New Zealand’s businesses are experiencing notable productivity increases in 2025 due to the use of Artificial Intelligence (AI). Across diverse industries – from manufacturing floors to rural farms – AI technologies are streamlining operations, cutting costs, and augmenting the workforce. This report examines key sectors, backed by detailed statistics and trends, and compares New Zealand’s progress with global peers. It also discusses challenges, government initiatives, and future outlook, providing a comprehensive picture of AI’s impact on productivity in NZ.
AI Adoption (2025)
82%
of New Zealand organizations report using AI in their operations
Efficiency Boost
93%
of businesses say AI made workers more efficient
Cost Savings
71%
of firms achieved operational cost savings through AI adoption
Job Replacement
7%
of companies report AI directly replacing any workers
Overview: AI Adoption and Productivity Trends in 2025
AI is widely adopted by New Zealand businesses, driving significant productivity gains.
Surveys in early 2025 show that 82% of NZ organizations now use AI in some capacity, a sharp rise (15% increase) from late 2024. The payoff has been substantial – 93% of businesses report that AI has made their workers more efficient.
Automation of repetitive tasks and smarter data insights allow employees to focus on higher-value work, boosting output per person. In fact, 70% of New Zealand CEOs say AI has made their workforce more efficient, far higher than the 42% of CEOs saying the same in neighbouring Australia.
Companies are also seeing financial benefits from AI-powered productivity. Over 56% of firms report a positive financial impact from AI (up from 50% previously), with 71% citing savings in operational costs due to AI efficiencies. These savings come from reduced waste, optimized resource use, and lower labor costs for routine tasks. Notably, most businesses have achieved these gains without mass layoffs – only 7% of organizations report AI replacing workers. Instead, many firms note they simply need fewer new hires because existing teams, augmented by AI, can accomplish more. This trend has helped firms maintain productivity even amid a tight labour market.
Figure: Rising AI Adoption and Impact (2023–2025) – The timeline below highlights the rapid growth of AI use among NZ businesses and its impact on productivity over the past few years:
2023 – Initial Uptake
%
About 48% of NZ businesses were using AI tools, as companies began exploring automation and analytics.
2024 – Acceleration
%
AI adoption surged to 66% of businesses by late 2024, with 80% of users reporting positive impacts on productivity.
2025 – Mainstream
%
Over 82% of organizations use AI in 2025, and 93% report improved efficiency. AI and automation are top investment priorities for NZ firms.
Sector-by-Sector Impact of AI on Productivity
Manufacturing
AI-powered automation, quality control, and predictive maintenance are boosting factory efficiency and output.
Agriculture
Precision farming with AI (smart sensors, drones, analytics) is improving crop yields, resource use, and sustainability.
Healthcare
Healthcare is adopting AI for administrative tasks and data analysis, easing staff workload while cautiously moving into clinical AI.
Financial Services
Banks and financial firms use AI for customer service chatbots, fraud detection, and algorithmic analysis, speeding up services.
Manufacturing Sector
Manufacturing in NZ has embraced AI to enhance efficiency and quality. In factories and production facilities, AI-driven automation is streamlining operations. Robots and intelligent machines handle repetitive assembly tasks, working alongside human operators. This reduces errors and frees workers for higher-skilled jobs like oversight and optimization. AI systems analyze vast amounts of sensor data in real time to identify inefficiencies that human operators might miss. For example, AI can automatically adjust production line speeds or materials supply to eliminate bottlenecks, resulting in smoother workflows and higher output.
Quality control has improved thanks to AI-powered vision and detection. Machine learning algorithms inspect products for defects far more reliably and faster than manual checks, catching issues early. This has cut down waste and costly rework – ensuring that only quality goods leave the line. Predictive maintenance is another game-changer: manufacturers deploy AI sensors on equipment to monitor performance and predict when maintenance is needed. By fixing machines proactively before breakdowns occur, companies minimise unplanned downtime, extend equipment lifespan, and avoid productivity losses due to equipment failure.
A strong example comes from an NZ heavy machinery company, McLeod Cranes. By using an AI system to interface with its field crews, McLeod significantly reduced the time spent searching for critical information and enhanced its safety response. In the event of a crane fault or incident, “AI can talk to field workers within seconds of an event and provide robust actions immediately,” improving on-site productivity and safety. This illustrates how AI not only speeds up internal processes but also aids in quick decision-making during operations.
