When we talk about AI in business, the conversation usually revolves around marketing, content, development and, of course, automation.
But over the past year at NEXA, I've seen another side of it.
AI has changed what's possible in Operations.
In my role, I'm close to a lot of the everyday friction across the business. I see where processes don't work as well as they should, where people struggle to find information, and where systems force teams to work around them rather than with them. The problem is that spotting these issues has always been much easier than fixing them.
Traditionally, the options were fairly predictable: buy another piece of software, adapt the process to whatever the existing platform allows, or put together a brief and wait for development resources.
AI has started to change that.
Two of the best examples are Momentum and the NEXA Handbook.
For years, we used an established project management platform for timesheets, resource planning and reporting. There was nothing particularly wrong with it. The problem was that we were paying for a lot of functionality we didn't really use, while some of the things that mattered most to us still didn't work exactly the way we wanted them to. So instead of immediately looking for another SaaS platform, we started asking a different question:
Why don't we build something around the way NEXA actually works?
That eventually became Momentum.
Momentum started as our internal project and resource management platform, giving us visibility across project planning, team capacity, time tracking, effort and project profitability. But it has since developed into something much more valuable: an operational intelligence tool for the business.
Momentum takes the information we're already generating across our projects and turns it into robust dashboards and AI-generated summaries of business performance. Instead of simply recording hours or showing us project data, it helps us understand what that data is telling us. We can see how projects are performing, where effort is being spent, how resources are being utilised and how that translates into the commercial performance of the work we're delivering.
And because the intelligence is built around our own operational and commercial logic, this isn't something we could simply buy off the shelf. A generic platform can give us dashboards. What we wanted was a system that understands how NEXA measures performance. That's where AI became particularly powerful.
It shortened the journey from “this is what we need” to having something we could see, test and improve. I could take what I understood from an Operations perspective, define the logic, work through different scenarios and prototype how things should work. From there, working closely with the NEXA AI Lab team, we could turn those ideas into something real, test them and keep refining them together.
That collaboration was important. I understood the operational problem and what the business needed, while NEXA AI Lab brought the AI and development expertise to turn that thinking into a working platform. Together, we were able to bridge the gap between operational thinking and technical execution much faster.
Now, when we need something different from Momentum, the first question isn't:
“Can the software do this?”
It's:
“What do we want to know, and how do we want to use it?”
That's a very different position to be in.
Momentum replaced an existing system. The Handbook solved a completely different problem. Like most growing businesses, we had information everywhere.
Presentations. Documents. Drive folders. And, inevitably, quite a lot sitting in people's heads. If someone joined NEXA and wanted to understand who did what, how a department worked, which tools we used or where to find something, there wasn't one obvious place to go. So we took the same thinking and applied it to our internal knowledge.
Using AI as part of the process, and working with the NEXA AI Lab team, we structured and built the NEXA Handbook, a central hub for our people, departments, processes, policies, tools and ways of working.
For me, the thinking behind it was quite simple: Internal knowledge shouldn't just be a document. It should be a product. It needs an owner. It needs to stay current. And most importantly, people need to actually be able to find and use the information inside it.
When people talk about AI in Operations, the conversation usually starts with automation: saving time, removing manual tasks and making processes faster. Those are obvious benefits, but for me the bigger change has been what AI allows someone in Operations to do. I'm close enough to the business to understand many of the problems. What I haven't traditionally had is the technical capability to take those problems much further myself. AI has started to bridge that gap.
I can explore ideas, work through the logic, prototype solutions and test the thinking before taking it further. That means when I work with the NEXA AI Lab team, I'm not simply handing over a problem. We can start with a much clearer idea of what the solution should deliver.
For me, that's the real opportunity: AI doesn't just help Operations work faster. It helps us solve problems we previously couldn't solve ourselves.
There was also a very real financial benefit. Replacing our previous project management platform removed more than $20,000 in annual licensing costs. That's significant, especially when you consider how quickly SaaS subscriptions can build up across a business. But I still don't think that's the biggest win.
The bigger win is that we now own the logic and intelligence behind these systems. Momentum doesn't just capture our data. It helps us understand it. We can continue developing the dashboards, reporting logic and AI summaries around the questions that matter to NEXA, rather than being limited to what an off-the-shelf platform thinks we should measure.
That flexibility, and the business intelligence it gives us, has far more value than the licence saving alone.
One thing I would add is: don't start with AI. Start with the problem.
We didn't decide that NEXA needed an “AI project” and then go looking for somewhere to use it.
We had real operational problems and started exploring whether there was a better way to solve them.
We also stopped assuming that every gap in the business needed another subscription.
Sometimes buying software absolutely makes sense. Sometimes the answer is simply improving the process. But AI-assisted development has added another option: maybe we can build exactly what we need.
And just because AI makes building faster doesn't mean you skip the boring but important stuff. Momentum still needed proper QA, testing, feedback and ownership before we rolled it out. AI helped us move faster. It didn't replace the need to understand what we were building and why.
AI isn't changing the purpose of Operations, but it is changing what we're capable of doing.
Momentum and the NEXA Handbook are two examples of that at NEXA. They came from real operational problems, combined with the ability to use AI and development expertise to build solutions around what the business actually needed.
And in Momentum's case, we've gone a step further. We're not just building a system to manage the work. We're building intelligence around the data that helps us understand how the business is performing.
That's probably the biggest shift for me.
When I see an operational problem now, I'm not just thinking about how we can work around it.
I ask myself: “Can we find a better way to do this?”