Simon Cornwell, Civica | Certinia at Dreamforce 2026

Welcome back to the cub's continuing coverage of Dreamforce 2026 where we're focused on the professional services industry which is clearly a leading indicator of where uh enterprise AI is heading. I'm Scott Hebner. I'm the principal analyst at the cube research for AI. Appreciate you tuning in today. Today I'm thrilled to be joined by Simon Cornwell. He's the CIO at Civica. >> Thanks very much, Scott. >> Appreciate you being here. >> Yeah, it's great to be here. Thank you. >> It's been a great show, hasn't it? >> Yeah. Yeah. Yeah. Dreamforce is always an intense like mix of new announcements. We get to see where the products are going. We get to meet great vendors like Satinia. So, yeah, good show. >> Yeah. Good weather, too, this time. Uh >> yeah. Yeah, it's a bit warm. It's a bit warm. [laughter] >> Not terrible. And uh we're in a great venue here with great food. They keep coming around with the steaks and lobster, so >> makes it a great environment. And actually before we dive into things here, what what was your thoughts on Mark Beni off's keynote and where Salesforce is heading in general? >> Yeah, I think it's I think it's really interesting. Two years ago, we were all talking about the SAS apocalypse and this is the end of SAS. You know, we don't need SAS anymore. We're going to vibe code it in a weekend. >> Uh I think what the the direction set out in the keynote is is really clear that, you know, it SAS in a way is a bit dead. SAS really now becomes the system of record. It becomes where we keep our data uh our workflows our semantics but actually the place of work where we do our work could be anywhere it could be in Slack it could be in teams or claude and so yeah I think it's very exciting that they are moving away from uh a Salesforce shaped product which is only Salesforce shaped and uh yeah >> and there's a massive uh corporate graveyard of companies that resisted the change and it's because we're indispensable. Yeah. Yeah. Yeah. >> Just to say, "Hey, this is I know this is what we built our business on, but it's time to change." And and uh yeah, I thought it was very good and I very clear. I like the idea of moving from probabilistic AI increasingly to deterministic. >> Yes. >> And all the stuff they're doing to build that stack. So, um I I thought it was a very interesting keynote. Um okay. So before we like start talking a little bit about what you see happening in the industry and talk a little bit about uh Civica, what you guys do, what your role as a CIO is. >> Okay. Yeah. So Civica, Civic's been around for a few decades now. It is a company. We provide SAS and services to predominantly public sector. So local government, central government around the world. Uh our products and services are powering the interactions of citizens about 100 million citizens right the way across the world. typical use cases. It could be anything from how you buy your parking permit to how your kids pay for their school lunch, you know, using a contactless payment or how you arrange social care for for a relative. So, it's, you know, we have a wide range of software that we deliver out um through our professional services >> in customized is it customized or is it >> Yeah. Yeah. >> Yes, it's a combination. uh we we have all of our base products but yeah we we then do professional services to actually implement those configure customize whatever the the the customer actually needs and then my role as a CIO so I own all of the technology that's used internally within Civica so the corporate space right >> uh so that includes things like Salesforce and Satinia uh and our telefan and our finance system so all of the internal technology right that comes under me >> and so what exactly are you doing with Salesforce in Certinia there. >> Yeah. So, um, Civic's actually grown quite successfully over a number of years, but it's grown organically and it's grown through acquisition and and that's left us with a landscape of bespoke systems, disconnected data, uh, fragmentation. So, we're going through a transformation at the moment. Um, we've had Salesforce for a number of years. We are in the process of implementing Satinia and it creates that center of gravity for everything relating to the customer. So all the data is in one place and you know the data then flows data that's captured in sales flows through to delivery and we're working from a single source of truth rather than multiple sources of truth. >> Right. And how do you see AI affecting all this big change incremental? >> Massively. Yeah. Yeah. It's going to be a massive change. Um uh it's probably a scale isn't it? Some some of it's going to be very incremental but others is going to be um you know for us groundbreaking in some areas. you know, it's um we're looking at how we can speed up our time to delivery, our time to value, time to revenue recognition. Um we are looking as well about how do we get the right mix of agentic workflows and people, humans, >> right? >> Um we're not sure what the answer is yet, but you know, that's something we're navigating right now, but it's uh it's very exciting. All of that only works if you've got good operational data, trusted data, trusted source so that you know you can trust then the outcome from whatever AI you're using. I remember last last year, I think it