New Zealand firms lag on AI-human design, Deloitte

New Zealand organisations are lagging global peers in designing how humans and artificial intelligence work together. Deloitte data shows 2% of New Zealand organisations say they are leading in this work, compared with 7% globally.

The findings come from Deloitte's 2026 Global Human Capital Trends report, which found 93% of AI investment is focused on technology and 7% on people. The New Zealand results were drawn from 61 respondents, 51% of whom cited a lack of capability and resources as the biggest barrier to AI adoption.

Sarah Clearwater, Founder and Chief Executive Officer of Reframr, said the problem for many organisations is not a lack of interest in AI tools but weak operating foundations.

"I don't think it's an AI adoption issue at all," Clearwater said.

"I think it's fundamentally a systems and standards issue that we're lacking."

She argued that AI produces better results when organisations have documented processes, consistent standards and clear links between customer outcomes and internal workflows. Without that groundwork, businesses risk increasing the speed of failure rather than improving service.

"If I introduce AI into my organisation, but my processes aren't documented, they aren't quality checked, they don't connect visibly and viscerally to the outcome I'm trying to achieve as an organisation, AI is going to accelerate the pace and the complexity at which we're failing because that is what AI does," Clearwater said.

Starting point

Clearwater said many organisations start in the wrong place by choosing a tool first and expecting transformation to follow. In her view, the better approach is to assess existing systems and customer journeys before deciding where automation or AI can add value.

"They start with the tool. They pick a platform, run a pilot, assign someone to own it and wait for the transformation," she said.

Organisations should first review existing gaps and identify whether AI fits naturally into the customer journey and operating model, she said.

"The first step has to be auditing what you already have to understand where the gaps are so AI can actually fit into the journey and help you get the gains that you're after."

Clearwater also linked AI readiness to customer experience design, saying that mapping customer journeys is a practical way to see where processes are coherent and where they break down.

"A customer journey, if nothing else, is a visual of how a customer touches an organisation end to end. It's actually an AI readiness play, if you want to view it that way," she said.

Customer impact

That approach matters because pressure to show returns on AI spending is pushing some organisations towards cost reduction, especially in customer service. Clearwater said the strongest gains come when AI is applied to well-structured businesses rather than used as a substitute for fixing poor workflows.

"The best thing I have seen... is when we have a structured, systematised business and then overlay AI. Then we get the gains," she said.

AI can improve outcomes for both businesses and customers, she said, but only when organisations are clear about where efficiency aligns with better service. In customer-facing functions, removing people too quickly can damage trust and create new operational problems.

"There are ways in which we can use AI to benefit the organisation that are meaningful to the customer," Clearwater said.

Her comments reflect a broader debate over whether AI spending should focus on productivity, customer service or workforce redesign. Deloitte's figures suggest many organisations are still directing spending towards technology deployment rather than organisational change.

Clearwater pointed in particular to the use of voice agents and automated service tools in contact centres, where businesses often see an immediate opportunity to reduce staffing costs.

"The biggest risk that I see is people get excited about voice agents or AI agents across the customer journey to try and cut back essentially what is often contact centre staff," she said.

"If that is the only decision constraint we are committing to, the experience is going to be worse for customers, and organisations are going to find themselves rehiring humans in the next 6 to 12 months."

Some interactions still require empathy, judgment and reassurance, especially when customers are under stress or dealing with financial, medical or insurance issues, Clearwater said.

"The last thing I want to do when I call up my insurer... is to talk to a bot because I'm stressed because I'm frustrated because something isn't working."

Her conclusion is that businesses should identify where lower costs and better experiences can be achieved together, rather than treating automation as an end in itself.

"The work that has to precede that is to understand the customer journey and where in that journey a cost saving would equal an experience improvement. And where those two things are coming together is where we're starting to see a win-win," Clearwater said.