agent the wrong level of access. Come on, guys. And and it will hallucinate its way through a number of nightmare scenarios. So it will move money, for example, without the required approvals because it's hallucinated that a shortcut is more efficient. It might schedule the wrong employee in violation of labor laws because it's prioritized productivity over compliance. It might expose sensitive data that was never meant to leave the system of record because it couldn't say no as Emma just talked about, to a clever prompt injection. Not because it's malicious, but because it has no constitution. It has no concept of what is the right thing to do. It can see everything, and it has no idea what not allowed means for your specific business. That gap is what we call the lawless agent problem. Beyond the liability, there's this classic architectural failure mode that's starting to, emerge. If you try to solve this lawless agent problem manually okay. Last time I paused. If you try to solve this problem manually, the path might seem logical at first. Right? Like, say you you you wire a bunch of agents into your data lake or data, you know, a database, for example. Then you come to the realization that you need rules. So you start encoding all structures and and approval chains into one of scripts and prompts. In the short term, you end up with agents that are vibe coded. That's what this whole phenomenon is all about. But what you're doing is you're stuffing prompts with policies and tools into a crowded wind context window and hoping that the model pays attention to those rules as well. Now let's fast forward this eighteen months. You effectively vibe coded your way into a shadow ERP system inside your AI stack. You've spent millions reconstructing Workday logic because, don't forget, every time this thing runs, you're consuming tokens. But without any of the unified object graph, configuration, compliance, machinery that keeps it all current. From an engineering perspective, like, this is what I have to tell my team not to do, this is a massive mistake. It costs more, it's riskier, and the quality is lower. Tokens are more expensive than an if then else statement in engineering. Right? Like, that's everyone knows that. So why would you put all of that into an AI model and try to recreate an ERP system? And more importantly, is your line of business creating ERP systems? If it's not, you shouldn't be trying to build it because then you will own the tech debt that comes with it. So why why do why do you take why take on that tech debt of keeping a shadow copy in sync when all that logic already lives inside Workday? So how does this logic work in our platform? So this is what the front door, the secure front door looks like, connecting every agent in Workday. Whether it's a Workday built agent, a partner built agent, or even a customer built agent. This is how we connect all of these agents into Workday's data and processes. If an agent takes any action inside Workday, it comes through the agent gateway where we establish its identity and trace its interactions to provide auditing of lawful actions. If you've already built agents outside of Workday or in your business, these agents can delegate to a Workday agent to act on its behalf. This leverages all the logic and processing delivered by Workday's agents following deterministic processes and correctly notifying and escalating to humans when it's needed. You're better served when AI reasoning happens inside Workday with all the processes, approvals, and trust controls all applied by default. In Workday, the agent system of record, which you might have already heard about, is where every agent gets its identity and its permissions. But registration is not just a security step. It's also an ROI unlock. When you register any work any agent into Workday, including third party agents, you get full traceability and auditing of agent actions on your most sensitive data. You get usage analytics that business users can act on, and you get a data foundation for deep agent analytics. Speaking of analytics, let's just go a little bit deeper into what our expanded vision is. And this is where you're all going to be seeing something for the first time as I have mentioned many times in this, talk. There will be a blood pact that you have to sign outside as you leave so that we are also on to secrecy here by the way. So when we think about agent analytics along these lines, first, observability analytics for which is your safety and trust layer. So things like hallucination rates, bias detection, volume of high risk agents, and also, more importantly, agent to agent network visibility as well. We'll cover that in a sec. Secondly, engagement analytics. So as you start rolling out these agents, how are they are they being adopted? Who's using what? Through which channels, and how are these agents performing, and more importantly, where are they not performing as well. And finally, business impact analytics, which which allows you to cost projections alongside productivity metrics from each one of those agents. Like, for example, one agent might do time to fill, another agent might do time to close, so that you can start measuring those agent outcomes as well. To bring this all to life, the the piece the resistance, we're gonna show you what that agent system of record looks like. As well. Take it away, Emma. Thanks, Sean. So this is the vision for what your agent system of record is going to look like in terms of the analytics capability. So those three areas that Sean mentioned before we will have dashboards made available. The first one we're going to look at is observability. Now observability might seem simple when you're only looking at deploying one or two agents, but once we're into the double digits of agents and not just single agent interaction but agent to agent interactions as well this becomes increasingly important. In the observability we can see that we've got a multi agent interaction volume of more than 1,200 interactions that's an agent handing over to another agent that's the type of activity that you're not going to see in the end user space. I think this is something that shouldn't be understated. So so far, we've been talking about human to agent interaction. Right? So we've all been grappling, or wrapping our minds around when do we actually hand over to agents. The new paradigm as of a few months ago when we had teams of agents is now you have people handing over to agents, and those agents then calling other agents agents to agents to agents and so on. Right? So you can you can see where this rabbit hole leads and the obscurity that comes with it. So unless you actually have visibility, a 100% visibility, a 100% observability, this can become a very big problem in the enterprise. Correct. And what we can see in our observability dashboard is that 88% of those agents or agent interactions are actually successful and it's increasing so that's a positive. We can see that the expense agent is having some issues so that's get that gets highlighted on a flag for us early so that we can actually address that. Another metric that we're measuring is hallucinations. Now as we're grounding our agents we will give the parameters around what the agent is available or is available for the agent to interact with in terms of for instance policy documents. What we do measure with our agents is we do comparison between the output that the agent produces and the level of information it's got available to make sure that what the agent is producing is truthful to what it has available. So what we can see here that's a positive is that for the most part the hallucinations are quite low and they're relatively stable, but again it will highlight to us if something needs to be addressed. Then we can see the refusal rate. Now this might be that we've set the parameters for the agent too strict and people want to do more with the agent or it could be people like me trying to get the agent to do things that they're not allowed to like giving themselves a pay increase. Increase. What's really important to Sian's point before around the agents for agent interaction is this is really unique for work that you get full visibility of the handover points between agents. As an end user I won't necessarily pay attention to what the agent to agent interaction is that's happening. We have full explainability from a Workday perspective which is how you can always go back in and see what the for instance SANAA agent handed over to the workday self-service agent, we give you that visibility. But we already know that the expense agent was a bit of a problem so we can see here that one of the problems with the expense agent is actually the handover points. There's quite a high number of agent to agent interactions and they're not always successful. So again it flags the issues for us to address them early on. Engagement engagement is around whether our users are actually taking on the agents because what is the point of making this investment if no one's using it. We've got 76 active agents and we've got more than 70 of our user population actively engaging with these agents. And what's important to note here is they are returning. They're not just using the agent once, they're coming back for multiple interactions with the agents. The adoption box plot that we can see here indicates how quickly people are learning how to use these agents. So within a couple of days people are actually using learning how to use, so the adoption rate is high for agents. They're also able to interact with agents wherever they are actively working we're not limiting them to just a single interface. And just a note that agent system of record is not limited to just Workday natively built agents, we have the ability to track and register partner built agents as well. So in this environment we have agents that have been built by Accenture Deloitte, other partners, you will have the same level of visibility to those agent interactions as well. And running in different environments. So for example, you can use the signer agent builder to build the agents. You can run it in Copilot. You can run it in, in, any platform, AWS, for example. And they all ship natively with the ability to, as part of our agent partner network, they ship natively with the ability to enroll into the agent system of record. Correct. It's about giving you the full visibility of your entire agent workforce. And the business impact is really again whether what we're investing in this area is actually giving us what we want. So you can track your current consumption but it will also give you the ability to predict to make budgeting easier and more trans trans visible? That's not a transponder word. Thank you. And what's also important here is that every process the a [Transcript truncated]