9-Figure AI ROI across 3,000+ Employees:
How JLG is Becoming the Agentic Leader in Insurance Building with Fluency

“Making a real impact with AI depends on deeply understanding what’s actually happening operationally in your business. Fluency is foundational to that. It’s how we understand where to focus, where we get the best impact, and where AI will actually create value.”
Nick Carnell, CEO — Johns Lyng Group
Key Highlights
40%
Capacity recaptured for back-office teams
30%
Savings on billable hours
100+
AI workflows deployed
$100m+
ROI opportunities identified
For Johns Lyng Group, Australia’s largest integrated building services group, complexity is the daily reality across insurance restoration, commercial construction, strata management, and disaster recovery.
Fluency gave Johns Lyng Group the definitive roadmap and execution for their AI strategy. Something that at their scale had simply never been possible before.
“I looked at our business, the complexity, the noise. I didn’t know where to begin solving challenges we’d had for the best part of ten years.”

Slow, Manual Process for Mission Critical Work
Across 120 operating entities, more than a hundred people were manually copying claim information from JLG’s internal system into insurer portals, every single day. The same task, executed differently in every region, with no single source of truth and significant room for error. It wasn’t a people problem. It was a structural one that had compounded for the better part of ten years. CEO Nick Carnell saw it firsthand.
“It looked like a massive duplication of effort. Huge room for error. Copying data from one platform to another, working outside systems in Excel spreadsheets. That’s lag, cost, inefficiency.”
What Fluency Found: The Portal Update Team
Over a hundred people across the country were doing the same job every day: taking claim status information from JLG’s internal system and manually entering it into insurer portals, one update at a time. Accurate information already sitting in one system, copied by hand into another, repeatedly, across every region.
“When a work request came in by email, somebody would translate what it said into a form in our system to register the job. That’s basically copying information from one place into another. Understanding how much time people spend doing that is what allows us to focus on exactly where to automate.”
Automated Claim Triage
Fluency discovered a high-volume claim intake process where staff were manually interpreting incoming requests and entering unstructured information into JLG’s systems by hand, thousands of times a week. Fluency observed it, quantified the cost, and surfaced a complete automation initiative: what to build, why it would return value, and exactly where in the workflow to deploy it. The JLG team had a ready-to-execute opportunity.
Getting Clarity Into Operations For the First Time
At the centre of JLG’s operations sit the Finance and Operations teams. The work is heavily regulated. Accuracy is non-negotiable. And the cost of an error, whether a miscoded claim, a missed compliance obligation, or a subcontractor payment processed incorrectly, is not just financial. It affects the insurer, the subcontractor, and ultimately the person waiting on the other end of the job.
Fluency changed what that work looked like for the people doing it. Removing the repetitive, accuracy-dependent overhead didn’t just improve operational metrics. It returned time and attention to the work that actually required human expertise and human empathy. As Nick puts it:
“They’ve got more time for empathy, to listen, versus just duplicating information from one system to another. They get a real kick out of having that impact on someone who is vulnerable, unsure, confused around the next steps.”
From Uncertainty to AI Execution
Johns Lyng Group are at the frontier of software innovation, building Beyond, a new internal platform to automate operations across the business. The goal was clear. What was missing was the evidence to decide where to build first. Jesse describes the problem before Fluency.
“There was clearly opportunity to make a big impact, but it was hard to quantify and hard to measure whether our approach was right. We were sitting and watching how people do things, doing the before and after manually. Fluency lets us do that quickly and easily. Speed is everything.”
Fluency became the foundation for JLG to objectively define the highest-value path for automation and AI, informing a ranked, evidence-backed roadmap that Jesse’s team could execute against with confidence.
“Fluency is foundational to how we think about AI investment. It gave us the clarity to define what to build, where to focus, and how to prove the return.”

The conversation inside JLG shifted as a result. Where before, teams were asking what AI could do for them, they were now asking how quickly they could move.
“The conversation goes from ‘what are you going to do?’ to ‘how quickly can you do it?’”
Proving Business Impact to the Board
For a business of JLG’s size and complexity, the most important question was how to prove the impact of investment. Nick explains how Fluency changed that conversation.
“Fluency helped us understand our ROI much more clearly. It articulated what steps could be removed, what speed could be achieved, and what that would equate to in market share gains.”
Fluency didn’t just surface the inefficiency. It quantified it. Steps removed, speed gained, business outcomes, cost reduction. Each one traceable back to what the data showed.
“When I talk to the board about the ROI of what we’re doing together, it’s a nine-figure sum. Significant in top-line revenue growth, but also the savings the business can derive.”
Becoming the Agentic Leader for Insurance Services
JLG isn’t running an AI experiment. It’s building AI-first capability at scale across the entire organisation, with a clear-eyed view of what the technology is for and a financial model to back every decision.
“We’re starting where we see the greatest opportunity, but it’s never-ending. This is a journey that’s just beginning.”
Jesse sees it the same way.
“New problems surface, operations change. Fluency is how we keep improving: once we solve a problem and give our people better tools, how do we keep updating, keep getting better?”
For a business that spent the better part of ten years unable to see how its own operation ran, the picture is now clear. The roadmap that follows represents one of the largest AI transformation opportunities for insurance building services.