Despite these advances, the manufacturing sector’s success with AI also hinges on workforce transformation. As routine tasks are automated, manufacturers are upskilling workers to operate and manage the new intelligent systems. Rather than cutting jobs, many factories are creating new roles for AI specialists, data analysts, and maintenance techs, while retraining technicians in digital skills. This approach ensures that the introduction of AI “redefines roles rather than replaces them,” as one industry expert noted. In summary, manufacturing in NZ is seeing higher productivity through fewer stoppages, better quality, and optimised processes – all enabled by AI – while concurrently evolving its workforce to collaborate with these technologies.
Agriculture Sector
Healthcare Sector
Financial Services Sector
Other Sectors: Education, Retail, and Government
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Education: Schools and universities are experimenting with AI to personalize learning and reduce administrative load. Educators use AI-driven platforms to tailor educational content to individual student needs and automate grading, where possible. As Dr. Geri Harris, an education sector lead, put it: “We’re not just teaching about AI; we’re using AI to revolutionize how we teach and learn”. This means teachers can spend less time on repetitive tasks like marking quizzes and more on interactive teaching. AI tutors and chatbots help answer student questions after-hours, effectively extending support and improving learning outcomes without requiring proportional increases in staff time.
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Retail and Customer Service: AI is enabling more efficient and personalized retail experiences. E-commerce companies and retailers employ AI for demand forecasting and inventory management – predicting buying trends so that stores stock the right products in the right amounts, thus improving sales productivity and reducing overstock. Virtual shopping assistants and chatbots on retail websites handle common customer inquiries (order tracking, product info), freeing up customer service reps. Marketing departments use AI analytics to segment customers and automate campaign targeting, reaching the right audience with less manual analysis. These improvements help retailers increase sales per employee and optimize supply chains. According to a tech guide, in NZ’s retail sector AI chatbots and data insights guide better stocking and tailored offers to customers, enhancing service without needing a large increase in staff.
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Government and Public Sector: The New Zealand public sector is also gradually adopting AI to improve productivity in governance and public services. AI is used in areas like fraud detection in tax and welfare systems, analyzing data to catch anomalies or false claims more efficiently. Some government agencies use AI tools to sift through public feedback on policy proposals or to help draft routine responses, speeding up administrative workflows. Additionally, AI helps with infrastructure monitoring (e.g., analyzing traffic camera feeds to manage congestion in cities, or using predictive models for maintenance of public assets). The Office of the Prime Minister’s Chief Science Advisor has even issued guidance on capturing the benefits of AI in healthcare and other areas, indicating high-level support for AI adoption. However, the public sector remains mindful of ethical considerations and is working within updated legal frameworks (like the Privacy Act) to ensure responsible use of AI. When used well, AI allows government employees to focus more on complex decision-making and constituent services, while automating more routine bureaucratic tasks.
Each of these sectors sees AI as a means to enhance human productivity, not replace it. The common theme is using AI for automation of routine processes, data analysis at scale, and providing decision support, thereby allowing skilled professionals – whether teachers, salespeople, or public servants – to concentrate on higher-level functions that AI cannot fulfill (like mentorship, creative strategy, or policy judgment). As we have seen, the AI adoption landscape in NZ spans both private and public domains, indicating a broad-based movement towards an AI-enhanced economy.
Workforce Impacts: Augmentation, Skills, and Employment
Workforce Augmentation
AI is largely augmenting workers, with 93% of NZ businesses seeing productivity rise and only 7% reporting any job losses from AI.
Upskilling Drive
Over 80% of NZ companies provide AI training for staff, reflecting a strong commitment to upskilling employees to work alongside AI.
New Roles Emerging
62% of businesses say AI is creating new career opportunities, and 75% of leaders plan to hire for AI-related roles in the next year.
Human Skills Matter
85% of NZ workers expect a greater need for human qualities like creativity and empathy as AI use grows, underscoring the enduring value of human skills.
Surveys of the NZ workforce reveal an optimistic outlook. In one report, an overwhelming 96% of New Zealand workers believed AI will create new forms of economic value rather than just eliminate jobs. Employees seem to recognize that, as AI takes over mundane tasks, it opens opportunities for higher-value work and entirely new lines of business. Indeed, 62% of NZ businesses say AI adoption is generating new career paths and roles in their organization. Many companies are now seeking data scientists, AI model trainers, and business analysts who can leverage AI – roles that barely existed a few years ago. A majority (75%) of business leaders plan to hire for AI-related positions in the coming year, indicating that job growth is occurring in areas complementary to AI.
