Alex Richter and Martin Foo say the opportunity for us is much more than just adopting AI's benefits. Competitive advantage will only come after we use it to build productivity, and that requires a three-part plan

By Alexander Richter & Malcolm Foo*

This is the second of three related articles. The first one is here.

New Zealand is adopting AI rapidly. As we argued in the first article in this series, adoption alone will not deliver the productivity gains the technology promises. The bigger opportunity comes when organisations change how work gets done - redesigning processes, roles and operating models around what AI makes possible.

Where in the New Zealand economy could AI generate the greatest productivity gains, and what would it take to spread those gains through the economy?

AI will not produce productivity in one uniform way. Its potential depends on the work being done, the sector, the scale of the organisation and its ability to integrate technology into how it operates.

For some businesses, AI will mainly help and augment individual workers. For others, it could automate parts of a process. But the greatest gains are likely to come where AI enables organisations to redesign entire workflows, functions and operating models, thereby increasing output, quality, speed or innovation without a proportional increase in resources.

Redesigning work means deciding how people and AI contribute, whose expertise informs decisions, and who can approve or override a recommendation. The people doing the work need to help shape these arrangements.

Where should we place our bets?

New Zealand's business structure makes this question particularly important. Around 97% of enterprises have fewer than 20 employees, and these businesses employ around 30% of New Zealand's workforce. Most workers are employed by larger enterprises.

Many small businesses will gain from AI by reducing administration, augmenting expertise, improving customer service or increasing the capacity of a small team. But the biggest economy-wide productivity opportunity lies in sectors and organisations where there is both significant economic activity and substantial scope to change how work is done.

Three factors can help identify where the greatest opportunities lie: economic significance, AI opportunity and New Zealand capability.

The first factor asks where AI-enabled productivity gains could have the greatest economic impact. The second asks where AI has the greatest potential to transform how work is done. The third asks where New Zealand has distinctive strengths - in expertise, data, institutions, industries, natural resources or cultural knowledge - that could allow us to develop or apply AI in ways that create an advantage rather than simply consume technology developed elsewhere.

For business leaders, the starting point should be the economics of the opportunity: where could AI materially increase productivity, what would have to change in the way work is organised, and does the organisation have the leadership, skills, data and resources to put those changes into practice?

Leaders also need to ask what happens to expertise over time. Are employees becoming better able to investigate problems and make decisions, or increasingly dependent on recommendations they cannot assess? Sustainable productivity requires preserving the practices through which people develop and exercise judgement.

For government, the challenge is to create the conditions in which AI-enabled productivity can scale and spread. One mechanism is sector-based ecosystems in which businesses, technology providers, industry bodies, universities, professional services firms and government work together around shared challenges and opportunities. These networks can identify high-value use cases, address common barriers, develop standards and data arrangements, and share evidence about what changed in practice: how roles and responsibilities were redesigned, what failed, and whether improvements lasted beyond the initial pilot.

Other countries are taking similar approaches. Germany’s Platform Industrie 4.0 brings industry, research and government together around industrial AI, common standards, data ecosystems and practical applications. Singapore is using public-private partnerships to test and deploy AI in real-world settings, including sector-specific initiatives, while involving industry and researchers in developing AI governance and assurance frameworks.

For New Zealand, the value would be in making expertise and proven approaches more accessible beyond organisations that have the resources to develop them independently. This could include sector networks that identify and share proven use cases, test and demonstrate new approaches, and improve access to implementation expertise, alongside the digital infrastructure, standards and data arrangements needed to integrate AI effectively.

Government can also help effective approaches spread through its role as a major purchaser of goods and services and through the standards and systems it establishes. The focus should be on making it easier for organisations to adopt approaches that have demonstrated value, rather than requiring each organisation to discover them independently.

From AI adoption to New Zealand advantage

This raises a broader question about digital sovereignty. Digital sovereignty concerns whether people and organisations can exercise legitimate authority over the digital systems on which they depend. For New Zealand businesses, this includes the capability and practical choices needed to govern their data, challenge AI-supported decisions, and revise arrangements as their needs change.

Exercising this authority requires the skills, data, infrastructure and institutional capability needed to use AI well, as well as the ability to develop distinctive applications and approaches where New Zealand has something valuable to contribute.

New Zealand has economic and cultural strengths that cannot simply be replicated by importing technology. Our primary industries, natural environment, health and education systems, and creative industries may provide opportunities to develop AI applications and approaches with distinctive value.

Our distinctive knowledge, perspectives and cultural capabilities could also provide opportunities to develop AI applications and approaches that are difficult to replicate elsewhere, including those grounded in mātauranga Māori.

So where does this leave New Zealand?

First: focus AI capability where it can make the greatest difference. 
Government can identify strategically important sectors where economic significance, AI opportunity and New Zealand capability intersect, and focus policy attention and support where those factors create the greatest potential for productivity and competitive advantage.

Second: create the conditions for those gains to spread.
Government, business, industry and research institutions can work together through sector-based ecosystems to develop capability, address common barriers, test what works and make proven approaches more accessible across the economy.

Third: turn AI adoption into an advantage. 
Our objective should not be simply to consume technologies developed elsewhere. We should develop the skills, data, infrastructure and institutional capability to apply AI to New Zealand's particular circumstances, and to develop distinctive applications where our own strengths create an advantage.

The opportunity is therefore bigger than AI adoption. It is about building the capability to turn AI into productivity, and productivity into competitive advantage for New Zealand.

*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. 

*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.