Alexander Richter & Malcolm Foo argue government and businesses must take action to harness and scale up AI use to drive productivity and competitiveness

By Alexander Richter & Malcolm Foo*

New Zealand has long had a productivity problem. For decades, our productivity and incomes have lagged those of comparable advanced economies, and we have struggled to turn new technology into lasting improvements in economic performance. 

Artificial intelligence (AI) could change that. But it could also make the problem worse. 

New Zealand organisations are adopting artificial intelligence with speed. A recent Datacom report found that 91% now use AI in some form, up from 66% just two years ago. But high adoption conceals a troubling picture: scaling remains very low. Only 4% say AI is transforming their core operations. 

A worker who uses AI to complete an existing task better and faster is an adopter. An organisation that redesigns its processes, roles, management practices and operating model around AI is embedding and scaling AI use. Both can contribute to measured productivity, but it’s the second case that has greater potential to generate sustained, economy-wide productivity gains. 

This situation is not new for New Zealand. 

Various reports on AI identify slow technology diffusion and comparatively low investment in intangible capital (the management systems, training and process redesign that let new tools transform ways of working) as specific risks to capturing AI's benefits. We have seen this pattern before with earlier waves of IT and automation, and we risk repeating it. 

Other countries are treating this as a critical problem to solve, not just monitor. 

Singapore has made AI adoption an explicit part of its economic strategy. AI adoption among Singaporean SMEs more than tripled in 2024, and 73.8% of surveyed workers reported using AI at work. More than 60% of AI-adopting firms said they expected to redesign jobs to integrate it. Singapore has since launched a National AI Impact Programme to support 10,000 enterprises over three years as they deepen adoption into transformation. 

Singapore is just one example. Australia and the US similarly have plans and policies to harness AI for economic and productivity growth, treating adoption as the start of an economic transformation, not the end point of a digital strategy. New Zealand doesn’t need to copy those programmes, but should heed the principle: both government and businesses must take action to harness and scale up AI use to drive productivity and competitiveness. 

The metric that matters isn’t how many New Zealand workers use AI. It’s how effectively our organisations use it to transform the way they work, measured against the countries we compete with for capital, skills, and markets. 

AI is a transformative opportunity to change our productivity trajectory, but only if we treat adoption as a starting point rather than an achievement. 

So what do we need to do to ensure AI works for us and our economy? 

First: move from AI adoption to organisational transformation. Organisations need to rethink how work gets done, including processes, roles and operating models, rather than simply giving employees new AI tools. 

Second: prepare people and leaders for a different way of working. AI transformation will require new skills, different approaches to leadership and governance, and a workforce that can work effectively alongside AI. Leaders need to connect technological possibilities with organisational purpose and involve employees in shaping new ways of working. 

Third: create the conditions for AI to scale. Government and business need to address the barriers preventing organisations, especially smaller firms, from moving beyond experimentation and adopting AI at scale.

The next articles in this series examine what AI transformation means for organisations and their workforces, and what policy and economic settings are needed to scale its benefits across New Zealand. But there is another question beyond productivity and competitiveness: what kind of AI-enabled future do we want for New Zealand? The final article in this series will explore how we can ensure AI is not shaped solely by economic incentives, but by the human and societal values we want it to reflect.

*Alexander Richter, Professor of Human-Centric AI at the University of Auckland Business School and inaugural Director of Huanui, its AI Initiative. Huanui advances ambitious research, engages with business, government, and communities to translate insights into societal impact, and develops the capabilities needed to work with AI responsibly and effectively.

*Malcolm Foo, former PwC Partner and New Zealand Government deputy chief executive; organisational performance, transformation and strategy adviser; EMBA Executive-in-Residence at Te Herenga Waka, Victoria University of Wellington.