AI Agents for JD Edwards: Who Owns the Digital Worker?

This episode explores how AI agents are evolving from software tools into digital workers that operate across business processes, systems, and applications. Kevin Van Horn discusses what this shift means for organizations, including how to approach ownership, security, permissions, autonomy, governance, and accountability as digital workers become part of the enterprise workforce.

What happens when your next employee isn't a person and doesn't work inside just one application? If an AI agent works across JD Edwards CRM, e-mail, spreadsheets and documents, who actually owns it?

Today, we're looking at AI agents as digital workers performing business processes across the enterprise. By the end, you'll have a clearer framework for deciding what they should do, how they should be secured, who should own them, and how to govern them.

Welcome back to Not Your Grandpa's JD Edwards. I'm your host, Nate Bushfield. Now, most companies still think about AI in terms of applications of JD agent to CRM agents and an e-mail assistant. But people don't work that way.

Someone in accounts receivable might use JD Edwards CRM, e-mail, documents, and even spreadsheets just to complete one singular process. So if an AI agent starts doing that work, does it really belong to 1 application or does it belong to the business process? And if we're creating digital workers that operate across the enterprise, who really owns them? What are they allowed to do? How do we secure them and how do we keep that environment under control as it grows?

Joining me today is Kevin Van Horn, managing director of AI Advisory at ERP Suites, to help us unpack this. Kevin, how are you doing today? And for the viewers at home that maybe haven't seen you before, can you give a little background?

Sure. Yeah. Hey, it was great to have me back. I appreciate it. Nate, it was good to see you. Yeah, it's, this will be my third one, my third podcast, so I'm excited about it. But yeah, I'm going a little bit more casual today, end of the summer. We're having a great day up here in New Hampshire.

So, yeah, my background is I, I was presenting to a user group the other day and, and this is my 36th year being involved in JD Edwards and JD Edwards related stuff, right. So started as a customer in 1990. But you know, you know, and I went along to, you know, through the Oracle acquisition, led the the JD Edwards solution consulting organization for 10 plus years and, you know, have a background more on the project side of the business.

And, and I'm just been thrilled to be part of the ERP suites family for the last, you know, six or seven months now and love doing the podcast. So I can't wait to chat about the subject. It's near and dear to my heart.

Yeah. And of course, we enjoy having you on because you really are the forefront of a lot of this AI talk that we have in this industry and across AI agents and digital workers throughout this space and throughout the entirety of what AI truly is today.

Now, it's always funny when someone says that to me because, you know, I'm sitting here, right, 26 years old, about to be 27 at the end of the month, though. So now I can't really set up for too long.

Happy birthday.

Happy birthday.

Yeah, I appreciate it. I appreciate it. But it really does put things into perspective as somebody who kind of grew up with technology at his fingertips. And AI really isn't that scary to me just because it's that next step of technology evolution.

And when we're talking about that technology evolution, like should companies really think about AI agents as software tools where it has been in the past, like with digital assistants or more as digital workers performing business processes?

Yeah, Yeah, that's a, that's a great question too. And it's a, it really kind of drives down to the heart of this whole question, right. And if, if I think about it, if I sit back and think about it, you know, the, the honest answer is probably neither is, is perfectly right. You know what I mean?

You know, 'cause whatever you label the IT as kind of determines everything after you know what I mean, then that that's the that's the problem, right? If you think of these AI agents as a software, a piece of a code, a piece, a, a, a tool, the way you buy it and then use it is you follow that traditional software evaluation pair.

You know the process, right? Does it have the features you want? What's the license? Does it work great? And then kind of you stop, right? Because that's what software is supposed to do, right? It's supposed to have a beginning and an end. And you know everything that happens in between, right?

You feel comfortable and confident that when you put in an AP invoice into JD Edwards, it's going to create a 411 record and you know it's going to go into this stat. You know, you know the process, right?

If you call it a digital worker, then you have to really answer a different set of questions, right? You know, you got to answer like, OK, it's a digital worker. What's its job description, right? You know, like, like, I mean, you wouldn't hire a human worker, right, for a job without a job description, right?

