Certinia at Dreamforce | James Davidson, Neocol

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More from Certinia at Dreamforce

James Davidson

CEO

Neocol

play_circle_outline Neocol: Quote-to-Cash Transformation on Salesforce with Revenue, Sales, Partner, Data Clouds and Agentforce AI Advisory, Build, Managed Services

play_circle_outline Agentforce/next-generation experiences as AI+UX over Salesforce platform

play_circle_outline Neocol AI-First Agents, T-Shaped Outcome-Focused Consulting with Certinia/Moonnox Integration and Trust-But-Verify Safeguards

play_circle_outline Human-led AI: humans + agents integrated across consulting methodology

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James Davidson, Neocol

James Davidson

CEO Neocol

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Scott Hebner

>> Hello everyone. Welcome back to theCUBE's continuing coverage of Dreamforce 2026, where we're focused on the professional services industry. And I'm Scott Hebner, Principal Analyst for Enterprise AI at theCUBE Research. Once again, thanks for tuning in. Well, I'm thrilled today to have James Davidson, who is the CEO of Neocol here with me., and we're going to continue our conversation around what's happening with professional services. So thanks very much for taking the time.

Scott Hebner

>> Yeah, thanks for having me.

Scott Hebner

>> Yeah, so why don't we start and just spend a little bit of time, giving our audience an overview of Neocol and what you guys all do and your relationship to Certinia.

Scott Hebner

>> Awesome. So, yeah, Neocol is really focused on the quote-to-cash business. So kind of end-to-end, we work on the Salesforce platform and we really see ourselves as revenue transformation experts. So all the systems that touch revenue, kind of the lifeblood of most businesses, We're focused on implementation services around the Salesforce platform, specifically Revenue Cloud, Sales Cloud, Partner Cloud, Data Cloud, and Agentforce, or now AI Force. Yeah, just at the conference. And then really in terms of how we help our clients, we have kind of 3 parts of our business, kind of advisory and business transformation services. So how to think about where the strategy and opportunity is with revenue transformation, build services. How to really deploy and scale Salesforce, Databricks, and AI platforms like Claude for business value. And then we have a managed services side of our business as well. So we help our clients manage their environments, ongoing break-fix work, and enhancements of their Salesforce environments.

Scott Hebner

>> What's been your observation so far here at the show? You like the keynote and what Marc

Scott Hebner

>> Benioff—I loved it. I think we see a massive opportunity around what we're calling next-generation experiences. So when we heard about Agentforce, We've already been working with Agentforce with clients and implementing. We say it's a rebirth of AI and UX over the top of the Salesforce platform. We're building solutions with our customers already. So really hearing the validation of Agentforce made us feel like we're investing our resources in the right things.

Scott Hebner

>> Yeah, I think they're keeping it simple with the stack. They are. The stack

Scott Hebner

>> just—it increases every year.

Scott Hebner

>> Yeah.

Scott Hebner

>> But it's exciting to see their innovation of the platform. And I do feel that Salesforce is back. Obviously, they had a— challenging time with SaaS apocalypse, but we're seeing them double down on the data. The business process is really key and driving AI adoption. So I thought the messaging was right on.

Scott Hebner

>> Yeah, I did too. I thought it was very inspiring. And I noticed he wore a suit.

Scott Hebner

>> Yeah.

Scott Hebner

>> Marc Benioff.

Scott Hebner

>> Yeah.

Scott Hebner

>> So he's always changing things up.

Scott Hebner

>> Yeah, he's changing things up every year.

Scott Hebner

>> Yeah.

Scott Hebner

>> Yeah.

Scott Hebner

>> So you recently became CEO.

Scott Hebner

>> Yeah.

Scott Hebner

>> Right. And I noticed that you had driven a total AI transformation within your organization. I always like to ask, what did you learn from that? what was the philosophy behind it? it's always interesting to hear the transformation stories after they've been completed, or at

