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 "Finance Strategy & Vision: A Practical Look at AI Agents in Finance": Well, welcome, everyone, and thanks for joining us in the finance track. I like to think that we purposefully made it the furthest away because we're all heading into month end, and we need to get our steps up before we get through that large hump. Welcome to the finance breakout where we're going to take some of the concepts that we talked about this morning and really double down around what does that look like for us in the office of the CFO. My name is Esther Monks, and I'm joined by my colleague, Luke Bevington. We're both industry advisers who support the office of the CFO across APAC. We're both chartered accountants. We've implemented ERPs in our careers, and we've been there in the guts of this epic transformation that we've all been leading into. Of course, we've got a range of people in the room from customers and prospective customers. So if you are looking at buying any making any purchasing decisions, both expanding your footprint or joining our community, do so of what's currently available. I think we can all agree that technology changes at a rate of knots. And we have some incredible solution consultants back out in the main expo who can talk you through the details around what's available now and what's available to come. To start off though, I thought we'd just double click a little bit into this whole impact of AI in finance. And if you can or able, just by quick show of hands, who before they walked in today, because I know it's it's come up a lot, but who has had a conversation about AI? Yeah. It's getting a little bit, you know, I wouldn't say boring, but a bit interesting and curious. And I think if we all had a dollar or even a cent for every time we we heard about it, spoke about it, whether it's in our personal lives or with our teams, we would all be very, very rich. But really, that's a symptom of the fact that over a billion people every week engage with generative AI, and it's which means it's the fastest adopted technology in human history. So it's no it's no, surprise that this is, that we're hearing about it, that we're speaking about it, and also that we're sometimes feeling a bit perplexed and confused by it because things are really, really different. So let's look at where finance actually is. Joanne Ruhl talked about this morning a research paper that we've done globally, and she mentioned around things like AI slop. Well, we also commissioned a research paper specifically around ANZ and Agentic AI adoption in finance. And what we saw was that 77% of CFOs are not seeing ROI from AI. Now I wonder whether that's that statistic that Simon talked about where four out of five pilots are failing and we're in this constant cycle of, well, how are we actually gonna move the dial and engage? I also wonder whether it's also a symptom of this historic measure that AI means faster, not necessarily the better outcomes. So there's probably a whole bunch of things that go into this, and I'd love to hear your thoughts and reflections around why AI isn't delivering ROI in your businesses when we after the break. But Luke, what are you seeing more broadly in the region as well? I think it's really interesting. When you talk about ROI, particularly how we measure it as well. Because if you talk to my nine year old daughter, she gets quite a lot of value from ROI. And me as a parent, I do as well actually. In fact, I've gone in a little bit of trouble because because she's my my kids are staying with the grandparents this week, and they had a homework due. They had to do a model. And, they were my kids were born in London. And so I said, hey. Why don't we do the, the Big Ben? And I was in Singapore last week, and I was like, gosh. I forgot to, to do that. So I said, why don't you my daughter's nine years old. She loves technology. So why don't you use AI and see if you can get, it's built a model of Big Ben for you that you can then cut out and fold up? The first results came back. Terrible. But so why don't we think about what we're asking for here? We were doing this on a on a on a FaceTime. Change the prompts a little bit. All of a sudden, believe it or not, we actually got a fully made model of Big Ben produced by, AI, which is pretty cool. So really interesting. I got a lot of ROI off the back of that, but it's a very different environment when it comes to the enterprise, the enterprise side of things. What we are starting to see is that software agents, so the likes of Claude Code and the like, have been hugely popular out there with software developers. If we look at them as sort of the early adopters when it comes to to agents. In fact, they are starting to run into trouble now that they are receiving value from these agents, but they're not necessarily receiving ROIs. They speed through using up all their tokens, like Uber who used up all their tokens in the first four months of the year, having to reset how we're gonna forecast our budget. So really interesting times, lots of value to be had, but still working through the ROI globally. And it's an interesting part that you talk about, you know, what what goes on underneath. Yeah. And and, yes, you say the prompt that created that Big Ben model, I mean, I actually really love to see some of those early results and whether it was actually a human called Big Ben. But we think that 89% of people say that their data isn't ready for AI and to support AI agents. And when we think about that as the foundation, when we think about that as, you know, if you're building a house, you know, we need to get that slab right so that all of these, AI tools can interact and intersect on top of it so that people aren't auditing the results, so they can actually get that base level of trust because of the security, because of the frameworks. What are you saying, Luke, in as well in in the data space? I think when it comes to enterprises, we've now appreciated that data is so critical to making AI work. The reason that a lot of these large language models, hallucinate is because there's multiple versions of truth out there on the world wide web. And as a result, it has