Tech Talks Daily
00:00:04 · Neil C. Hughes
[00:00:04] S0: What changes when your business software can explain a process, teach you how to use it, and then even carry out the work? Well, this week, I'm recording at SuiteWorld in Las Vegas. And I spoke with Brian Chess, who leads AI product and technology for Oracle NetSuite. And we discussed how people move from checking an AI answer to trusting an agent with a business task. And Brian will share examples today involving payroll, financial close, and the knowledge that usually lives with the person everyone usually calls. Yeah, department has a go to person, right? And we will also talk about permissions, human approvals and the records needed to understand which agent changed a transaction. Ultimately, for anyone wondering where a conversational ERP becomes useful, today's conversation will put the focus on everyday work and the decisions around it. So if your finance team's favourite interface is still a spreadsheet, and I know there's more than a few of you out there, you might appreciate the starting point that Brian describes today before asking anybody to hand the process over to a AI agent at work. Lots of value in this. And with that scene set, let me introduce you to him now. So we're recording here today at SuiteWorld in Vegas, and thank you so much for taking the time to sit down with me today. Can you see everyone listening and watching a little about who you are and what you do?
00:01:40 · Brian Chess, Neil C. Hughes
[00:01:40] S1: I'm Brian Chess. I run AI product and technology for Oracle NetSuite, And more or less, that means I do everything related to how do we come up with our product and how do we take it to market. So, I started at NetSuite around the turn of the century. Century. So I was one of the early developers of what was then named NetLedger. And then, I left, started a company of my own, came back with a much greater appreciation for what small and growing businesses need. And then a few years ago, I got interested in AI. And back then, AI was a really interesting topic, and then it became a really important topic, and then it became the only topic. And that's where we are today. And so much has changed. The last eighteen months to two years alone, what excites you most about everything that's being announced this week? You've been [00:02:34] S0: there from the ground up and seeing it come to where we are now, but what excites you? [00:02:37] S1: The most exciting thing this year... Well, maybe I should back up and say, last year was when we announced NetSuite Next. And so, next was the big word last year. [00:02:48] S0: Yeah. [00:02:49] S1: My big word this year is now because next has arrived, and it's not the promise of AI anymore. The promise has arrived. It's about putting it to work. [00:03:02] S0: And there is so much going on here at the moment, and I think it can be overwhelming for the average business leader wherever they are in the world. So what technical changes are needed when enterprise software moves from just AI suggestions to agents that complete work?
00:03:02 · Neil C. Hughes, Brian Chess
[00:03:02] S0: And there is so much going on here at the moment, and I think it can be overwhelming for the average business leader wherever they are in the world. So what technical changes are needed when enterprise software moves from just AI suggestions to agents that complete work? [00:03:16] S1: Well, enterprises face a whole range of challenges. They've, in many cases, had humans in the loop because the loop was all humans because that's all there was was humans. And now they've gotta figure out how do we have a loop that maybe involves a lot of AI and, relatively speaking, fewer humans. The nice thing is for businesses that are running on NetSuite, the sis... The data is already organized. The processes are already in place. The roles and permission system already exists. We've got a nice setup to make that transition easy on our customers, and we're really proud of what they can now do. And before joining me today, I had a quick look [00:03:59] S0: at your stuff online. You've created so much great content out there, I saw a clip of you saying users connecting AI through NetSuite Next are exploring work that they have never attempted before and feel empowered doing it. Do you have any examples just to to bring that to life?
00:04:14 · Brian Chess
[00:04:14] S1: One of the things we see is AI acting as a teacher. Yeah. So someone says, is my account configured, for... Oh, let's name something. Who's logged in recently? NetSuite knows we have that information, and we've also made it accessible to people if they know where to look, but they haven't always felt like that was in their power to do it. Now they can just ask ask Oracle, and it will not only tell them the answer, it will tell them how they... How it got the answer. And now they can do it whenever they want because it taught them how that part of the system works. So AI is a fantastic enabler because it's a great teacher, and so it can take people into doing things. I'll give you another example. An administrator frequently might not be a developer. But they can ask, how does this script in my account work? And now they're starting to learn a little bit about the code, and they can talk to Ask Oracle about, well, why... What if I wanted to do this? What would that look like? And it can coach them through it, and we see that over and over again. We had an example today with our customer MCNC where all of a sudden the payroll administrator was out. Oops. Everybody still wants to get paid, but we don't have payroll administrator. So now the boss of the payroll administrator, the controller, needs to step in. Well, they weren't trained on the system. Yeah. How's everybody gonna get paid? Ask Oracle walked her through the process, and that's immensely powerful.
00:05:55 · Neil C. Hughes, Brian Chess
[00:05:55] S0: It really is. And I'm curious, again, people listening and watching, which NetSuite workflows are maybe best suited for AI agents today, and where is automation probably still too risky just to rely on? [00:06:09] S1: Well, we are really happy with what we've done around financial close. Yeah. And this is a process that every company has. Largely, they've had to manage it on spreadsheets. Yeah. And we looked at that, and we said, you know, we can automate a whole bunch of this now. But they've got their spreadsheet, and they want that close to happen the way they want it to work. Why is it on a spreadsheet? Because it's being run by the finance team. Yeah. That's that's their weapon of choice. Yeah. So how about we just ask them for their spreadsheet? Show us your spreadsheet. We'll create a model of that, and now you can do exactly what you used to do inside NetSuite and incrementally automate that process. That's really important because in order to trust the system, you don't wanna take a huge leap all at once. You wanna go a step at a time. And so we've enabled that. So financial close is a great example, but you look at supply chain management. A lot of people doing things there, trying to understand what's going on with with their vendors. If you look at workforce management, that's another one where I I gave you the example of, well, like, who's who's logging in? Who's using this thing? There's a lot that's happening there too. So it's really all over the suite. And in a former life, I'm an IT guy,
00:07:37 · Neil C. Hughes, Brian Chess
[00:07:37] S0: and I was helping. I was the resource for month end, year end period, and it's the scariest time. There's so much at stake there, isn't there? There's a lot of stress involved, so what kind of feedback have you had from departments that go through that stress, month after month, year after year? Well, it is [00:07:56] S1: a holy grail of sorts to make that a a a not stressful period Yeah. To a lot of people. I think I'd include myself in this in this camp. I've been working with generative AI since generative AI came around. It still feels a little magical to [00:08:13] S0: me. Yes. [00:08:14] S1: Some of these things where, like, you have a major problem, and then it just poof disappears feels like magic. [00:08:20] S0: Yeah. Really does. And how does the platform give an AI system enough business context without exposing data or permissions it shouldn't have? I suppose that is one of