was last year, Mark Benov did a interview with Dave Volante at the cube, >> the same setting here, >> and he had made the comment that he was going to be the last leader >> at Salesforce to manage a human-on workforce, >> right? Yeah. >> And uh so it's interesting your comment about, you know, there's going to be digital agents, little co-workers, >> how that mixes in, you know, my observation from just tracking the industries, I think AI will eventually be a net job growth. >> Yes. versus it's going to change the nature of jobs, but people are just going to get superpowers going to be to do more and then they're going to want more people to do the high value things, right? So, >> exactly. Exactly. The the the nature of work may change. Uh it's not going to just do away with everybody's job overnight. You know, I don't believe any of those predictions, >> right? >> Or kill everyone like uh over the week. >> That's a really interesting debate going on right now around the pace of development and uh unchecked development. It's it's an interesting discussion. >> Yeah. Yeah, I think that's one of the interesting things that c certainly we have to struggle with and it's a lot more intense than it was in the cloud transformation or client server or >> um >> how much do you slow down how much do you regulate to slow down the technology advancement? >> Yeah. >> When perhaps other parts of the world that's not going to happen as much. >> Yes. >> Yet you run into risk like uh I don't know I watched the video from open AI about how those >> how those models escaped and hooked up. >> Yes. What a that was they should make a movie out of that. It's like a drama. >> It sure will. >> Yeah. >> You know, and um so it's going to be interesting to see where that all goes. >> Yeah. >> And obviously you you're in public sector a great deal of your business >> which tend to be a little bit more regulated >> Yeah. >> than everyday commercial industry. So how do you see AI affecting that world? I mean you you mentioned the key word which was trust. >> Yeah. Trust is is going to be the word that everybody's going to be hearing both at Dreamforce and outside for the next few years. It's it's the most important word. You know, we have to be able to trust the uh trust what the AI is doing, trust the outputs, trust the decisions that it's either making for us or the decisions it's suggesting to us. Um so you know I think um for our particular line of work where we're dealing with citizen data you know absolutely we have to be able to provide that level of trust to our customers >> right >> uh and sometimes the um the work that we do means that uh we can't use models which are in a different country and we have to think about residency and sovereignty and and those uh different aspects of compliance. defense and regulatory uh compliance. >> Yeah, that's another big uh topic these days is sovereign AI. >> Yeah. Yeah. >> And uh it sort of reminds me of the the cloud transformation in reverse. >> Yes. >> Right. Um but I think that you know your your data is proprietary, your information, your policies, your people. >> Yeah. >> And there's got to be an element of sovereign capabilities. And I think that's what's going to help to and I think trust is multi-dimensional, right? is are the explanations you know accurate enough that you can rely on it and feel confident about it. Yes. There's the human trust you know these things are only going to be as good as humans trust to right then there's like are you know all the compliance and security of data and yeah >> you know do I trust that ROI is going to come. So I agree with you that if I was to summarize um all the conversations I get to have in this job with leaders across the industry, the single word I would use to define the state of enterprise AI is that word trust. >> Yeah. Yeah. >> Heavy multi-dimensional and I imagine in the environments you're working is even higher because there's fewer degrees or you need greater degrees of precision. >> Yes. >> Um Yes. >> to do things in those kind of regulated environments. >> Absolutely. Yeah. Absolutely. Yeah. Yeah. The decisions we make need to be grounded in trust and in truth. And we have to be certain uh that the models that we use uh we understand how they work. We understand where our data is going. Uh how it's going to be used. Um how do we protect it? Because like you say, our data is proprietary to us. Our ways of working is proprietary to us. >> Yeah, definitely a number one topic. Um, in fact, we're running actually running a digital summit on AI trust and cyber resiliency. >> Um, which I think has been part of the slow down, you know, with all technology ramps up and we've slowed down as an industry a little bit. >> Yeah. >> And I think it's because of that word >> trust because as you get into more consequential, it's one thing to have us doing better analysis and all that, but when you start making consequential decisions that have, you know, consequence like real consequence to the business, whether it's financial, reputational, >> Yeah. >> you know, you got to have that higher level of trust. So >> yes. Yeah, definitely. Definitely. >> Which is I sort of like the um again what Mark Ben off was saying about going from probabilistic to more deterministic. >> Yeah. >> That's going to enhance a little bit of trust. >> Yeah. >> Uh Sat