Scott Hebner

>> least—So it's a great, great question. I think professional services is having a moment and it's— we're really having to rethink our business model top to bottom. So at Neocol, traditionally, time and materials business, labor-based consulting. I think what we are seeing more and more is clients approaching us. Now, everyone wants quicker, faster, cheaper. And so we're really faced with seeing the business model of professional services changing in front of our eyes and really looking for a way to do projects quicker but at high quality with humans and agents. That's really where we're a Certinia PSA customer. So we use that for workforce management and professional services side of our business. And then we were lucky enough to get connected with Moonnox, which is now part of Certinia, part of the Veda platform. When we started doing evaluation to say, how do we take all the knowledge, the best practices and experience we have from years of doing these Salesforce implementations and turn that around into a more AI-first approach for our clients? So that was our original hypothesis. How do we go more AI-first and enabled? Because customers want projects quicker, cheaper, faster. We ran a pretty extensive evaluation process and were really looking at the platforms that were out there and what we really loved about the Veda platform was the ability to take our knowledge, take our skills, and then create agents for our different pockets of our consulting organization, whether that was our sales, presales, delivery, finance, or ops, and then start to connect those agents to drive value. There are a lot of out-of-the-box agents that just gave us capabilities that we needed right away. So RFPs are something no one likes to do, we have a massive repository of those. We now have the ability with their platform to take an RFP and respond very quickly. You need to trust but verify that and make sure the content is of high quality. But the more that we put into this platform, the higher the value we see. The other side of this for us as well is instead of thinking about deploying AI individually, we credit Certinia with this and coming in and really helping us think through that entire professional services journey as kind of an end-to-end experience.

Scott Hebner

>> Right.

Scott Hebner

>> Because if you think about it, it's a team sport. Consulting works best when sales, is working with delivery, is working with finance, is working with ops. And so the way that we really thought about that was end-to-end, finding where the biggest pain point was, whether it was on sales scoping and estimation, whether that was running client workshops, facilitating that and transferring those workshop notes into requirements, all the way down to build. We managed to think through that end-to-end and see where the pain and the human labor was. And for us, the vision is How do we actually take our people and redeploy them to high-value activities, not low-value activities where you're spending too much time? So that was some of the hypotheses that we had going into this.

Scott Hebner

>> Yeah, I covered the Moonnox acquisition. I wrote a research paper on it. I was really impressed with the capabilities, and even prior to that, I've been a big advocate of evolving from knowledge graphs into what I called context spaces.

Scott Hebner

>> Context-based, yeah.

Scott Hebner

>> The ability to maintain the context across the project even when it's changing due to meetings and stuff like that.

Scott Hebner

>> Absolutely. You found that it's a game changer. And I think everyone uses this technology differently. For me, you take the software, you deploy the software, but I think everyone needs to have their aha moment. And for me, before I became CEO, I was Chief Strategy Officer, and I'd oversold my capacity. So in one week I had 4 engagements hit all at the same time. Highly strategic advisory conversations that I need to have with 4 separate customers. And if I go back in a time machine to 2020, this would have been 40 hours per presentation, sweating the pixels, the content, the layout of the deck, the storyline. With this technology, I was able to focus more on the storyline and have all the context of the conversations I'd had with the customer.

Scott Hebner

>> Yeah.

Scott Hebner

>> and within about 20 hours I'd completed 4 of those deliverables that if I went back to 2020 would probably have been 20 to 30 to 40 hours' worth of work.

Scott Hebner

>> That's you personally?

Scott Hebner

>> Me personally.

Scott Hebner

>> Yeah.

Scott Hebner

>> That was the unlock moment for me where I'm like, that's just one use case. And if you deploy that across your entire workforce, whether you're writing stories, whether you're creating technical documentation, RFPs, it's an unlock.

Scott Hebner

>> So what was the big observation on, where people are now spending their time compared to maybe 2020?

Scott Hebner

>> I think you're spending more of the time, like consulting is a people business.

Scott Hebner

>> Yeah.

Scott Hebner

>> The more you're spending time with your people, whether it's your project team or your client, you're adding value. You're not adding value when you're just sitting there formatting a document, right? So I think what we find the deployment of time being now on the value is to spend time on the high-value activities, which are client-facing, icing on the cake, but not doing the kind of manual work of, taking a spreadsheet, having to find themes and patterns in that and organizing that information into buckets. I went back to workshops that I'd used to run as a consultant, journey mapping, Post-it notes that you had to transcribe and just the manual labor in doing that to now that piece is taken away. So you can really focus on the value story and the opportunities for your client in the solution. Not so much just admin work.

Scott Hebner

>> Yeah.

Scott Hebner

>> Yeah.

Scott Hebner

>> And you mentioned the people business, which has been a theme here. And I know you have a term that you use, which is, what is it? Human-led AI.

Scott Hebner

>> Yep.

Scott Hebner

>> Centered or AI.

Scott Hebner

>> Absolutely.

Scott Hebner

>> So in practice, what does that mean for you guys as you do your work?