Crucially, New Zealand’s approach has been to invest in upskilling the current workforce. Rather than relying solely on hiring new AI specialists (which only 20% of organizations plan to do in the near term), most firms are training their existing employees to use AI in their jobs. Around 81% of NZ businesses now support AI training or upskilling programs for staff. This includes formal workshops, online courses, and on-the-job learning initiatives to build AI literacy. Employees are eager as well: they increasingly expect their employers to provide access to AI tools and learning pathways, seeing these as essential for their career growth. The skills revolution is underway – 73% of respondents in one survey said they had received some form of AI training at work. This widespread upskilling ensures that productivity gains are maximized by using AI effectively rather than letting tools sit underutilized due to lack of knowledge.
Alongside technical training, businesses are emphasizing human skills that AI can’t replicate. As routine tasks automate, employees are encouraged to develop strengths in creativity, strategic thinking, emotional intelligence, and ethical judgment. Interestingly, 85% of New Zealand workers expect that the need for human connection and interpersonal skills will increase as AI use grows. Corporate leaders echo this – they value employees who can pair domain expertise with AI-assisted analysis, then apply human insight to make decisions or build relationships. Human-AI collaboration is the model: the AI handles the data crunching or repetitive execution; the human interprets results, adds context, and engages with clients or colleagues. This synergy is shaping a “uniquely New Zealand” approach to the future of work, where technology and people work in tandem and neither is sufficient alone.
It’s also worth noting that AI has introduced an “optimism gap” between business leaders and workers in some cases. While 86% of NZ business leaders believe AI will positively impact their teams’ work in the next two years, only 56% of workers are as confident about AI’s positive impact on their own roles. And about one-third of workers (33%) are concerned about job displacement due to advanced AI systems. This highlights the importance of clear communication and training from leadership; employees need to see how AI will benefit them personally. As one talent development expert noted, leaders have a responsibility to bring their people along “with transparency, upskilling and trust” to bridge this gap. The good news is many NZ organizations are actively doing so by involving staff in AI rollouts, explaining the purpose of new tools, and showcasing early wins where AI made everyone’s job easier.
In summary, AI in NZ workplaces is raising productivity by augmenting employees, not replacing them. The country’s firms are proactively adapting: investing in their people through training, creating new roles for a digital age, and fostering a culture that values both advanced tech skills and irreplaceably human abilities. This balanced approach has enabled NZ to enjoy higher productivity growth (some studies link AI use to fourfold increases in productivity growth rates globally) while maintaining employment levels, with job growth even in sectors where automation is high. The workforce feels the change – work is evolving, but with optimism that AI is a tool for empowerment. Companies that successfully blend AI tools with human talent are seeing gains in output and innovation, and they position themselves as desirable places to work for top talent in an AI-driven economy.
Challenges in Adopting AI for Productivity
Budget Constraints
Limited budgets pose a hurdle – 34% of NZ businesses cite financial constraints as a barrier to AI adoption.
Skills Gap
A shortage of AI talent is evident. 76% of NZ workers have had no AI training, and only 20% of firms plan to hire dedicated AI specialists.
Security and Trust
Data security and compliance concerns are the top barrier for 53% of organizations, and many employees have low trust in AI due to unfamiliarity.
Change Management
Integrating AI requires cultural change. Companies struggle with change management, ensuring staff buy-in and understanding of new AI tools.
- Funding and ROI Concerns: Especially for small and medium enterprises (SMEs), the cost of implementing AI solutions can be prohibitive. A recent survey found 34% of NZ businesses identified budget constraints as a key barrier to further tech investment. Developing custom AI or purchasing enterprise AI systems requires upfront investment in software, hardware (or cloud services), and expertise. In uncertain economic times, some firms hesitate to commit these funds without a clear, quick return. There is also the issue of scale: NZ’s market size is modest, so companies worry whether investing heavily in AI will pay off in proportion. That said, many off-the-shelf AI tools (from cloud providers or software vendors) are making AI more accessible cost-wise, and indeed 72% of NZ businesses prefer off-the-shelf AI solutions over building custom systems to save on costs and deployment time. Still, demonstrating ROI remains important to loosen purse strings for AI projects.
