Quanton rebrands as AI partner to take pilots to scale

Quanton has repositioned itself from an automation specialist to an AI transformation partner, as organisations across Australia and New Zealand struggle to move AI projects beyond pilots and early deployments.

The Auckland-based firm launched New Zealand's first robotic process automation programme in 2016 and estimates it has helped organisations in the region save more than five million hours through automation and process improvement. It is now placing greater emphasis on AI programmes that reach production and scale across the organisation.

The shift comes as expectations rise for AI's economic contribution. Microsoft and Accenture research estimates AI adoption could add $76 billion to New Zealand's economy by 2038. Even so, many organisations report slow progress in turning experimentation into material operational change.

From pilots to production

Across the market, many AI initiatives remain limited in scope. Organisations often run proofs of concept, deploy chatbots, or publish internal strategy papers. Quanton argues the main blockage comes later, when leaders try to extend a working pilot across teams, processes, and systems.

"Everyone's talking about AI strategy and running pilots. But it's in the execution that most initiatives stall-in the gap between PowerPoint and production. That's where millions of dollars in value is being left on the table, and it's the gap we've evolved specifically to close," said Garry Green, Quanton's managing director.

Research cited by Quanton points to mixed signals in executive sentiment. IDC has found 66% of CEOs report tangible benefits from AI initiatives. Yet many organisations still lack a repeatable approach for moving from early success to broad deployment. Quanton also cited an industry statistic that only 23% of organisations have successfully scaled AI systems that deliver business transformation.

A broader service scope

Quanton says its work now extends beyond deploying automation tools to a broader transformation remit, spanning advisory, implementation, and enterprise scaling. It also highlighted QLOAD, a methodology it describes as a framework for assessing AI readiness and mapping the path from pilot to production across people, process, data, and technology.

Green said organisations need to treat AI as more than a technology rollout. "When we started in 2016, we focused on robotic process automation-taking repetitive tasks and automating them. What's happening now is exponentially more sophisticated. AI systems can reason, plan, and act autonomously. But most organisations are approaching this with old playbooks-treating AI implementation as an IT project rather than fundamental business transformation," he said.

Quanton positions its process background as a differentiator, particularly in environments where data is inconsistent and handovers between teams create delays. It says this experience comes from working at detailed operational levels in client organisations, where automation and AI outcomes often depend on how work is structured and measured.

Barriers beyond technology

Quanton argues organisations face barriers that combine skills, data, and workforce issues. It cited research indicating 97% of organisations in Australia and New Zealand lack AI competency, and findings that 58% of CIOs point to data infrastructure as the primary barrier to implementation.

It also highlighted the human impact of rapid technology change, citing research that 59% of employees report stress about the pace of AI advancement. That pressure can surface as resistance to transformation programmes or reluctance to change established ways of working.

"Technology is the easy part. The hard part is understanding where the real value sits in your business, how to change the way people work, and how to build capability that lasts. Most AI initiatives don't fail because the technology doesn't work. They fail because organisations skip the hard work of actual transformation," Green said.

Mid-market positioning

Quanton is pitching its approach to organisations that want practical delivery as well as advice. It contrasts its model with larger consulting firms that focus on strategy and operating model work without staying through implementation.

"We don't build frameworks in isolation and then test them on clients. We build them with clients, solving real problems as they happen. These lessons come from the ground, not a laboratory," said Ursula Riemer, Quanton's strategic engagement director.

Riemer also framed the pitch as a better fit for mid-sized organisations. "The Big Four have impressive credentials and global resources. But when you're a mid-market company trying to implement AI, you don't need a global playbook. You need someone who understands your specific context and can deliver practical solutions quickly and efficiently," she said.

Brand and identity

Alongside the repositioning, Quanton has refreshed its brand identity and moved to a new primary domain and email domain under quanton.ai. It said the changes maintain continuity for existing client communications. Quanton also said it has refined what it calls its "Massive Transformation Purpose", alongside updates to its visual identity.

Green said the company's view of transformation has shifted from discrete programmes to a more continuous model. "The old models of business improvement-change something, stabilise, change again-don't work when you need to continually innovate just to keep pace with the market. Organisations need to build what we call 'transformation readiness'-the capability to continually assess and adjust operating models as technology and market conditions evolve," he said.

"Our focus has always been on business outcomes, building client capability, and delivering quantifiable results. That hasn't changed. What has changed is the technology landscape and the sophistication of what our clients need to navigate. They don't need another technology vendor. They need a transformation partner who understands that successful AI adoption requires getting people, process, and data foundations right," Green said.

Quanton expects demand to rise for partners that stay engaged through implementation and scaling, as organisations reassess how quickly AI programmes can move from experimentation into production systems.