to make the best prediction as to what comes next off the back of that. Is when you actually think about what AI is, there's a term that's come out of some of the research, in The US that really behind the scenes, it's actually a large scale statistical pattern matching machine. If you can get that out of your mouth correctly, which I did just say. Did it slowly. But it's basically a pattern matching machine. And in order for a pattern matching machine to be accurate, you really have to get that data quality. So we're starting to see a big emphasis actually on focusing on the data to then get the accuracy from AI and then ultimately turn back to ROI. And at the foundation of all of this, it comes down to capability, right? And when we think about that statistic that's just popped up on the screen, 6% of organizations have mandated AI training. And we think about all the people who stood up in that room or remain standing to say that they're using tools whether they're enterprise approved or not. AI is pervasive across our organization. To have any 6% mandated, and I'm hoping that this number has gone up since the research was conducted at the end of last year, but that feeds into a whole bunch of things. We need to understand a tool to be able to get the best use out of it. We need to understand the tools to be able to think about what's the appropriate way to measure. Going back to your Big Ben example, was the measure the fact that you got DADCRED and could help us sort of circumvent the outcome and get to it quicker than trying to build it from scratch? Was it that it was completed on time? Is it that it was completed remotely? There's so many different ways that you can cut ROI and say understanding it and understanding the way we can use it and and catching that up, becomes really important. I can go deep in the big bin. It put flaps on the inside on the first version. And so my daughter, she's nine, bless her. She cut it out and then realized there's no way to glue to, like, stick it together. So she said, why don't we ask it to flip the flaps on the outside? And then it did it, it did it correctly. So really, really interesting on that. I think it's interesting here in Australia, right, in particular. The Australian public service has actually mandated as of June this year that all public service employees actually have to take, generative AI training. And as well, organizations need to have a chief AI officer. Right? So we're actually seeing the public service actually start to lean into this more. I do imagine that next year, when we hear that 6% number is gonna be a lot higher, there. AI is arguably the biggest opportunity that we have in our careers and our businesses, but it is also the biggest risk, and we need to upskill everyone in the room to to take advantage of that. So let's take a look around maturity. An interesting statistic here is that 86% of organizations are still just exploring. We're at our infancy. I mean, it thinks about agentic AI. That kind of makes sense because twelve months ago, this was a really new topic. Three years ago with when ChatGPT or four years ago now when ChatGPT really hit mainstream, that was when we were really starting to see this emergence. So it's not unsurprising that we have such a large cohort of ANZ organizations still in its infancy. But when you think about your own level of knowledge of artificial intelligence, Maybe by show of hands, who feels like they could confidently explain the difference between sort of traditional machine learning to generative AI and agentic AI? A And the fact is, is that, yes, hopefully, you can. Otherwise, get off. But it's true, right? We are it's changing at such a rate of knots. And so if we can't understand it, if we can't explain it, whether it's to our partner, to our kids, to our colleagues, to our board, how can we then implement it with trust and confidence? But we know that Workday has a whole bunch of finance customers like Anthropics, Salesforce, OpenAI. Their technology company is really leading the way in this AgenTek AI space. But, Luke, how do we see this transition outside of technology companies? It's interesting, isn't it? And this particular survey did call out AgenTek AI. And I think it's worthwhile calling out that the term Agintiq AI only really became mainstream in January 2025. So we're not even eighteen months into a journey of the term actually being widely used, across organizations. So, hence, I'm not surprised that 86% of us, in the ANZ region here are only at the early stages awareness and and exploring where we are with, the agentic side of things. Overseas, look, we've got we've got hubs. Right? Google, DeepMind came out of London. Clearly, San Francisco is a hub for AI now. We're actually I was speaking to a few customers just yesterday, at an event, and we, actually starting to set up hubs in London, Seattle, San Francisco just to be closer to what's going on. It's moving so quickly, and half of it's just educating and then starting to work together as partnerships on this. So early days, but we're starting to see, organizations lean in. The foundation piece is is your core ERP. Right? We talked about the fragmentation of data. And it's not just your ERP, it's that ecosystem that sits around it. I mean, finance information is the output of really rich operational data that's coming from all of your other systems. And so not surprisingly, 14% of organizations have said that they're really they're fully modernized. They're on that journey. They have integrated systems, and that foundation is there and clear. But 57% are only just really starting that journey, and perhaps that's reflective of some of you in the room. I was chatting to a colleague who's visiting over from The US yesterday, and we talked about this. And those organizations that that haven't made the transition yet to a cloud solution, In some ways, some might say, okay, well, it's time for them to sort of get on that journey. There's a risk mitigation now to move to the cloud. But also, we haven't necessarily seen the return from a business case around putting that sexy business case up to the board to say, let's modernize our finance system, and we'll have some real