Certinia's message here is be certain. >> Yes. >> Be certain about the actions and they're trying to drive towards greater certainty. >> Yeah. >> Which again is another one of those little coral areas or pillars off of trust. So >> totally. Yeah. And and all of that relies on that data foundation which is leads us back to our transformation and our focus on that center of gravity of Salesforce and Catinia. you know, we we >> need data to flow through the process in a single system. Uh then we can use that to expose it to AI for agentic AI >> uh and use that to help develop insights, >> right? >> Actionable insights, >> right? >> Yeah. >> Well, you know, that's one thing I'm really impressed with in terms of Satennia doing the >> they have built the knowledge graphs and then now they have the ability to maintain context. >> Yeah. >> Right. with the Moon Knox uh acquisition and now they're using that to create you know more certainty. >> Yeah. >> Or you know confidence in the actions that you take the system of actions and how they relate and affect each other. >> Absolutely. >> Which ultimately will lead to better outcomes that >> that you can then compound the value over time. >> So it's it's an interesting um approach to it which at its core is what you've been saying is it's trust. It's addressing the trust iss you head head on. >> Yeah. Yeah. Yeah. Yeah. And being certain um you know that's one thing which Catinia does give us. It gives us the ability to go from an estimation uh at the start of a a deal process through delivery and understanding that the estimation is based on you know how we can actually deliver this uh and if we improve the accuracy of the estimation at the front end it improves the success uh of the the project the implementation uh reduces time to market improves the predictability of onboarding customers. Yeah. So yeah. >> Yeah. And back to your point your point earlier about it's it's always going to be a mix it's going to be a mix of humans and digital agents >> one augments the other. >> Yeah. Exactly. And and when they when the trust is improved between both of them >> Yeah. >> you're more certain about what you're doing. >> Yeah. >> You know it it it it makes a good >> you know I the word I was struggling with and it just came to me is the word judgment. >> Yes. >> Because in the end humans are still gonna have to make judgments. the more they can trust the AI agents, more certain they are that what they're recommending or what they're uncovering, the better judgment you're going to make. The better judgments you make, the better the outcomes. >> Yes. >> And false negatives and going off the wrong path and stuff like that. So, >> and then you get things done cheaper, more efficiently, >> better price point and you can do more and you can see how it becomes an economic catalyst. >> Yeah. Exactly. Exactly. Yeah. >> At least in the in the commercial market. Now what additional constraints are you seeing just in the p in the public sector area besides because ROI doesn't really have the same meaning does it as in commercial? >> Well yes and no. uh so I guess public sector aren't beholden to uh shareholders but they are beholden to the public and so they have to be able to demonstrate that they have made good judgment themselves in their purchasing decisions you know buying our software uh and uh using that to deliver the services they need to the citizen you know they have to be able to justify so it's still uh an interesting conversation around ROI >> yeah I think that the other thing I've been picking up on too is more and more uh leaders out there saying you the architecture really matters now. It's not >> it's not as simple as going off and choosing the most capable model. >> No, >> it now is becoming an architectural um game where you have multiple elements of AI doing thing, not just agents, but yes, >> you have models and you have knowledge graphs and you got Yeah. >> Yeah. Exactly. Yeah. Now uh probably a year 18 months ago we were talking about what's your AI platform whereas now you know that's not even a question anymore because we use the right AI for the right job >> uh the right circumstanc and and that will mean using models from different providers. It'll be using solutions, AI solutions from different providers, but then the right solution for the right uh purpose and the right bit of our um organization rather than blanket everybody gets everything. >> Yeah. And where you put the models and whether they're in a sovereign environment and what the data >> exactly and exactly >> it becomes much more of an architectural, you know. >> Yes. Yeah. And we have to think about not just uh what are the tools that we're putting in place but how do we govern those tools? what is the the fabric or the framework that we're using to to manage those and uh ultimately should we ever need to to stop them from uh from doing what they're doing. >> Yeah. So, go back to the the the notion of the headwinds of, you know, more regulatory or more constraints or um do you think we're at a point now that there's so much new technology out there that it's not a bad idea to kind of get get our hands around it, figure out what you can do with it? Um, again, part of what I get to do is talk to tons and tons of people. I get I get a sense that there's so much new stuff out there >> that's coming