You know, so it's like, so you know, let's call it a digital worker then. So what's the job? What do you, what is it trying to accomplish, right? Who's the manager, right? Like you don't wouldn't hire somebody just being like, Oh yeah, you're, you're on your own, you're out there, right? You report to no one, right? That kind of thing, right.

And then, you know, the last question is what is it allowed to do, right? You know, what kind of decisions is it allowed to make, right? So, so going back to your question, right, which was the important one and the good one? It's like, you know, how would I answer that question?

I, I think then digital worker is the more useful way to look at these AI agents, right? Not because not, you know, no one's pretending that a digital worker is a person, right? I mean, but that's, that's why we call it a digital worker, right? You know, that's why we call that.

But because those questions that it forces you to answer, right, are the ones that actually matter and the ones that will actually ensure success and or failure, if you know what I mean, like if you don't answer them correctly.

So it's like, you know, because you know, quite frankly, if you, if you think of it as a tool, then then you're thinking about an agent, a very narrow view, right? And, and you're probably just going to have an an agent that's kind of expensive that just does what the ERP applications already do, right.

When you think of it as a digital worker and think of it as a job with a person that manages it with autonomy to perform actions, then you really start at answering or asking the right questions. Is that fair?

Yeah, exactly it. It's kind of like I, I don't know if you caught the Apple event and they were talking about their new Airpods, their new devices, everything that's coming out. And the Airpods one are, is the main one that really stuck out to me because I've always used it as a way to talk to people or a way to listen to music, listen to podcasts, listen to audio books, that type of stuff, right?

There are features that are within the Airpods that turn it from, all right, this is a very expensive listening device to, oh, I can actually translate a conversation through my Airpods and it will tell me in English what this person is saying.

She's amazing, right?

It's incredible. And it's that same idea of I put these things into that specific box, into that specific application, think that it can only do this one thing. Well, that's not the case at all. It just depends on your perspective, right? So really should, right, sorry, go ahead.

Well, no, no, as you were looking at the Airpods as a tool, right? You know, you weren't looking at your Airpods as your communication worker, right? For you, right? I mean, you did, you never thought in a million years that your Airpods were actually an interpreter for you, right?

And even if you got into that situation where somebody was trying to communicate with you in a different language, you probably wouldn't even have thought about it, right? And, and like, oh, my, my, my Airpods can do that, right? I can, I can understand this person.

So now hopefully going forward, you'll reframe how you think about your Airpods, right? And think about the what job is it trying to do for me? That's what we're saying here.

Yeah, agreed on.

Organizing Digital Workers Around Business Processes, Not Applications

So should companies still organize Asians digital workers around an application or should it be around an entire business process?

Oh, wow. Yeah. I mean, yeah, not an application. It's not an application at all, right?

You know, and, and it's interesting because we'd like, you know, even us at ERP suites, we like to say, hey, we're building agents for JD Edwards, right? Well, part, part of that's true, right? I mean, we're, we're building agents for companies in the JD Edwards ecosystem, right? We're, we're not, we're not building, you know, necessarily building agents for JD Edwards.

All right, so, and I'll even take that further, right. You know, you, you organize an agent around an application. And this is kind of what we were just talking about, particularly around your Airpods. I mean, you create that exact silo of what that application does and what people have been complaining about for the as long as they've used that application.

It doesn't do this or I've got to do this from this Excel spreadsheet, or I get this invoice in and I've got to manually type it in, right? So if you build it around an application, you're just, you're framing it to what that application does, right?

You know, think about, you know, you know, think, think about an AR clerk in an organization, you know, and to and to work on, say a past due invoice, they've got to go to JD Edwards, right? And they look at an, an AR aging report, right? And try to, oh, this is this one's the problem, right?

And then they go to CRM and try to figure out, well, who's the owner and kind of what was the, what caused this? You know what I mean? And then, and then they do some type of e-mail communication or phone calls of, Hey, how do we fix this problem, right?