great savings across our organization. But when we think then about this agentic finance future, this is really chart starting to change change the conversation because now no longer is it really a justification around, well, should we host our ERP or our GL on premise or should we, like, host it in the cloud and how do we mitigate risk and drive sort of this incremental efficiency and automation. But now it's really looking at how do we reimagine those business processes that sit across the organization that translate that information from our operational systems to the way that we close our books and drive confidence in our data in the decisions that we're making. Luke, I would love to pass over to you. I don't know if you want to comment on that again or really just start to really deep dive into our product vision. So I think there's an amazing way, an amazing way that we're leaning into and, and get some insights. It is interesting. I'll do a what I'll do is I'll do a call out, to the customer conversation that we've got later today. Salesforce Laura has, joined us here to talk through the Salesforce implementation. I think one of the biggest things I'd call out is that in the age of big data and cloud, you can move so much faster than you ever could. You know, sneak peek with Salesforce, 44 countries. They had over 400 integrations, half a million customers, active customers that they migrated, big bang, within two years. You know, Anthropic just went live on Webday Finance less than nine months start to finish. So the the the traditional career defining move of ERPs has really changed, in this modern environment. So quite exciting, but hear more, at the Salesforce session, later today. So, Luke, why don't you take us through what is that product vision and and how's it, turning up for us at Workday? Thank you, Esther. So that set the scene with some of the where we are in the AMZ environment. I want to take you through how we're thinking about AI, here at Workday. And just before I crack on with, where we see this going, I wanted to call out just how fast this, pace, we're moving. So for those of you who know Claude bought or it was renamed OpenClaw, ability to build your own, agent, that was released in January this year. And that grew to 3,200,000 active users within the first three months of the year. There was also an organization called MoltBook that was created at the end of January off the back of OpenClaw agents. First week, they had 1,600,000 agents on that platform. And think about that for those that are not familiar with mold book. That's like social media for agents. Agents can talk. Humans are not allowed. Wrap your head around that. And then wrap your head around that Meta or Facebook has now acquired, Motebook. It's a wild world, that we live in. And in Claude, their revenue surged 9,000,000,000 run rates in January, through to a sorry. 9,000,000,000 run rates in January through to 30,000,000,000 at the end of April as we've seen the uptick in organizations and employees using AI. So it's a fast moving world. So this product vision does change, believe it or not, but let's talk you through it. Okay. So when we look at AgenTek finance, what we're actually trying to achieve within finance hasn't changed when it comes to AI, and I think it's worthwhile pausing on that. Right? What are we actually trying to do as a finance function here? Fundamentally, we want to work with our business to make better decisions, get better insights from our data, and look to where we're going, forward. We want to be more productive with our time. I spent about six years of my career running finance operations. I think 60% to 70% of a finance function can be spent just preparing the numbers, bringing in the data, cleansing the data. So we really want to drive that productivity so we can spend more time working with the business on driving that growth. And then finally, greater confidence. If you really boil it down, it's what we do in finance. It's risk versus reward. How do we allocate the capital within our organization to get the reward as well? So we want to continue to ensure that we are managing the risk as well. And as we heard on the main stage today, these large language models are incredibly powerful. Their context windows are getting larger, and it feels like they know almost everything. But the reality is they don't know your organization or at least I really hope they don't have the data on your organization. The reality is they've not been trained on general digital data, on manual journals, on your operational data. So if you're trying to talk to an agent and understand if you've got any anonymous journal postings or where your business is going. It's gonna really struggle to give you accurate, and reliable results. So in order to guarantee accuracy, this is where we refer to ERPs like Workday as the deterministic platform where you've got precise and predictable elements going on, which is very different from our probabilistic AI that we have, that large scale predictive matching machine that we have there. It's gonna give you the best answer that it thinks is correct based on the data that it has. I was speaking at the Elevate version of this in Singapore last week, and Binance was on stage. And, they're doing some really cool things, with agents and the like out there. But they put a quote up, which I think, on screen, which really sort of summarize the state that we are. And that was SaaS is the savior for AI, which I thought was a a bit of a laugh, in the current environment. But the point was you can do some amazing things in AI. But once you get there, you need to then come into the deterministic engine. You need those accounting rules. You need the audit trails. You need the safeguards and guardrails that you have, in your ERP environment. So let me talk you through how this works and where AI actually sits on the platform. So at the foundation, nothing has actually changed at Workday. We're very fortunate with the vision that our founders had where we built a unified data platform at the bottom. The governance, the compliance, security, audit trail, all of that good stuff in a post Sarbanes Oxley world that's baked into our core