Scott Hebner

>> So every consulting company has a methodology of how they think through their process from sales all the way through delivery. So human-led AI first to me is, How do we take every step of the consulting methodology that we have and overlay agents to actually support our people in doing their work? So for sales, helping write proposals, create contracts, statements of work grounded in the context of the conversations we've had with the customer, it's an unlock. You're no longer it's no longer guesswork or going back through someone's notes or guessing at this. The ability to have those call transcripts feed the platform for consultants. Taking that context from sales into delivery and using that to create deliverables and assets that are highly aligned, that we're seeing on the projects where we're using this technology, it's reducing scope creep, it's reducing disconnects between teams, and you no longer have this concept of sales to delivery handoff. You just have context that gets better the more you get into the project with the client. So the methodology for us is one with humans and agents. Across every step of our delivery methodology to deliver project work cheaper, faster, quicker. That's really what clients are looking for in the age of AI-first consulting.

Scott Hebner

>> Yeah, and I'm curious to hear your observation or your view on the current theme that Certinia has. as I've been following for the last year, it started off with the need to orchestrate across the entire end-to-end and then around Services Week, I think it was late spring, it was about judgment. AI brings efficiency, but you still need human judgment.

Scott Hebner

>> Absolutely.

Scott Hebner

>> And now it's be certain. And the more certain you are in the actions you're taking, the better the outcomes. And then when you hear Marc Benioff in the keynote talking about the evolution from probabilistic to deterministic, it kind of fits nicely with certainty, right? You got to be certain on what you know, what you're doing. And you take their platform and what you're doing and you add in the context That's sort of where we're heading, right? Is more and more certainty in the output.

Scott Hebner

>> We are. And I think you're— the way I use AI, I think we're all using it maybe a little differently, but I think it is a coach that knows you, knows the context. And that's really what we see in this platform is that sometimes in consulting, when you're on the line trying to get a deliverable over the line and you don't have access to everyone on your team and you're the consultant on the ground having to make a decision, you're now backed up by this massive repository of context and knowledge for the project that you're doing, all the collective best practices that you have in the organization, that it's a true unlock. And what we're seeing is it takes a junior consultant and gives them the ability to be more senior. And for a senior consultant, it's just unlocking value in being much more prepared or organized for the conversations you're having. And then a cautionary tale though, I think the human in the loop or trust but verify. If you only just say create a consulting deliverable top to bottom and fire that out to your client, you can get sometimes hallucination, AI slop. So I think that you still as a human need to spend time inspecting the quality of the deliverable. Yeah, but some of the admin work I would say is going away with this technology, which is fascinating. And then for our teams, how do we take that time to deploy that to high value activities versus the low value activities that no one likes doing, but always had to do. It's part of the job.

Scott Hebner

>> Yeah, and there seems to be obviously a bigger narrative in the industry, the overall industry, not professional services, but just tech, and probably just society that AI is going to take everyone's jobs, and now you have this thing that's going to kill us all. But back to the job thing, one other thing I've learned in the conversation so far here is that in the professional services, AI is actually creating more jobs because you do more projects, things are happening faster with higher quality. Yep. What's your view about the job?

Scott Hebner

>> I 100% align with that. So we're seeing the remit of a consultant. Are you aware of T and I-shaped consulting? So I think what we're seeing is this great opportunity. So if you're an I-shaped consultant, you might say I was always a business analyst. I meet with a client, I sit in meetings, I take notes. I write stories, I move those stories into Jira or whatever the platform is, and then I execute the project and I ride along. What we're seeing is clients are pushing us and our consultants are pushing us to say, I want to do more than just be pigeonholed into doing one thing. So with AI, I think it's changing the shape of a consultant from just someone that's just doing one thing to being able to do more than one thing.

Scott Hebner

>> Right.

Scott Hebner

>> So I'll give an example. We have folks now that just used to be QA, working down the line through test cases, testing the solution. Now stepping into kind of BA roles. We have BA roles stepping into functional consulting roles and taking on some PM duties. And AI is giving them the ability to say, I can actually help to create those deliverables and actually become more of a T-shaped consultant versus an I-shaped consultant. Because I think what we're seeing is diversity of skill set is what our clients are asking us for. They're not asking for more bodies on a project. They're asking for more specialized resources that can do more than one thing.

Scott Hebner

>> So it's giving superpowers.

Scott Hebner

>> It's giving superpowers and it's closing gaps, right? and everyone, and it's giving you an ability to kind of practice, dry run. It is your coach as you're going through your consulting engagement, whether it's the project context you need or the broader context of the consulting practice.

