Video: Welcome to Elevate Online | Duration: 210s | Summary: Introduction session for Elevate Online.
Video: The Agentic AI opportunity: lifting productivity for better economic, business and employee outcomes | Duration: 1360s | Summary: In a business environment where productivity is constraining economic and business growth, we have an unprecedented opportunity to augment employee productivity with digital labor, in the form of AI & Agentic AI. By adopting an AI-mindset, we stand to reap the gains on offer from AI, and avoid the fear-based narratives. Now is the time to prepare your organisation for this seismic workforce shift, examine the reskilling and workforce planning required, and explore how you will take your organisation on the journey.Resources:Ebook: Critical Success Factors to Enterprise AI AdoptionWorkday Blog: 10 Hard Truths About Enterprise AI Adoption
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Video: CFO ADAPT Insights: 3 things top performers do for the most success in AI | Duration: 2245s | Summary: Drawing on ADAPT's recent research on Agentic and GenAI across 800 Australian business leaders, Dr Michael will explore the key factors that contribute to AI success for CFOs. AI is now a strategic priority with 70% of respondents planning to increase their investment, however, only 25% of organisations have automated workflows, highlighting a gap between AI readiness and actual implementation. Learn the 3 things top performers do for AI success, how to track long-term value and ROI, and which internal measures set the leaders apart.Resources: Workday Blog: How AI Is Changing Corporate Finance in 2025Workday Blog: The Agentic Wave: A New Era of Workforce ManagementReport: Global CFO AI Indicator
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Transcript for "Industry Insights - The role of AI in transforming customer experience in Financial Services":
Welcome to Workday Elevate online, and thank you for joining us. I'm Luke Bebbington, and I lead our financial services strategy across Asia Pacific here at Workday. Now the past few years have tested the resilience of financial institutions, Persistent inflation, interest rate volatility, market volatility, evolving regulatory expectations, and an ongoing war for talent have forced firms to adapt at pace. And at the same time, technology, particularly AI, is fundamentally reshaping how organizations function. Workday sits at the intersection of finance, people, and technology. And today, I'm excited to explore how financial institutions are managing risk, modernizing platforms, and using AI as a lever for performance. I'm joined by Brad and James from KPMG who bring a valuable perspective grounded in both global insights and the Australian and New Zealand markets. Brad, James, welcome. Thank you. Thank you, Luke. Now let's get us going. Would you like to briefly introduce yourselves and share a bit about your focus at KPMG? Great. Thank you, Luke. My name is Brad Duffy. I'm a financial services partner at KPMG, and I lead our artificial intelligence services for the financial services sector. So what that means is I get to spend all my time working with our banking, insurance, and asset and wealth management clients to help them scale AI, but also do it in a really safe and responsible way. Awesome. Thank you, Luke. My name is James Mabbit. I'm partner in charge for KPMG Futures, and our role in the firm is to bring to life future technologies and new businesses to accelerate and create a better future for our clients. So we specialize in research, experimentation, and incubation, and AI is one of the technologies we're focused on. Thank you both. Some great experience there. Now before we get started, let's have a little bit of fun. Fun is actually one of our core values here at Workday. So since we're talking a lot about AI, and you both have a lot of experience in that, let's share one of your more fun or unexpected ways that you use AI, whether it's at work or at home. Yeah. Look. I'm really excited about the ability to use AI with my smart devices at home. It's really great to be able to orchestrate my vacuum, my climate control system, so it all knows what I'm gonna do and when. And it's interesting because I think we're now seeing those technologies and those the the those starts at some sorts of smart use cases really entering into the workforce. And I just wish I was having as much fun as Brad. So I I I tend to push the envelope on hallucinations. That's where I like to do it. And particularly at work, I like to look at those hallucinations because the predictive nature of AI, again, maybe that's telling us where the future will go. And in our work, that's what we're trying to understand. So we like to push it hard, see what hallucination comes out of that, and maybe that's where we're gonna focus next in terms of the work we do. Awesome. Thanks both. I love it. The smart home and then also focusing there on actually the hallucinations, as well and the challenges that that brings, with AI. So thanks both for that. So to get us started, KPMG's recently, released a financial services, tech report. And there were three key themes that emerged, from that that report. So if I just call out a couple of the key statistics that I took away from that report. Firstly, in regards to, the complex developments in regards to regulation, 75% of financial services executives have highlighted that complex regulatory environment as a barrier to investment, confidence. And then secondly, 92%, of the organizations are generating profits from AI, which is great to see, but only 30% are seeing returns at scale. And then finally, 58%, of respondents report that flaws in their foundational IT systems are actually disrupting their business on a day to day basis. So a question to you both from this report. What does this actually mean for financial services leaders, and what separates those realizing value from those still stuck in pilot mode? Look. It's a it's a really interesting area to explore. And I think at a very top line, what we're hearing from our financial services clients globally, as