cannot be turned off. Hopefully, everyone in this room is very familiar with our financials solution. You may have heard we also do an HR product as well. We also have some industry solutions, like students, across the across the room there. So we've got our products that sit on top of our unified data core. Now I do geek out on this. The data cloud, I think, is super exciting. Those next door in the technology track are gonna be hearing more about that. One of our great customers, Netflix, actually created this concept called Apache Iceberg, Zero Copy Data. We don't have time to go in that today, but it's pretty game changing as to how you manage your data within an organization. No longer having to to copy all your data to the various data lakes you have in your organization. So we've partnered with Snowflake, Salesforce, Google Cloud, Databricks, for our first release. More to come on that. Really, really exciting. And we also, in the technology room, will be talking about Workday build. You can build on our platform as well for those unique use cases to your organization. But then what you see up in the top is really where the Agintiq revolution has taken Workday. So we have Sana agents and hopefully you, understood Sana is effectively our name for AI now at Workday through an acquisition that we made last year. So we're providing our Sana agents, our Workday agents, to our customers, and we're gonna jump into those in a minute and actually show you practically what they are. Within working with our partners, we're partnered with the likes of Microsoft, Google, Accenture, KPMG, etcetera, building agents on our platform as well. We also give you the ability to build agents, on our platform, which I think is super exciting. And when we come back next year, I'm hoping to see many of the agents that people in this room have built. And then at the top, we're doing giving a complete refresh to the user experience on Workday as well as through the Sana acquisition. And that comes with a whole lot of connectors, built in well to help you in the job that you're doing, whether it's connecting to your email, Google Drive, Teams, Jira, depending on your job. Really, really exciting as to how this, is moving forward. Okay. So you can think about the world that we're now living in as effectively a superintelligence. We've got these helpers that are helping us do our day to day jobs. So at Workday, we're very thoughtful, about AI. We're not just building agents for the sake of building agents there. So we've got AI built into the core as Esther alluded to before. In some cases, it's the machine learning that we're using for, like, work tag recommendations. In other case, it's an agent. In some cases, it's gonna be generative AI. So we're very thoughtful as to how we do it. Agents are not the answer to everything in the world. We've talked a lot about data. We're gonna hear more about data as well, Fundamental to get the foundation correct in your organization. We're built for change. So we're in a low code, no code environment. I think finance professionals in particular are very well suited for this age that we're moving into. When you're in a low code, no code, think of it like building a complex model in Excel. So I expect finance to be taking the charge, some extent from our technology counterparts as we move forward into the future. And then finally, this is a bit of a change for Workday. We've really opened up our platform. There are two key words, MCP and ATA. If you haven't heard those yet, go use your large language model of choice to delve into them. The very simple answer is MCP is the integration to an agent, and agent to agent is simple agent to agent talking. So an example would be if you use Salesforce as your CRM, you have an agent over there talking to a Workday agent. So the financial analysis asks for some customer information on the customer. The Workday financial analysis agent goes off, has a chat to the Salesforce agent, gets the information about the customer, the background, the interactions, and then brings that back, into the Workday environment. So really exciting and as a result, very much opening up the platform to connect those various agents that you have within your organization. Final slide I want to touch on in regards to our vision for Workday, and this is what does AgenTic finance actually mean. The more time you spend playing around with agents and the like, you will see that it's like having additional teammates. And all of a sudden, you're gonna be starting to orchestrate these new new teammates. Imagine if your boss said, hey, I'm gonna give you three additional headcount. What would you do with that? For example, you might have now an agent that autonomously watches the general ledger. Maybe it's gonna start booking things on a daily basis so that you can get a daily view of where your business is going. Planning that adapts daily. I've seen some really interesting ones going out and looking at competitor information, having a look at Reddit. What's the feedback that we're getting for our particular product? Bringing that back. Do we need to adapt our business, take it in a different direction? Spends govern in real time, seeing what's going on in the organization. So much possibilities. And all of a sudden, you're gonna be managing these agents that are doing this within your organization. Not too different to how you manage, people. So with that, bring Esther back on stage. And, another one of our great customers in Singapore was DBS Bank, actually, Esther. And, I told him I was gonna steal, the slogan they had on their t shirts. And that was at a senior management conference, and they all turned up, to the conference. And they said, talk is cheap. Show me your agent. So I I think that's a good good segue, Luke. It's I think it's time to show the audience how how this all turns up. But, I mean, there's there's so much that we can talk about when it comes to AgenTic AI. And so I think that framing that you had at the start around what is it that we actually do in finance is a great place to start. So better decisions. How do we surface the insights that matter? I mean, I grew up after order, cut my teeth in commercial