Scott Hebner

>> So if you're in this business and you're a consultant, this AI is a good thing.

Scott Hebner

>> It's an amazing thing. I do think one of the things that we need to do is spend more time getting our junior consultants. I think the reason why some of your older consultants that have just had more experience knowing what questions to ask and how to prompt AI to get results. The thing that we need to do as a consulting industry is make sure that we're bringing our junior talent along for that as well. Because it's interesting, my daughter's 17. She started to use Claude in school and just use it to help with homework. It's interesting to see the questions that she asked versus the questions that I ask. And I think helping people know what are the right questions to ask to get the value out. there's a garbage in, garbage out scenario. So helping to train people on what's a good prompt, what are the right questions to ask is something as a consulting industry we're going to have to face with our more junior talent coming in and learning this technology.

Scott Hebner

>> Yeah, we talked a little bit before we got on the air here about our time at IBM and yeah, doing a lot of CMO kind of marketing stuff. It's kind of interesting, actually behind the scenes right now as we're talking, I'm actually building agents with Claude. Yeah, it's writing the code right now. So I'm a marketing guy who's now building real code and real applications. It's fascinating what you can now do, incrementally you just learn more and more and more. I would imagine every profession, those— it's going to be those that don't adopt AI can be replaced by those that do. It's not that these jobs are going to go away. That's been my overall idea.

Scott Hebner

>> Yeah, it's going to be a shift of talent from time and materials legacy I-shaped consultants to a more high-skilled diverse consultant that can kind of plug in and do different things. And some of the opportunity that we're seeing, you no longer need 3 months of an engagement to do discovery work. To start to prove value very quickly. So we're now starting to do our forward deployment style engagements where we actually have a consulting team on the ground working with a client, and we meet with a client on one day, and the next day we're turning around a highly tuned concept of what they're looking for. Not a bunch of user stories and technical documentation.

Scott Hebner

>> It's—

Scott Hebner

>> you can iterate so much quicker towards solutioning, which is really helping to kind of move forward solutions at lightning speed. This is where I think the unlock is for consulting companies. Yeah, no, you have to rethink your traditional model.

Scott Hebner

>> Yeah, just transforming how everything—

Scott Hebner

>> 100%.

Scott Hebner

>> So, last question, because I know we have to wrap up here. it seems to me, covering this industry, that with all transformations, you get off to this rapid start in the maturity, and then it slows down because people are getting a little risk-averse, and the whole trust issue and stuff like that. But if you were talking to a CEO, right, what would you tell them about how it's time to make this AI transformation. Don't be fearful of it. What would be— what would you tell a CEO that's reluctant to really pour on the gas?

Scott Hebner

>> So it's a great question. We're having a lot of conversations with clients because we do AI advisory for our clients. So the thing that I've seen in the year 2026, as we're recording this, 2024, I think B2B AI was starting to get some grounding. It was immature. 2025 was kind of the year of pilots and experimentation. And I think a lot of those pilots actually did not result in value, as some of the data we heard coming out of the keynote yesterday. 2026, the conversations we're having now with CEOs is that they are having pressure from their board to become more AI-first as a company. And what I would tell them is it's less of a technology problem. Most companies have all of the technology. They're using Anthropic, they're using OpenAI, they're using platforms like Certinia. But most of them fail on that strategy. And I credit some of the work that we did with Certinia when we were putting in our implementation was thinking through that strategy. How do you think through where the business value is? How do you really understand your users? How do you think through that end-to-end experience? And then where do you map the pain points in your business to drive the strategy? And then you need to create an approach that then creates agents at scale. What we're finding is deploying one-off agents that do one thing at a time doesn't drive business value. What drives business value is creating a strategy and approach and a roadmap to executing and building agents. The last thing I'll say is we did a presentation this week at Dreamforce with a customer. You also need to fire agents. Yeah, we're treating them like performance reviews. So just as you would onboard an employee and go through getting them in the job and then offboard them if they weren't doing the job effectively, the same is true for agents. We're finding some of our agents driving high value. And some just sucking resources and not actually creating value. So have a framework for looking at the agents that are driving and measuring business value and retiring the ones that are not. Because I think that orchestration and connecting them is where the flywheel gets going.

Scott Hebner

>> Yeah, it's very consistent with what I've been kind of witnessing as I talk to people, is that it's it's transitioning from a technology phenomenon into an economic and sort of digital labor transformation phenomenon, coworkers, the superpowers and all that. So, all right, well, this has been a great conversation. Very informative. I appreciate you taking the time to be here.