You know, And then she goes in or he or she goes into SharePoint to try to find, you know, AAPO or, you know, a proof of delivery and, and then she jumps into a spreadsheet to update something, Right.

Well, that's the process, right? You know what I mean? JD Edwards was only the first little thing they did right there, right? They, they went in and looked at an aging report, but then they went to CRM, they went to spreadsheets, they went to documents, they did emails. They did all that, right?

JD Edwards is one piece of it, right? An important piece, but it's one piece, right? Yeah, it's kind of the easiest piece, right, You know what I mean? And and not trying to be a, you know, flip about it, but it's kind of the piece that's in there kind of works.

But the hard part is, you know how how do you get all that data and information and how does it interact and how do you make good decisions based upon that data, right.

So, so trying to build an agent around AJ Theatre's application is, is, is trying to build an agent around something that you know, the easy part of the process, right, not necessarily the challenge in part of the process.

And then you don't necessarily get the return, right. You know, it, It's fine if you're trying to do something like a digital assistant where you say, what's the status of this order or, or you know, what's the account balance of this? And it just comes back and gives you a figure, right?

You know, really the value is how does that agent work and support that process, right? To make it more effective, more efficient, less manual, more accurate, you know, less error prone, all those things, right?

So it's these agents are incredible because they work in that area around JD Edwards to help make decisions, but also can then just go right into JD Edwards itself and make those updates that you want it to and, you know, eliminate a lot of that manual process.

So do you think that it's maybe like in a naming convention here, like if I were to roll out an agent and call it a GDE agent, obviously I'm going to think that it's only working in Shady Edwards. But if I but if I were to call it like an accounts receivable agent that happens to use JD Edwards, would that be a better way to really look at the digital workforce here?

Oh yeah, IA 100% right. I mean it, it's the way I refer to our, you know our agents. I've and you know me, I don't even call them agents, I call them digital workers, right?

But it's always around this is our financial digital workers or this is our home building digital workers or this is our distribution workers right there. We have AP digital workers, we have reconciliation digital workers. You know, we have all of those, right? Not JD Edwards, right?

These agents happen to, can happen to use JD Edwards. They understand JD Edwards, right? They're knowledgeable about JD Edwards, but there's not, they're not JD Edwards agents. They're and you know, that's important for what we just said.

JD Edwards is just part of the process, right? They're trying to manage the process, right.

So, you know, let's say you know that that digital workers job today is is doing collection calls or what not AJD Edwards only agent can just tell you what invoices are 60 days past due.

Yeah, yeah, sure.

Which which is not bad stuff, right? You know, but it doesn't tell you if the customer disputed the invoices 3 weeks ago and the CRM system says they're in a renewal process as well.

And, and then, you know, the, the, the documents over in, in your SharePoint say that proof of delivery settles that dispute, that they didn't get it. You know what I mean?

The, the JD Edwards agent puts the, puts the customer to the top of the call list and AR agent looks at all the possible data sources to help that person make the best decisions, right?

So you know, your company already has the data. It's the workers are trying to organize and to rally and to kind of combine that information to make make decisions, right?

And that's what ours is doing, right? We just happened to work with companies that have JD Edwards, you know, as their ERP system, right. But these agents work in around outside of JD Edwards just as naturally as they do with it.

So absolutely we shouldn't be calling them JD Edwards agents anything. They're the process that they're trying to solve for. Episode 45 - Kevin Van Horn_1-e…

Yeah. So that's, it's a perfect Segway into where I'm kind of going with this. Like what changes when executives start thinking about agents as digital workers are part of their workforce compared to maybe how they're thinking about them today?

Yeah, I mean, it's, it's important, right? I mean, it's, it's, you know, if I'm thinking about that, I'm thinking about 3 different things, right? And, and one of them could be, one of them could be uncomfortable, actually two of them could be uncomfortable.