finance for a while. And there were so many times where I'd be sitting there with my stakeholder, with my PowerPoint deck that I copied and pasted across, and maybe I had some drivers around volume versus yield or retention rates or whatever it might be, occupancy depending on the industry that that I've worked in. And they went into that question. Oh, yeah. But okay. But but what about this and what about that? And it'll always be that point where no matter if I had my PowerPoint presentation with my supporting Excel spreadsheet or my Power BI spreadsheet or my Power BI dashboard, I'd always get to that point where I had to say, I'll need to look into that. I'll get back to you. We always are needing to get back to people, like, be that bottleneck. So how are we actually helping people to drive better decisions through Agenctic AI? Absolutely. I'm sure that's a pain point we can all relate to, in this room. So I'm gonna talk you through two of the agents, that we're currently with early adopters at at the moment, to go in towards generally availability at the end of the year. So the first one I want to show you is our financial analysis agent, and this helps exactly in the situation that you talked about yesterday. We're trying to do some analysis, on your numbers. And we're gonna delve into a global company here, to have a look what's going on, some of the costs that we have in the business, what's driving that impact, and then ultimately what action, can we take off the back of that. You'll see here as well, we have the ability to attach. For those of you who are familiar with Clore, they have a concept called skills. There's always unique context to your business, your industry, your product line. So you have the ability, to attach, these skills in this concept here. And in this case, it's some of the flux trends that we have in our business, the seasonality change. So we're giving it some context so that it knows what to look for here. So in this case, we're gonna jump in here. We're going to, load in our Fox analysis, and I'm gonna say, hey. Right. Let's let's have a look and see what's going on, with our organization. You can think of this like chat gbt built on into Workday here. So you can see quite quickly, it's had a look and it's saying, hey. Look. There is something that looks a little bit odd, and that's our freight charges that we have here. So it's flagged that for us. So let's drill into our freight charges and see what's actually going on, in here. Straight away, we can see it's rendered some charts for us in real time. We can see that the Midwest is having a few challenges, for us there. 25 increase, in rates that's happening. You can see Workday accounting center for those that you're familiar. We have some of our operational data in here, so we can really get down to the detail. So now we can see what's going on within our organization, and I love the sort of the visual charts along with the text telling us, what is going on here. We can then create an executive summary. The lovely waterfall charts for those of you that are experts in Excel is becoming a lot easier, to create. And so then it's given us a few actions there for those of you that can read fast. Do we want to renegotiate our contracts for freight charges? Do we want to start to use some additional, freight organizations as well to build out? It's now moved into our planning module. We're now starting to forecast the different variances based on whether or not we go and, get some new vendors there to help reduce the freight charges in the Midwest. And we can see we've now pushed that through and we said, hey. Yes. What we're gonna do is we're gonna do dual source freight charges. Can you find it off now and, get approval for that to update our financial forecast? And you see that's just one example of all the projects that we're working on here as we orchestrate, the agents as we do our financial analysis. This one, we're doing a productivity, analysis here, seeing what's going on in the business. Do we need to adjust the headcount that we have in our organization? And again, you have the ability to take the action to actually raise that headcount request, removing that sort of duplication that I always had, where our finance team had one version of the open headcount and, the business had a very different version. I think the other part that that really brings to light is that multidimensionality that we're always grappling with. There's only so much dimensionality that you can extract through an awesome pivot table or through your fixed accounting code. And so what this has done is it's not just taken us from that initial question, but it's taken us on that journey of all the things that go on in your head or your stakeholders' head around, yeah, but so what? So what can I do with that? And I love that rich dimensionality that it's dying to bring. It really looks at organizations, not in a flat linear model, but really that cube and dimensionality. Yeah. Absolutely. You can see how powerful it is to do this analysis, with the business there. So super exciting. That's on its way. Another one that I just wanted to cut, was the cost and profitability analysis. So again, starting to think about how do we actually manage the profitability, the margins within our, organization. So this I've used an example of a bank here and effectively understanding these key drivers of your business. So in this case, net interest income, efficiency ratio, and the like are critical for a bank to understand how your business is performing. So we're building this out by industry, by sub industry to make it's very tailored to your organization. You will then have the ability to to customize this, for your sort of KPIs and the like that you have within your organization. But when you're doing this, there's often costs that need to be allocated. So you might look at it by line of business, by cost time. If we jump in here and have a look at our, by products and here we can see our consumer banking, consumer banking, etcetera. We have to take those costs and allocate those out across those various product lines. It could be business lines as well. So you may have seen the old, ask Workday, on