Scott Hebner

>> Awesome. Thank you.

Scott Hebner

>> You bet. You bet. All right, well, we'll be back here at Dreamforce 2026 with our continuing coverage. This is theCUBE, and stay tuned. We'll be right back.

James Davidson, Neocol

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Scott Hebner

>> Hello everyone. Welcome back to theCUBE's continuing coverage of Dreamforce 2026, where we're focused on the professional services industry. And I'm Scott Hebner, Principal Analyst for Enterprise AI at theCUBE Research. Once again, thanks for tuning in. Well, I'm thrilled today to have James Davidson, who is the CEO of Neocol here with me., and we're going to continue our conversation around what's happening with professional services. So thanks very much for taking the time.

Scott Hebner

>> Yeah, thanks for having me.

Scott Hebner

>> Yeah, so why don't we start and just spend a little bit of time, giving our audience an overview of Neocol and what you guys all do and your relationship to Certinia.

Scott Hebner

>> Awesome. So, yeah, Neocol is really focused on the quote-to-cash business. So kind of end-to-end, we work on the Salesforce platform and we really see ourselves as revenue transformation experts. So all the systems that touch revenue, kind of the lifeblood of most businesses, We're focused on implementation services around the Salesforce platform, specifically Revenue Cloud, Sales Cloud, Partner Cloud, Data Cloud, and Agentforce, or now AI Force. Yeah, just at the conference. And then really in terms of how we help our clients, we have kind of 3 parts of our business, kind of advisory and business transformation services. So how to think about where the strategy and opportunity is with revenue transformation, build services. How to really deploy and scale Salesforce, Databricks, and AI platforms like Claude for business value. And then we have a managed services side of our business as well. So we help our clients manage their environments, ongoing break-fix work, and enhancements of their Salesforce environments.

Scott Hebner

>> What's been your observation so far here at the show? You like the keynote and what Marc

Scott Hebner

>> Benioff—I loved it. I think we see a massive opportunity around what we're calling next-generation experiences. So when we heard about Agentforce, We've already been working with Agentforce with clients and implementing. We say it's a rebirth of AI and UX over the top of the Salesforce platform. We're building solutions with our customers already. So really hearing the validation of Agentforce made us feel like we're investing our resources in the right things.

Scott Hebner

>> Yeah, I think they're keeping it simple with the stack. They are. The stack

Scott Hebner

>> just—it increases every year.

Scott Hebner

>> Yeah.

Scott Hebner

>> But it's exciting to see their innovation of the platform. And I do feel that Salesforce is back. Obviously, they had a— challenging time with SaaS apocalypse, but we're seeing them double down on the data. The business process is really key and driving AI adoption. So I thought the messaging was right on.

Scott Hebner

>> Yeah, I did too. I thought it was very inspiring. And I noticed he wore a suit.

Scott Hebner

>> Yeah.

Scott Hebner

>> Marc Benioff.

Scott Hebner

>> Yeah.

Scott Hebner

>> So he's always changing things up.

Scott Hebner

>> Yeah, he's changing things up every year.

Scott Hebner

>> Yeah.

Scott Hebner

>> Yeah.

Scott Hebner

>> So you recently became CEO.

Scott Hebner

>> Yeah.

Scott Hebner

>> Right. And I noticed that you had driven a total AI transformation within your organization. I always like to ask, what did you learn from that? what was the philosophy behind it? it's always interesting to hear the transformation stories after they've been completed, or at

Scott Hebner

>> least—So it's a great, great question. I think professional services is having a moment and it's— we're really having to rethink our business model top to bottom. So at Neocol, traditionally, time and materials business, labor-based consulting. I think what we are seeing more and more is clients approaching us. Now, everyone wants quicker, faster, cheaper. And so we're really faced with seeing the business model of professional services changing in front of our eyes and really looking for a way to do projects quicker but at high quality with humans and agents. That's really where we're a Certinia PSA customer. So we use that for workforce management and professional services side of our business. And then we were lucky enough to get connected with Moonnox, which is now part of Certinia, part of the Veda platform. When we started doing evaluation to say, how do we take all the knowledge, the best practices and experience we have from years of doing these Salesforce implementations and turn that around into a more AI-first approach for our clients? So that was our original hypothesis. How do we go more AI-first and enabled? Because customers want projects quicker, cheaper, faster. We ran a pretty extensive evaluation process and were really looking at the platforms that were out there and what we really loved about the Veda platform was the ability to take our knowledge, take our skills, and then create agents for our different pockets of our consulting organization, whether that was our sales, presales, delivery, finance, or ops, and then start to connect those agents to drive value. There are a lot of out-of-the-box agents that just gave us capabilities that we needed right away. So RFPs are something no one likes to do, we have a massive repository of those. We now have the ability with their platform to take an RFP and respond very quickly. You need to trust but verify that and make sure the content is of high quality. But the more that we put into this platform, the higher the value we see. The other side of this for us as well is instead of thinking about deploying AI individually, we credit Certinia with this and coming in and really helping us think through that entire professional services journey as kind of an end-to-end experience.

