AI Ireland with Mark Kelly
E238 Building Trusted AI at Enterprise Scale with Workday's Graham Abell
18 Jun 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: What was Graham Abell's journey to becoming a VP at Workday?
Having AI be able to kind of infer, kind of make decisions, but apply that in a deterministic way. And so, you know, moving as much of the kind of toil away from people working in the company, taking action on their behalf, but always having human loop, kind of the key decisions being made by humans. We were contributors to the EU AI. We want to make sure it
It does provide protection and that kind of balance with the ability to innovate and drive for business outcomes.
Chapter 2: How has Workday's Dublin team evolved as a major R&D hub?
I don't see AI replacing full jobs, it's replacing parts of jobs and I think therefore the opportunity is how do we help those people do much more valuable work with that time that's freed up.
Hello everyone, it's Mark Kelly here and I am chatting with Graeme Abel, VP of Software Engineering and Site Lead at Workday, where they are leading £175 million investment in their new AI Centre of Excellence, which will be in College Green soon to be. Graeme, thank you very much for joining us on the podcast today.
Thanks for having me, Mark. It's great to be here.
Graeme, before we jump into the work that you and the team are doing at Workday, tell us a little bit of an overview about your road to here.
Chapter 3: What strategies does Workday use to build trusted AI at scale?
I started like you know coming out of college went to Trinity did computer science there I think we were chatting earlier kind of left at a point where there wasn't many jobs for grads and so did a cycle of kind of interviewing trying to get a job with no experience and not being able to get that job so ended up moving to Edinburgh and taking a contract job in test automation essentially and spent the first number of years of my career when I moved back kind of working in that space kind of moving up to being the kind of tech lead for those types of teams and then ultimately into leadership which led me into
leadership of development and product teams and expanding that as I moved into Workday and taking on larger and larger parts of the business.
And when you initially went into Workday you were working as more kind of engineering software engineering kind of or is it kind of directed kind of a product role?
It's probably more of actually looking back on the dev side leading kind of development teams product we're starting a separate function that we kind of paired with and then as I said over like I've been there nearly 10 years now taking on kind of larger roles taking on more of the
Chapter 4: How is AI changing team dynamics and business impact at Workday?
the span and ultimately kind of running in a more kind of gm model i suppose running the product on engineering for what deploying technology is what i'm currently running i bet you in the role you have now having the kind of your hands dirty in those different types of roles over the years probably gives you a good insight probably from the now you've got the acumen from the business side but also you've got that technical chops too
Yeah absolutely I think it's good for being able to be able to ask the questions and know when you're not fully told the truth or when we're in those fire drills when something goes wrong being able to kind of try and rationalise where it's probably happening what's the likely causes because like any system it's massively complex there's all these interdependencies and being able to kind of visualise kind of how the system's working and you know identify where we've probably got challenges it helps us manage the team when we're you know in those crisis moments or
particularly now as we're looking into AI, kind of knowing what we should be building and how we should be building it and making sure the architecture is correct to scale.
Yeah. Tell us a little bit about the Dublin team because people would be surprised at the actual size of it.
Chapter 5: Why is Responsible AI crucial from the beginning of development?
Oh yeah, absolutely. I was surprised when I joined. I didn't really, like, you know, I'd heard of Workday, didn't really understand the kind of size they had and we've grown a lot since then. So, Right now, we're just over 2,200 people in Dublin.
Chapter 6: What leadership qualities are essential in the age of AI?
And another kind of interesting or differentiating factor is we're about 85% products and technology. So kind of R&D function, which for kind of US headquartered companies, quite an unusual blend in Dublin. So we've got about 1,800 kind of development products, UX, et cetera, building core parts for products, leading core parts for product out of Dublin, which is, it's incredible. It's a
pretty significant high investment to have in those roles because you rightly said there's probably usually different types of kind of mix of what they would have.
Chapter 7: How does AI augment jobs and enhance productivity?
Is Ireland or Dublin specifically something that you've just kind of seen that you get really good talent here? Has it been a kind of a key competitive advantage? Because you probably could have done this anywhere around the world.
Yeah, well, I guess it started with the acquisition of an Irish scale-up called Cape Clear, about 18, 20 people at the time. So, you know, two orders of magnitude growth in 15, 16 years.
Chapter 8: What personal experiences does Graham Abell share about using AI?
And I'm sure you've, I think you've talked to some of the kind of regenerators of that, I'm sure. So it started off as a tech acquisition, essentially, right? So that's sort of set the seeds of what ultimately became this large oak tree that we have now in Smithfield and moving to College Green. So we were always really focused on the technology side and workability.
And had like senior folks who became very senior leaders within Workday building that out. So I think, yeah, we had the technical capability. We had access to a great talent pool, both locally and through the universities that we have kind of longstanding partnerships with. Early talent's been massively important to us. And then obviously access to all our European folks as well.
So we've got over 70 nationalities working in Dublin. And so, you know, I think that's been massively important to us as we are a global business, understanding global context, being able to build with kind of empathy for global constraints and kind of legislation and, you know, cultural reference and all the rest of it.
And particularly, I think, as we're moving into this AI era, you know, being able to really understand what the requirements, particularly in EMEA, are as the AI act is coming in. Kind of have lived experience of all of that and building the product to kind of meet that has been kind of key to our differentiation.
Yeah, it's so multifaceted and it's moving at kind of warp speed. What is Workday's AI vision?
Yeah, so I think like as we were kind of chatting earlier, like, we run really important parts of very large businesses and, you know, medium-sized businesses as well. But, like, it's their people, their finance, and their kind of business vision. And so, you know, it can't be probabilistic. It has to be correct. You know, we can't run payroll in a way that's going to be 99% correct.
It has to be correct. And so...
we are really building towards ai on rails essentially so having ai be able to kind of infer kind of make decisions but apply that in a deterministic way and so you know moving as much of the kind of toil away from from people you know working in the company taking action on their behalf but always having human loop kind of the key decisions being made by humans and making sure that anything that's kind of that needs to be deterministic is managing the back end
Yeah. And when you kind of think about AI changing your work and your team's work, how do they use, I suppose, eat their own dog food? What are they doing day to day differently than maybe they would have done three, four years ago, maybe?
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