your current Workday tenants for those that are that are customers. So we can then jump in here, and we can start to have a conversation with our agent. So we can ask here around, hey. I'm looking to revise the the cost allocation that we currently have going. Can you help me? And let's see what this is gonna look like. So it's gonna come back and say, great. Yes. I can help you with that. But it needs, again, some more of this context. So what are your accounts, what are your cost allocation rules? And best case, can you provide an example as to what you're after here? So we can upload this. We're now giving the agent the context that it needs in order to understand what we're asking for in the calculation. And then comes back and gives us, hey. This is what the allocation, is gonna be. Do you want me to roll push this out, into your organization? You confirm that. It's then gonna go off to approval, for an organization, and then your dashboard is updated. So really powerful. This is a banking example. You could use it for your, you know, global tax transfer pricing, many, many different use cases and trying to understand the profitability within your organization. I was only just thinking, I I support a lot of our for purpose organizations, the mission based organizations. And Aged Care, you don't have to look too far in the news to say that they've gone through huge regulatory changes. And even just thinking about like what finance folks deal with on a day to day basis, we're always adjusting and changing. So the ability not just to have that static interrogation or the way that we intersect through that example of the model that you uploaded, but then to be able to do scenario analysis off the back of that and pivot to how businesses are changing day to day is just incredible. And I think the other part that this really shows is that democratization of commercial decision making. It's not just now finance that are the custodians of all of this rich information. How you then work with your stakeholders and really lift the level of discussion that we're having in our organizations around margins, around financial sustainability. It's powerful when you can sort of overlay that probabilistic conversational element that the billion people that are interacting with AI every week are using, grounded in that deterministic element of looking at your single source of truth that is your finance data. It really, I think, changes the conversation in a really positive way. It does. And on that trend of the probabilistic element, you've gone out, you've done all this analysis, you've been firing it back to the deterministic world. And I think that's where the agenda piece becomes really powerful, being able to take that action. So you go, great. I've done that analysis. I've looked at that. I now want to lock in this new cost allocation. I'm gonna send it off for approval, and it just flows directly back in. So there's none of this, hey, we agreed to something over here, but what actually happened? Did anyone actually record that? So the second pillar that we talked about is around productivity. And I don't know whether and I'm sure looking at the people in this room, I'm not unique in, you know, wanting to have made myself or at least what I do redundant in every role. I've wanted to always make sure that the processes that we were doing were becoming more efficient. And, you know, I often worked in organizations where they encourage that innovation so long as it could be done in Excel. But so how so how are organizations really starting to lift up above that, you know, removing a couple of clicks from here or there into really changing the way that finance is operating to become more productive? Yes. A place close to my heart. So I'm gonna give you an example here, revenue contract agent. You can think of this a bit like document driven, accounting. So large language models are very good at that. They're very good at understanding language. So for organizations that have contracts, order forms that are sent out to customers, master service agreements, and the like, the ability to be able to read that contract, come away with the key information in that probabilistic world, and then bring that back and match that up to the deterministic nature that we need. So what was the amount? What was the date? Effective date, etcetera. So in this case, let's have a look what we've got here. So in this revenue contract agent, we do rental properties here. We can see, the documents that we've got here ready for review to send out to our customers. So we can see the rental order form here. Great. We're all used to seeing these documents. We can then ask some questions. What's the effective date? Start to understand what's going on, with this contract here. And you'll see how it links it back to the Workday system that we know, the exact amounts, the dates, side by side to really give you that clear traceability as to what's going on there. It's linked because you've got your contract management there to your master services agreements. In this case, it's identified some rebates that because of the volumes that had gone through that we need to update the customer invoice for to make sure that we're billing them accurately. So we can do that, update it, and send it all out. So again, you've got this really powerful interaction between these large language models built into the platform for the ability then to take action. It becomes a really important point because we talk about this whole redesign of work and redesign of skills. I think about the accounts payable teams that I've led over the years. There was so much excitement when we could just match transactions faster and make sure that we're having those up to date vendor records or customer records. What I think this does is then shifts that time to say, okay, we're doing that matching more quickly. So what? So how are we adding value to the organization? How are we uplifting or leveling up the almost the contribution that they can make? What this starts to show is that other work that those teams can be working on, they can be reviewing those vendor contracts, looking at forward looking purchase orders and starting to