But the first thing that I'm that I would think about is, is that capacity and headcount are two different things, right? And it's something that we've been trying to have as part of our dialogue with our with our great customers as well as that, you know, when you first look at it, the agents can just do amazing things to help give organizations back time, right, which is capacity, right?

It's labor capacity, right? It's throughput, you know, it's you know, but it's not necessarily that's up to you as an organization. What you do with that capacity, right? How you allocate that that capacity. How do you change organizational roles now that you have digital workers as part of your organization, right?

So you know, so that's important, right? It it's like, you know, you don't have to, you know, this isn't about jobs and job racks, you know that, you know, so it's, it's just a question of what do you want to do with that new capacity that you're OK.

2nd is that because of the way that these workers tie into your organization, you really have, you really have to name an owner for something that you don't necessarily have an owner for today, right? You know what I mean?

You know, going back to that our very first point around, you know, why digital workers instead of tools, right? Because you know, what's the job? Who manages it? You know, what do you allow them to do?

Well, we all. Understand that, you know, when we hire somebody, there's an organizational chart and they flow up, right? And there's only one person that doesn't have a manager, and that's the person at the top, right?

But otherwise, everybody kind of has, and I don't want to say it the weird way, but everyone has an owner, right? Everyone has a boss, everyone has a manager, right? That's kind of ultimately responsible down the line, right?

But but that's for people boxes. That's where rolls, right? We now have to name an owner for a process, right, where that's not something we necessarily did before. It was always this, it was always just a group of people trying to work together, right to to solve a problem.

Now we've got to name the owner of that so they can actually start helping that digital worker coordinate that. And you know, ultimately look at how the company is performing that process. Not a specific role, right?

And third one is, is this one might be, this is the one I thought was uncomfortable, but then I realized that the labour 1 is, is certainly kind of that a different kind of conversation to have.

But the the third thing to think about is governance, right, is how much, how much are you going to allow the how much autonomy you're going to you allow these digital workers? How much are you going to delegate to them? Right?

You know, you know, you know, everybody asks the same question, You know, what can AI do for us, right? How can it help us? Right, you know, you know, kind kind of the better question, you know, like if, if the, if my chair was differently and I was on the other side of it talking to me, it'd be like, you know, what am I willing to what am I willing to allow AI to be accountable for, right, Versus, you know, you could because now it's a person, right, you know, and, and, and that's why you have managers, right, because, you know, ultimately somebody's accountable for doing something and the manager above that, and they're accountable for everything those people do.

And and it moves on up the food chain, food chain that way. But now when we're looking at this, it's all you, you have to have that thought and that, that process of what am I going to let them do? Right?

And you know, we work with you on this as well. And we realize that, you know, on day one, you know, these don't have to be fully autonomous digital workers that are doing things without human intervention. And you wake up in the morning and all this stuff's done and you don't know how, right?

I mean, clearly we have all the account of the audit trails and the observability of everything that the agents are doing. But it's more important of how do how do you want that governance to happen? And it will change over time, right?

I mean, as you start seeing how these agents are executing your thoughts around what am I, you know, what's, you know, my capacity for letting the digital worker do something autonomously will change, right?

Because you see that it just processed 10,000 invoices and anything that over had a 95% confidence score from them was perfect to begin with. Well, you know what, maybe, maybe we don't need to have that, you know, level of governments and let them do that work.

My, my dream is that someday digital workers will be part of the org chart and this and maybe someday the org charts going to look differently, right? It won't be an org chart that has these structured roles. Maybe it's an org chart around are the critical business processes a company needs to execute to be successful.

But they should be there. But they should be there, right?

Yeah. And I think that's a very interesting goal to have of the next step of this digital worker evolution is to put them into the spots where they make sense in the org chart.

Because yeah, if we start looking at them as part of the workforce and we start giving them a specific roles, then it really will open up how the idea of AI agents can shift to that idea of digital workers.

But if we stop thinking about that agent as belonging to 1 application and start thinking about it as performing part of a business process, I think that shift will come.