well as here in Australia, is that there is a significant amount of investment happening in AI, but the real potential has not yet been reached. And the power of AI is not yet being exhausted. One of the things that we're seeing over the last two years is a real focus on pilots and proof of concepts, and there's now a big push to get those use cases actually into production and realizing a greater level of value. And I think the use case focus is really important. And those organisations who we see as being really successful but also sustainable at scaling their AI programs are those ones who are identifying the use cases that they wanna drive with the benefit profile attached to that and really having a level of energy and passion to get those use cases into production and delivering real value and avoid getting stuck in endless pilots and proofs of concept. Yeah. And I think just building on what, Brad was saying, a couple of things. One, I don't think we should be surprised that people are experimenting still. We're still pretty early actually in some ways. Like, we're two years into the generative AI revolution and and what that means for financial services. So I think, you know, taking a considered approach and looking for validation with customers and inside the organization makes sense. And then to Brad's point, where you find that working is when you've got a real problem you're trying to solve. I think that's the other bit that's important here is focusing on real problems, real use cases, and trying to solve those. That's where we're seeing clients be successful. Absolutely. Yes. And it's really good point to call that. Right? Focusing on those problems, the challenges that you're facing rather than just throwing technology, at everything. Financial services firms are understandably among the most heavily regulated, and that makes trust, governance, and accountability essential as AI adoption grows. We're starting to see new frameworks emerge to support responsible use such as ISO 42,001, the first international standard for AI management systems. In fact, KPMG was one of the first organizations globally to be certified. And Workday is also proud to be among the first enterprise AI platforms to meet the standard. So Brad James, how are leading banks and insurers, investment management firms striking a balance between innovation and control? And what do frameworks like the ISO standard play in building trust, both internally and with regulators? I think, Luke, trust is really important, not only from regulators but also from customers or members as well. And we only need to look at what's going on globally in this really rapidly evolving regulatory space around AI to start to identify some core principles that are really being associated with the use of AI, but the use of AI in a trustworthy and a responsible way. Here in Australia, we have the voluntary AI safety standard. There's acts abroad like the EU AI Act, And we're seeing a number of financial institutions really anchoring their trusted AI programs against many of the principles that are in those key standards or regulations. And then the ISO standards you mentioned is also introducing new considerations. But I think it's really important that financial services organizations are not holding themselves back from their AI programs and waiting for more regulation. There's already a lot of precedents and principles and regulations that we can look to, and we're seeing a number of organizations really accelerating their use cases, but creating trusted AI frameworks and policies and processes that are anchored in what we're seeing both here locally as well as globally. And I think this is a really good point that Brad makes because our research particularly around trust shows that where organizations have in place good governance practices, so the sorts of things that Brad's talking about, the frameworks, identified use cases, policies, guardrails within an organization, coupled with a clear strategy of execution. So knowing where you wanna play and the right sort of cultural settings, and I think this is an important point because regulation in Australia does talk to things like your risk culture. So getting those things right sets you up for success. And that's where the good financial services institutions who are gonna be successful are gonna get things right. Absolutely. And in that trust report that you mentioned there, James, we're talking about it earlier, but there's a big gap, between education, around AI and how to use it responsibly in the workplace, here in Australia versus, overseas. Did you want to just touch a little bit on on that as well? Yeah. That's a good point you make, Luke. The literacy and education side of things is really important. And so those financial services organizations that focus on trying to build literacy amongst their employees are the ones that are also gonna create a better environment to support success because where you've got good literacy, people begin to do things like think critically about the tools they're engaging with. They also understand the limitations and the ways in which those tools operate so they know how to safely use those tools in order to meet the needs of customers. So literacy and education is a really important area to focus alongside those governance and strategy pieces as well. Yeah. Absolutely. And I know at Workday, a big focus of ours is making sure that responsible AI is baked into all the products and features that we deliver so that it's fully, explainable, it's fully auditable, so that organizations can understand, exactly what's going on. So, look, we've seen AI move, at a really fast pace here. It's moved from predictive models, and machine learning to generative AI in a in a very quick, time period. And it feels like we're already, entering a new chapter where GenTec AI and autonomous workflows could fundamentally change how how work is gonna be, is done, again. So could you talk us through how you were seeing financial institutions begin to experiment, with these new advanced forms of AI and maybe touch on some