say, oh, great. Well, actually based on our current volumes, let's think about it. And they don't necessarily have to come up with the answer themselves, but they can have these conversations and interact and have that curiosity to then start to look at where we can drive value and savings for the business and drive that productivity. What else have we got? Absolutely. And so then if we flip that on its head, we've then got the supplier contract agent as well. So operates in a very similar way that it can review all of the contracts. It can look both historically, but then also, with your procurement team looking forward as you're reviewing new contracts that are coming in the door, making sure that you've got terms that align towards, you're after and that it's what you agreed on the financial side of things as well. So again, can start to add, a huge amount of value here. And we've actually found internally at Workday, our procurement team and our legal team working hand in hand have saved huge number of hours in regards to reviewing the many, many contracts that we have across the globe, with our suppliers as well. And I I think it's really interesting. Like, the use cases here are quite endless. Past life, investment management, we always had rebates and commissions locked down in these contracts, safe down on a file. And it was always a nightmare when every now and then it would come out of the woodwork that that contract that was signed seven years ago, turns out we weren't quite in compliance and it was a mad rush to find the the contract and then go back and recalculate. So the power now with these large language models built on top of your contract intelligence, you can now go back and you can do that scan to make sure that you aren't caught in that situation that we've all been before where you realized you've been accounting for something, incorrectly. Well, my favorite is when, when you wanna renegotiate that contract and it turns out the, the renewal dates already just passed or because we didn't have the visibility. So how you actually get that visibility across these documents that hold so much rich data locked up in ivory towers almost or filing cabinets is incredible. Let's take it through that last pillar around greater confidence. I don't know, just asking for a friend, if anyone else has been in this situation, but you sent the flash on year end to your executive team. Your investor relations team are super excited because revenue growth, whatever that really critical margin is, it's rounding to that double digit. It's rounding to 10% only to get through to your reconciliations on, you know, workday four, five, six, seven, material adjustment that needs to be posted. You know it needs to go through because those auditors are going to pick it up. But now the impact is that 9.55 is a 9.3, and it's going down that way. So but what this drives is it's this idea of confidence. How do we how do we drive confidence in the numbers? How do we get insights faster? How do we make sure that whole idea of lights out finance that you talked about, how does that come to life? Absolutely. And I'm sure there's a lot of ex auditors. I know both of us, it just started our career, one of the big four as an as a as an auditor. So it's something that I'm sure is close to a lot of our hearts. I'm gonna touch on two things that we're working on here. Firstly, reconciliations. I often think of finance as bit of a giant Sudoku, particularly at month end, quarter end. We were trying to make sure all the numbers line up and that we're comfortable with what's going on, out there. So what we've got is we've been doing a lot of work on our closing consolidation hub and reconciliations and the certifications that we have here. So let me talk you through what, what this is doing here. So we have, the hub, and you can see here the reconciliation status, really clear view as to where we are at month end right now, those reconciliations. And you can see it's also approved. It's also reconciled a lot of our, monthly reconciliations as well. Because in a lot of cases, you can now do this automatically, with an agent when you go to reconcile reports and the like and check for anomalies. In this case, we've seen two have been also prepared, but they've been flagged for us. So if we go in and we have a look, we can see there the two that have been flagged in Amber for us to take a look at. If we open that up, we can see that it's in regards to our AP aging account. So we can see it's given us some natural language there in regards to what's going on. We can see our AP aging account. And whilst it all reconciles, the balance technically, is correct. We have an item that is now sitting in an aged bucket. And as a result, we should probably take some action on that to understand what is going on. So we can, raise a, a notification internally, send a message off to the team to understand what's going on. Is this correct or actually should we get this paid? We don't wanna be popping up on the report that we're not being paying our suppliers on time. So we can notify that again. Key difference, you can now take actions on the platform to chase this up. I know that was something I struggled with with some of my employees that reconciled a balance, but but hadn't done that thought process. Well, why is that item sitting in that age bucket? And, just because it reconciles doesn't mean no action is required. My favorite was always when you you clicked on the link through and it was to a previous month's file. And so the link wouldn't actually take you through to the supporting documentation. So having it live and in the system is incredible. Absolutely. So really cool. This is going to help speed up, that close process for all of us here. And then on that audit point, so audit's huge. I don't think I've ever met an executive who doesn't get a little bit nervous when they look, either yourselves as your financial controller, head of FP and A, head of tax, who whatever your role, are you comfortable that these numbers are good? I have to sign here. We're seeing more and more accountability, come onto the executives as well. So this is a big focus for us to really build out our