Scott Hebner

>> Right.

Scott Hebner

>> Because if you think about it, it's a team sport. Consulting works best when sales, is working with delivery, is working with finance, is working with ops. And so the way that we really thought about that was end-to-end, finding where the biggest pain point was, whether it was on sales scoping and estimation, whether that was running client workshops, facilitating that and transferring those workshop notes into requirements, all the way down to build. We managed to think through that end-to-end and see where the pain and the human labor was. And for us, the vision is How do we actually take our people and redeploy them to high-value activities, not low-value activities where you're spending too much time? So that was some of the hypotheses that we had going into this.

Scott Hebner

>> Yeah, I covered the Moonnox acquisition. I wrote a research paper on it. I was really impressed with the capabilities, and even prior to that, I've been a big advocate of evolving from knowledge graphs into what I called context spaces.

Scott Hebner

>> Context-based, yeah.

Scott Hebner

>> The ability to maintain the context across the project even when it's changing due to meetings and stuff like that.

Scott Hebner

>> Absolutely. You found that it's a game changer. And I think everyone uses this technology differently. For me, you take the software, you deploy the software, but I think everyone needs to have their aha moment. And for me, before I became CEO, I was Chief Strategy Officer, and I'd oversold my capacity. So in one week I had 4 engagements hit all at the same time. Highly strategic advisory conversations that I need to have with 4 separate customers. And if I go back in a time machine to 2020, this would have been 40 hours per presentation, sweating the pixels, the content, the layout of the deck, the storyline. With this technology, I was able to focus more on the storyline and have all the context of the conversations I'd had with the customer.

Scott Hebner

>> Yeah.

Scott Hebner

>> and within about 20 hours I'd completed 4 of those deliverables that if I went back to 2020 would probably have been 20 to 30 to 40 hours' worth of work.

Scott Hebner

>> That's you personally?

Scott Hebner

>> Me personally.

Scott Hebner

>> Yeah.

Scott Hebner

>> That was the unlock moment for me where I'm like, that's just one use case. And if you deploy that across your entire workforce, whether you're writing stories, whether you're creating technical documentation, RFPs, it's an unlock.

Scott Hebner

>> So what was the big observation on, where people are now spending their time compared to maybe 2020?

Scott Hebner

>> I think you're spending more of the time, like consulting is a people business.

Scott Hebner

>> Yeah.

Scott Hebner

>> The more you're spending time with your people, whether it's your project team or your client, you're adding value. You're not adding value when you're just sitting there formatting a document, right? So I think what we find the deployment of time being now on the value is to spend time on the high-value activities, which are client-facing, icing on the cake, but not doing the kind of manual work of, taking a spreadsheet, having to find themes and patterns in that and organizing that information into buckets. I went back to workshops that I'd used to run as a consultant, journey mapping, Post-it notes that you had to transcribe and just the manual labor in doing that to now that piece is taken away. So you can really focus on the value story and the opportunities for your client in the solution. Not so much just admin work.

Scott Hebner

>> Yeah.

Scott Hebner

>> Yeah.

Scott Hebner

>> And you mentioned the people business, which has been a theme here. And I know you have a term that you use, which is, what is it? Human-led AI.

Scott Hebner

>> Yep.

Scott Hebner

>> Centered or AI.

Scott Hebner

>> Absolutely.

Scott Hebner

>> So in practice, what does that mean for you guys as you do your work?