use cases, that that you've seen which are closest to moving from hype to reality. Yeah. Absolutely, Luke. What we're seeing in the financial services sector over time is it's been an area where there's been really early adoption of a lot of new emerging technologies, and we're seeing similar things around the use of AI as well. There are some really great AI use cases here locally as well as globally in the sector across a number of really key areas, across the customer service and customer support functions where we're seeing the ability for AI to better serve customers, but also to identify customers who could be at risk of things like hardship and may need some extra support. In the financial crime and fraud prevention space, there's lots of really good use cases for AI to help support customers who might be, being targeted in fraud and scams and also look at the large volumes of data associated with transactions to identify patterns of fraudulent activity. And then finally, the area that I I think is of most interest to me is around regulatory compliance. We're seeing a significant number of financial services organisations focusing use cases on uplifting their risk, their compliance, and their controls function, and really trying to understand what their compliance obligations are and ensure they have the right controls and compliance coverage over those. And it's really important to know that this doesn't always mean we're going to see the rise of these AI agents or Agintiq AI directly interacting with customers. We're likely to see that, but we're also going to see some use cases where those those agents are augmenting and supporting team members, and providing new insights that team members may not be able to experience. And I think that's where we're gonna see a huge focus in the year ahead is around this agentic AI framework, and and use case structures, where we've got technology which is operating much more autonomously, still, of course, with human oversight and human in the loop for those critical critical moments and critical times, but less of a focus on having to have all of the AI solutions prompted and directed by a team member at all times. Yeah. I think it's really interesting some of those use cases and, particularly, I think the compliance and fraud type spaces because, traditionally, I think applications like those within a financial services organization typically get looked at it as a bit of a cost to serve and there is an efficiency and an efficacy story around the use of AI. But also what we're seeing here is a quality uplift piece as well, so a better outcome too. So I think you can drive both of those outcomes. You can get more efficient and effective in those areas whilst raising the standard of what you're doing in that compliance and fraud detection function too, which I think is fantastic. On the eugenics side, more generally too, I think publicly, you know, it's been well documented in the buy now pay later space for example, the journey that Klarna has been on and what they've done with regards to Agenix AI. And they were quite bullish and out there and saying, you know, we're going to drive very hard at this. Their call center example is one that's been well documented in the public space. But recently, you know, they announced that they're actually gonna have to hire a few more people as well. And so I think to Brad's point that shows the importance of having humans in the loop. It's not like you can take people out of the equation altogether, and I think it's really important to get that balance right between where you apply these technologies, the type of outcome you're trying to achieve, and making sure that you still got people in the loop because you want to make sure ultimately that you're delivering to your customers. Absolutely. That's very consistent with what we hear from our clients as well, where teams are stretched, trying to drive the operational efficiency within the organization, and also to spend more time to actually focusing on the business, helping to drive that business strategy is very much sort of top of mind. And thirdly, talent is always a struggle, trying to find the right talent for the organization, talent that, is continuously evolving as new skills come to the forefront as a result of these, changes, right, in AI that we've talked through as well. I think agents, we're also seeing as a big move, at Workday, particularly as we're seeing, these agents start to actually act and and take those actions, whereas previously, the generative AI was often creating content or summarizing content as well. Here at Workday, we've recently released two agents, that are live. One on the finance side of things in regards to analyzing contracts, redlining those contracts. And then the next stage of that, that we're working on right now is actually document driven accounting, which is really exciting, area, which we don't have time to jump into today. The other area, hide score, is a great use case of agents that are acting out there today with our customers and actually helping drive that recruitment process and onboarding of employees, organizations as well. So it's a really exciting time as we work with organizations to drive organizations forward. Thanks again, Brad and James, for the great discussion. What stood out to me is how most forward looking financial services organizations are juggling three priorities at once, fixing core systems that regularly disrupt operations, navigating increasing regulatory pressure, and still pushing ahead with AI innovation. The fact that only 32% of firms are seeing AI deliver returns at scale really highlights how tough this balance is. But there's clear progress. With standards like ISO 42,001 now in place and AI agents starting to take on practical everyday tasks, the path forward is becoming clearer, one built on strong governance, modern platforms, and enabling teams to focus more on meaningful value adding work. If you'd like more information on the reports discussed in today's conversation, check out the link on your screen now. Thanks again for joining us.