audit, ability on Workday. I'm gonna just talk you through a couple of things that we're working on because our wider audit strategy here has a bit going on. One, we're gonna talk through some of the order agents working in the background in regards to identifying risks in real time, the ability to build your own order agents, believe it or not. Not sure if that was on anyone's bingo card, for today. And then also how to handle those audit requests. I've been on both sides now of, being the auditor asking for all the information from the finance team and also having to prepare that. So let's have a look at what is actually going on here on our, audit hub. So we go into our financial test suite. It gives you a nice kind of scoreboard as to what's going on in your organization, where you're sitting, and then highlights where you have potential issues within your organization. In this case, it's highlighted in the procure to pay function. Looks like there might be two invoices in there that are duplicates. And we click into that, we can see, the detail that is going on here. And we'll be able to see that the invoice numbers themselves differ, but the amounts and the dates are very, very similar, something that we should probably, look into. You can see the three that is flagged for us there. Again, we've got all the supplier data, so we can then raise a email notification off to the suppliers with the details. Can you please check that these invoices are actually accurate? So that's just one. What you're seeing here is the marketplace of all the agents that we have. So Workday, we're delivering a number of these agents. We're also working with partners. KPMG was, our design partner on this, searching for those unrecorded liabilities and the like. Your internal audit team has the ability to come in here, turn these on and off. As I said, we're also giving you the ability to build your own internal audit tools here as well to give you that comfort. Every organization has their risks, their unique challenges. I can relate to this example, transaction currencies. For any of you who have operation multiple countries, you have certain countries that'll be more problematic in regards to getting their postings accurate. So you can be quite specific here. Which companies do I want this to look at? Maybe call out some currencies. What am I expecting? I can then have this agent operate in real time behind the scenes identifying any potential issues, that would raise. The agent here will give you recommendations when you're setting this up as well as it continues to learn your particular organization and where issues have arise risen in the past. And then the final part I wanted to cover is audit requests. So we all receive audit requests, from our external auditors. Right? Could be internal as well. So we can come in here and we can add in what is that request that we've been asked for. Are they taking a controls approach, a substantive approach? I want to see these invoices, these contracts. You put this in here. It's then gonna say, okay. These are the sample that you're after. Have I understood what you've asked for here correctly? If we click accept, that's then gonna go down and say, okay. What are the parameters that we're after? Let's just validate. Is it these companies? Who in our organization is gonna be responsible? We always need a human in the loop, which you'll see is consistent throughout all the examples that we have shown you here. So once you've validated that you've got the the fields correct for your organization, we can then proceed. Because it's all on the one platform, it can now pull out those invoices, the PDFs, the original contracts that you have, and that now is in a place that you can pass that on to your auditors to then review that information. So So here, it's taking away a lot of the pain that we have when we have to go and find all this information. I still remember getting the physical invoices and the like, putting it together in a file for the auditors. So very much looking to drive efficiencies here whilst also, improving the comfort that organizations have. I think what you've also articulated is just this idea that you mentioned before, you know, who would say yes to a couple of extra headcount. Right? I think most of us would. But this is really around looking at shifting the design of how we work. So we're embedding that digital workforce in these elements, for in this example, like that peak period of audits of audit season where we're responding to audit queries or as you say, we can embed it in our day to day, which is then freeing up your people to do the really business focused impactful work. This piece around ROI, though, I want to circle back to it because we talked at the start around 77% of CFOs not seeing the value. On our recent investor relations call, our one of the analysts talked about it. How long does it take for these agentic AI features to start to deliver value to organizations? And because of the model, because it's not looking at that machine learning element of the AI sort of suite of solutions, it starts to become really immediate. And I welcome you to have a conversation with the teams out on the floor to deep dive into any of these in more detail. But this is stuff that's really driving results, for our organizations and that are doing the early adopter program now. Luke, anything else that you wanted to touch on or talk about when it comes to this ROI? Yeah. And I think it's important as I kinda started the session about saying how quickly this has all moved. Right? It's still very early days. So there's two keywords up on the top of the ROI slide that we have there, and that is early adopters. So at Workday, we're not rushing out hundreds of agents to sort of throw those out there and the like. So we're very thoughtful about what agents we build. We make sure that they value it them that they're providing value to our customers and getting that really early feedback. So it's been very exciting working with our early adopters who are further ahead on their journey, than others. And so Planning Agent has been hugely popular. I think that's in part because you can put it alongside [Transcript truncated]