Scott Hebner

>> So every consulting company has a methodology of how they think through their process from sales all the way through delivery. So human-led AI first to me is, How do we take every step of the consulting methodology that we have and overlay agents to actually support our people in doing their work? So for sales, helping write proposals, create contracts, statements of work grounded in the context of the conversations we've had with the customer, it's an unlock. You're no longer it's no longer guesswork or going back through someone's notes or guessing at this. The ability to have those call transcripts feed the platform for consultants. Taking that context from sales into delivery and using that to create deliverables and assets that are highly aligned, that we're seeing on the projects where we're using this technology, it's reducing scope creep, it's reducing disconnects between teams, and you no longer have this concept of sales to delivery handoff. You just have context that gets better the more you get into the project with the client. So the methodology for us is one with humans and agents. Across every step of our delivery methodology to deliver project work cheaper, faster, quicker. That's really what clients are looking for in the age of AI-first consulting.

Scott Hebner

>> Yeah, and I'm curious to hear your observation or your view on the current theme that Certinia has. as I've been following for the last year, it started off with the need to orchestrate across the entire end-to-end and then around Services Week, I think it was late spring, it was about judgment. AI brings efficiency, but you still need human judgment.

Scott Hebner

>> Absolutely.

Scott Hebner

>> And now it's be certain. And the more certain you are in the actions you're taking, the better the outcomes. And then when you hear Marc Benioff in the keynote talking about the evolution from probabilistic to deterministic, it kind of fits nicely with certainty, right? You got to be certain on what you know, what you're doing. And you take their platform and what you're doing and you add in the context That's sort of where we're heading, right? Is more and more certainty in the output.

Scott Hebner

>> We are. And I think you're— the way I use AI, I think we're all using it maybe a little differently, but I think it is a coach that knows you, knows the context. And that's really what we see in this platform is that sometimes in consulting, when you're on the line trying to get a deliverable over the line and you don't have access to everyone on your team and you're the consultant on the ground having to make a decision, you're now backed up by this massive repository of context and knowledge for the project that you're doing, all the collective best practices that you have in the organization, that it's a true unlock. And what we're seeing is it takes a junior consultant and gives them the ability to be more senior. And for a senior consultant, it's just unlocking value in being much more prepared or organized for the conversations you're having. And then a cautionary tale though, I think the human in the loop or trust but verify. If you only just say create a consulting deliverable top to bottom and fire that out to your client, you can get sometimes hallucination, AI slop. So I think that you still as a human need to spend time inspecting the quality of the deliverable. Yeah, but some of the admin work I would say is going away with this technology, which is fascinating. And then for our teams, how do we take that time to deploy that to high value activities versus the low value activities that no one likes doing, but always had to do. It's part of the job.

Scott Hebner

>> Yeah, and there seems to be obviously a bigger narrative in the industry, the overall industry, not professional services, but just tech, and probably just society that AI is going to take everyone's jobs, and now you have this thing that's going to kill us all. But back to the job thing, one other thing I've learned in the conversation so far here is that in the professional services, AI is actually creating more jobs because you do more projects, things are happening faster with higher quality. Yep. What's your view about the job?

Scott Hebner

>> I 100% align with that. So we're seeing the remit of a consultant. Are you aware of T and I-shaped consulting? So I think what we're seeing is this great opportunity. So if you're an I-shaped consultant, you might say I was always a business analyst. I meet with a client, I sit in meetings, I take notes. I write stories, I move those stories into Jira or whatever the platform is, and then I execute the project and I ride along. What we're seeing is clients are pushing us and our consultants are pushing us to say, I want to do more than just be pigeonholed into doing one thing. So with AI, I think it's changing the shape of a consultant from just someone that's just doing one thing to being able to do more than one thing.

Scott Hebner

>> Right.

Scott Hebner

>> So I'll give an example. We have folks now that just used to be QA, working down the line through test cases, testing the solution. Now stepping into kind of BA roles. We have BA roles stepping into functional consulting roles and taking on some PM duties. And AI is giving them the ability to say, I can actually help to create those deliverables and actually become more of a T-shaped consultant versus an I-shaped consultant. Because I think what we're seeing is diversity of skill set is what our clients are asking us for. They're not asking for more bodies on a project. They're asking for more specialized resources that can do more than one thing.

Scott Hebner

>> So it's giving superpowers.

Scott Hebner

>> It's giving superpowers and it's closing gaps, right? and everyone, and it's giving you an ability to kind of practice, dry run. It is your coach as you're going through your consulting engagement, whether it's the project context you need or the broader context of the consulting practice.

Scott Hebner

>> So if you're in this business and you're a consultant, this AI is a good thing.