out so quickly that everyone's just struggling to to to understand it all. >> Oh yes. >> And it seems like there's enough there's going to be a way before it's saturated where we have to move on to the next innovation. >> Yeah. >> And it's going to be fascinating to watch the debate coming up about >> does the industry slow itself down. Now, by the way, these guys like, you know, that are talking about this, the CEOs of Enthropic and Open AAI and all this, I mean, they can certainly just slow things down, right? >> Yeah. Yeah. Yeah. Um, but >> yeah, I'm I'm I'm not sure how it's going to go, you know, perhaps we're reaching this point and having these conversations now because the capabilities are becoming more credible. Uh, the ability is there to do more. uh there are more stories of models that have escaped their guard rails and there's been unintended consequences and so it's good that we have these kinds of discussions what the the landscape's going to look like in a few years. Uh I think that's anybody's guess you know are we going to see similar to the uh the cloud uh technology landscape where you know it it exploded and there were so many new produ uh providers and then it kind of consolidated over time and things dropped out you know we we focused then on on core capabilities which are now purely commodity um we don't even think about them anymore and I think that's where AI is going to get eventually. Well, I remember we were all going to die with the year 2000 and all the cobalt developers are gone and no one knows what they built and >> I worked on the millennials. Remember that? So, sometimes you have to take these things, but my sense in professional services at least is there's a lot of new technology that still needs to be >> tuned. Yep. >> Proven. >> Yep. >> Um, a lot of really good use cases and outcomes so far. Yeah. But there's enough to work with now where maybe as an industry just not so much the producers of the stuff but the consumers get that trust level to where before you start innovating to the next level and >> yeah yeah I agree and um I think it's almost beholden on the consumers to take a lot of the responsibility because how you use a product what you do with a product what data you provide that product that's a choice that you have to make and there's a there's a education which needs to happen right the way across um the world. You know, people need to understand what AI can do uh and what happens when they interact with it. And we have to take responsibility in our own businesses about what that means. So, Pacifica, we consider any new AI tool or product before we introduce it. We think about as I the the themes I talked about, where is our data going to be? Is it going to be used for anything other than what we say it's going to be used for? um where's it going to be processed? How many copies are going to be stored? You know, all this kind of stuff. Um what can it do? Uh and how how can we trust that it's going to deliver predictable outcomes, whatever that outcome is we're trying to achieve. >> Got to as an industry ramp up the responsible AI mantra, which was very very prevalent a couple years ago. it kind of has faded back into you don't hear as much about it anymore but yeah >> maybe the more recent uh you know discussions we'll get that back up >> yes it's just going to become all our responsibility you know we we we can't simply just uh let something happen and then say well it was the AI that did it >> right that won't that >> I'm responsible yeah yeah >> yeah so last question here before we have to wrap up it so when you talk to a CIO >> right your your cohort out there. What would be one question that they should ask every vendor before they really consider them? >> Yeah. >> If they're going to be like a a provider of some sort of AI capability. >> Yeah. So, it's it's all all comes back to this one word, you know, how can they demonstrate to us trust? >> How do we know um that they understand how their product actually works, what it's doing, um what are the implications for us? How will it work with everything else that we've got? because we will never be a a single vendor enterprise. I don't think any organization will uh will be. So yeah, it's it's it's demonstrating to us with authenticity and credibility that uh the the service that they're providing >> is what we need and trustworthy. >> Yeah. Sort of um getting getting in there with this huge innovation message. >> Yeah. >> Needs to be balanced with the trust message. >> Yeah. Yeah, it's it's way more than just saying our product is great. >> Yeah, >> our product is the best out there, right? >> You know, why is it the best? Why, you know, why should we trust you with our >> most valuable assets, our data, >> especially as it get, you know, it evolves into more consequential business decisions is that trust that that is like current, you know, trust is the currency of innovation, I think, going forwards, you know, from this year on forward. So, everyone's got to double down on that. So, I think that >> answers, you know, right on with everything I've heard. So, >> all right. Well, it's been great. I appreciate taking the time to be here. Enjoy the rest of the show. >> Thank you. >> All right. All right. Well, we'll be back with more here from Dreamforce 2026. Hang in there. We'll be back real soon. Thanks.