AI at Datacom isn’t an experiment: it’s a strategic lever for productivity, transformation, and long-term value, says Joe, who plays a central role in aligning Datacom’s application investments with business outcomes.
EASA supports the critical platforms behind Datacom’s IT outsourcing and managed services — ensuring they are secure, scalable, and high-performing. This includes everything from IT service management (ITSM) and monitoring tools to automation and self-service systems that power daily operations across Australia and New Zealand.
Joe’s focus is now on the next evolution: weaving AI into the fabric of how Datacom designs, builds, and operates enterprise applications. “This isn’t just about adopting new tools — it’s about using AI as a lens to rethink how we deliver value, optimise outcomes, and prepare our platforms for the future,” he says.
Why AI and why now?
“We’re not pursuing AI because it’s trendy. We’re doing it because we believe it will fundamentally shift how we work,” says Joe.
“Whether it’s reducing people’s drudge work, enabling us to make better decisions, or unlocking insights from data we already have — AI is a force multiplier.
“That’s the north star guiding Datacom’s internal AI adoption: how can we make every person, team, and process more productive?”
At the heart of Datacom’s approach is a bold ambition: to surgically dissect how we work today and reimagine what’s possible using AI, he says.
“We’re not just layering AI on top of existing workflows — we’re taking a step back and asking, if we were starting from scratch with today’s technology, how would we design this process?”
This mindset shift is more than just improvement — it’s about transformation. By understanding the full capabilities of modern AI, Joe’s team is exploring what is possible, which opens doors to redesigning processes in ways that were previously unimaginable — removing complexity, reducing effort and unlocking speed at scale. But like anything worthwhile, there are challenges.
Perhaps the biggest barrier to AI adoption isn’t technology — it’s people.
“We’re asking people to reimagine their roles, not replace them,” says Joe. “The future of work at Datacom isn’t about humans versus AI — it’s humans with AI.”
That’s why his team is also focused on driving a mindset shift across the organisation. From internal enablement sessions to hands-on use case workshops, the goal is to equip people with the confidence and skills to use AI tools meaningfully in their day-to-day work.
“AI is not a ‘nice-to-have'. The ability to work with and understand AI is a core skill for the modern workforce,” Joe says. “We’re making sure our people are ready.”
“It’s easy to build a great proof-of-concept (POC). It’s much harder to scale across a complex enterprise,” says Joe.
“We’ve seen this again and again. A use case looks incredible in isolation, but once you try to ‘productionise’ it — connect it to real data, secure it, make it work across different teams—the complexity balloons."
To address this, Datacom is focused on security-first, scale-ready development. Joe’s team works closely with the CISO's (chief information security officer's) office to ensure AI solutions are compliant, trusted, and built to last.
“Clean data is a rarity but in the context of AI, dirty data is no joke,” says Joe. "Data that could power valuable AI use cases is messy, siloed or incomplete.”
Research commissioned by Datacom in New Zealand has found that just 9% of New Zealand businesses consider 100% of their data to be ‘clean’ and one third of companies think that half or less of their broad data set is free of issues.
So where to start? Datacom tackles the dirty data challenge by turning the problem on its head: start with the outcome, then identify the data that matters.
“Instead of boiling the ocean, we laser in on specific use cases with clear value. Then we work backward to understand what data we need and how we can clean, enrich, or augment it—often using AI itself as a tool to help.”
A recent internal project used this exact method, applying large language models to summarise and extract key insights from operational data that would otherwise take hours of human effort.
"AI is transformative, but the most useful way to think of it is as normal technology rather than a separate entity, which is how it is often portrayed", says Joe. “Electricity and the Internet were transformative, but they are also everyday technology. It is up to us to decide how to use it and control it.”