Scott Hebner

>> It's an amazing thing. I do think one of the things that we need to do is spend more time getting our junior consultants. I think the reason why some of your older consultants that have just had more experience knowing what questions to ask and how to prompt AI to get results. The thing that we need to do as a consulting industry is make sure that we're bringing our junior talent along for that as well. Because it's interesting, my daughter's 17. She started to use Claude in school and just use it to help with homework. It's interesting to see the questions that she asked versus the questions that I ask. And I think helping people know what are the right questions to ask to get the value out. there's a garbage in, garbage out scenario. So helping to train people on what's a good prompt, what are the right questions to ask is something as a consulting industry we're going to have to face with our more junior talent coming in and learning this technology.

Scott Hebner

>> Yeah, we talked a little bit before we got on the air here about our time at IBM and yeah, doing a lot of CMO kind of marketing stuff. It's kind of interesting, actually behind the scenes right now as we're talking, I'm actually building agents with Claude. Yeah, it's writing the code right now. So I'm a marketing guy who's now building real code and real applications. It's fascinating what you can now do, incrementally you just learn more and more and more. I would imagine every profession, those— it's going to be those that don't adopt AI can be replaced by those that do. It's not that these jobs are going to go away. That's been my overall idea.

Scott Hebner

>> Yeah, it's going to be a shift of talent from time and materials legacy I-shaped consultants to a more high-skilled diverse consultant that can kind of plug in and do different things. And some of the opportunity that we're seeing, you no longer need 3 months of an engagement to do discovery work. To start to prove value very quickly. So we're now starting to do our forward deployment style engagements where we actually have a consulting team on the ground working with a client, and we meet with a client on one day, and the next day we're turning around a highly tuned concept of what they're looking for. Not a bunch of user stories and technical documentation.

Scott Hebner

>> It's—

Scott Hebner

>> you can iterate so much quicker towards solutioning, which is really helping to kind of move forward solutions at lightning speed. This is where I think the unlock is for consulting companies. Yeah, no, you have to rethink your traditional model.

Scott Hebner

>> Yeah, just transforming how everything—

Scott Hebner

>> 100%.

Scott Hebner

>> So, last question, because I know we have to wrap up here. it seems to me, covering this industry, that with all transformations, you get off to this rapid start in the maturity, and then it slows down because people are getting a little risk-averse, and the whole trust issue and stuff like that. But if you were talking to a CEO, right, what would you tell them about how it's time to make this AI transformation. Don't be fearful of it. What would be— what would you tell a CEO that's reluctant to really pour on the gas?

Scott Hebner

>> So it's a great question. We're having a lot of conversations with clients because we do AI advisory for our clients. So the thing that I've seen in the year 2026, as we're recording this, 2024, I think B2B AI was starting to get some grounding. It was immature. 2025 was kind of the year of pilots and experimentation. And I think a lot of those pilots actually did not result in value, as some of the data we heard coming out of the keynote yesterday. 2026, the conversations we're having now with CEOs is that they are having pressure from their board to become more AI-first as a company. And what I would tell them is it's less of a technology problem. Most companies have all of the technology. They're using Anthropic, they're using OpenAI, they're using platforms like Certinia. But most of them fail on that strategy. And I credit some of the work that we did with Certinia when we were putting in our implementation was thinking through that strategy. How do you think through where the business value is? How do you really understand your users? How do you think through that end-to-end experience? And then where do you map the pain points in your business to drive the strategy? And then you need to create an approach that then creates agents at scale. What we're finding is deploying one-off agents that do one thing at a time doesn't drive business value. What drives business value is creating a strategy and approach and a roadmap to executing and building agents. The last thing I'll say is we did a presentation this week at Dreamforce with a customer. You also need to fire agents. Yeah, we're treating them like performance reviews. So just as you would onboard an employee and go through getting them in the job and then offboard them if they weren't doing the job effectively, the same is true for agents. We're finding some of our agents driving high value. And some just sucking resources and not actually creating value. So have a framework for looking at the agents that are driving and measuring business value and retiring the ones that are not. Because I think that orchestration and connecting them is where the flywheel gets going.

Scott Hebner

>> Yeah, it's very consistent with what I've been kind of witnessing as I talk to people, is that it's it's transitioning from a technology phenomenon into an economic and sort of digital labor transformation phenomenon, coworkers, the superpowers and all that. So, all right, well, this has been a great conversation. Very informative. I appreciate you taking the time to be here.

Scott Hebner

>> Awesome. Thank you.

Scott Hebner

>> You bet. You bet. All right, well, we'll be back here at Dreamforce 2026 with our continuing coverage. This is theCUBE, and stay tuned. We'll be right back.