4. Security, Identity, and Permissions for Digital Workers

But you're right, it also raises that important question of how are we going to make sure this is secure? Should we trust this? What should that really look like?

So if an AI agent can access enterprise systems and really take action, how do you govern? How do you make sure that it's secure and what it is allowed to do?

Yeah, Yeah, I like to think about it as you start treating the digital worker as a privileged identity, right? Not a feature of an an application or a tool, right.

The digital worker, you know, and the great thing about our AIG agents is that, you know, and, and why it's so quick to value is that because of our relationship with JD Edwards and because, you know, our understanding with that, you know, our agents can assume those security identities that within JD Edwards and you know, it can do that.

So if you think about it, an age in itself, right, It has credentials.

Yeah, it does.

I mean, an agent will have a credential, right? It's it the JD Edwards knows when an agent logs into it?

No, it knows when it updates it and knows just like it knows that you and I did it, right?

It has permissions. We allow it to do certain things. Can it add? Can it change? Can it edit? Can it update? Can it do all those things? It has credentials, right?

And because of the credentials and the permissions, it can take actions, right? So those things together, that's, that's an identity, right? You know what I mean?

That's, that's not a a tool, that's not an application, right? You know, that's, that's, that's a digital worker, right? Credentials, permissions and actions, right?

So, you know, then you turn this conversation back and and you know, and it's really important, right? I mean, so I'm not trying to minimize it at all, right?

The governance around AI with an organization's has to be, you know, a a sea level conversation that all companies are having, right? And, and I'm seeing it everyday.

I mean, we're talking to, you know, sea levels, we're talking to board of directors and they're all, you know, wanting to have this conversation, right?

But so if you if you take them a step back and it's typically kind of this the the CIOCTO organization that's really kind of responsible around that kind of governance model, right?

You start thinking about those actions, right? You know what I mean that I said before, I mean, you know, they understand credentialization, right? They understand permission sets, it's all this.

But what do you want them to do? So think about the that those actions, right? And think about it kind of in four different ways, right?

They can, what could an agent do? It could read something, helps it learn, could then recommend something, it could approve something or it could execute something, right?

Those are kind of the actions that an agent can perform, right? And you know, even within a singular process, the tasks within that process could be different. You know what I mean?

It's like, you know, you could have something along a process where you say, you know, for instance, if we're do talking about our AP agent, you might give the the agent the autonomy to execute a two way match on an invoice against the PO, right?

Why not?

But you might not, you might not give it the approval to go out and update the JD Edwards 411 tables, right? You might want that human in the Lube at that point, right?

So that that's that's kind of a a that that stops at the execution and brings it back to the approval, right? So it stages things for approval.

So even within the same process, it's not like it's not like about anyone singular process has to follow that. It's even just the individual task within the process, right?

You know, So you know, a well designed agent usually looks at a lot of different data, right? You know what I mean? It's a lot of different areas in there, right?

Lots of systems to recommend from, you know, and you know, then it usually gets to a point where it executes to one specific space or one specific place, right?

You know, and that's, you know, we're all used to those flow charts of a business process. That's usually the one at the very end, right? You know, so you know, the so that's kind of how it works.

And I guess, you know, if you boil it all down to one thing, right? And, and, and say the one thing you know out loud is that the goal of any one of these digital workers is not to eliminate me, right?

You know what I mean, right? It's to match the autonomy with the action right now. Does that make sense?

It's like, you know, oh, it does.

You know, if, if we give the AP agent to autonomy to do a two way match, fine, if it makes a mistake, it would actually learn from that mistake, right?

But if it makes a mistake, there was really no harm and it was a learning opportunity, right? You didn't cut a check. You know what I mean? Money wasn't flying out the door.

Not, not nothing bad happened except a learning, a learning, a learning opportunity was done, right.

So it's it's, you know, we're not from a governance perspective, you're not trying to eliminate, you know, you don't want to eliminate the, you know, autonomy.

You want to match the autonomy to the actions that you want the digital worker to perform, if that makes sense.

Building a Governance Model for Digital Workers