- AI Skills and Talent Gap: New Zealand faces a significant skills shortage in AI expertise. There are not enough experienced AI engineers and data scientists to meet demand, and competition for such talent is global. Interestingly, a KPMG/University of Melbourne study highlighted that only 41% of Kiwi workers currently use AI at work, compared to 91% in India – one of the highest in the world – underscoring a huge gap in usage and confidence. It’s not that NZ workers are unwilling; rather, 76% of NZ employees haven’t had any AI training (formal or informal), and over 60% don’t feel confident using AI tool. This lack of hands-on experience breeds uncertainty and low trust in AI. Many respondents in that study were unsure if AI’s benefits outweigh the risks, simply because they haven’t been properly introduced to AI in their jobs. On the leadership side, only 8% of survey participants felt their organization is responding “extremely well” to the changing AI landscape – indicating that many companies acknowledge they are behind the curve in building AI-ready teams. To close this gap, NZ needs not only more AI specialists, but widespread upskilling initiatives for general staff (which, as noted, are already underway). The relatively low number of firms planning to hire new AI experts (just 1 in 5) suggests most companies will rely on training existing employees or outsourcing to consultants to get the skills they need.
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Data Security, Privacy, and Trust: Over half (53%) of NZ organizations say security or compliance concerns limit their use of AI. These concerns are quite valid – using AI often entails handling large datasets, some of which contain sensitive personal or financial information. Companies worry about protecting this data when using cloud-based AI services, as well as complying with laws like the Privacy Act 2020. There’s also a fear of AI making mistakes that could breach regulations or ethical norms (for example, an AI might inadvertently make a decision that biases against a group of people, running afoul of human rights law). All this means trust in AI systems has to be earned. Many NZ businesses report hesitancy among staff and customers to trust AI’s output. NZ ranks low in public trust in AI compared to other countries – this is tied to the low exposure; as one analysis noted, “How can you trust something you’ve never been shown how to use?”. To address this, organizations are implementing strong governance: testing AI systems thoroughly, implementing transparency (e.g., explaining AI decisions), and keeping humans in the loop for critical decisions. The government and industry bodies are also working on clear ethical guidelines so that AI deployment doesn’t outpace the framework needed to use it responsibly. Nonetheless, winning hearts and minds – ensuring employees and consumers trust AI – remains an ongoing challenge in NZ’s AI adoption story.
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Change Management and Integration: Introducing AI effectively is as much about people and processes as technology. Some businesses struggle with integrating AI into existing workflows. It requires rethinking job roles, redefining processes, and continuous iteration. A common pitfall is companies adopting AI tools without a proper plan to train users or redesign workflows, leading to poor uptake or misapplication. Experts observe that projects often fail when organizations don’t focus on the “human side” of adoption – explaining to teams why the AI tool is introduced, how it helps, and setting clear success criteria. In NZ, where many businesses are small, formal change management may be overlooked. This can result in scenarios like employees experimenting haphazardly with AI (e.g., trying out ChatGPT for tasks) without guidance, occasionally leading to errors or frustration that sour people’s view on AI’s value. Addressing this challenge means strong leadership and change management practices: involving employees early, providing sandbox environments to try AI, celebrating quick wins, and adjusting based on feedback. The organizations that succeed with AI are those that bring their people along on the journey, making AI adoption a collaborative effort rather than top-down imposition.
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Infrastructure and Data Quality: Another challenge (particularly relevant for NZ) is the digital infrastructure and data readiness needed for AI. AI works best when there is abundant, high-quality data and robust IT systems. Some NZ companies, especially smaller ones, have inadequate data collection or legacy IT systems that are not AI-friendly. And while New Zealand’s internet infrastructure is generally good (ultrafast broadband in cities, for example), rural connectivity can be spotty, which affects cloud-based AI usage for rural businesses (this ties into urban-rural disparity discussed later). The New Zealand Treasury pointed out that the country has traditionally had slow diffusion of new technologies and low investment in intangible capital (like software and R&D), which could be a barrier to fully realizing AI’s benefits. If companies don’t upgrade their systems and invest in data, they may not be able to implement AI effectively. This challenge is being gradually overcome as more businesses move to cloud platforms and as government initiatives encourage digital transformation.
In summation, New Zealand’s push toward AI-fueled productivity comes with real challenges that must be navigated. Budget and resource limitations require smart strategies (like using ready-made AI solutions and focusing on high-impact use cases first). The skills gap and trust issues call for massive education efforts and a culture of continuous learning. Security and ethical concerns demand strong frameworks and perhaps updates to regulations – something NZ’s government is actively examining. And internal change management is crucial so that AI isn’t just adopted, but adopted well. How New Zealand addresses these challenges will determine whether the current AI productivity gains can accelerate further or plateau. So far, the trend is encouraging: awareness of these issues is high, and collaborative efforts between industry, government, and academia (often led by groups like the AI Forum NZ) are in play to build solutions.
Government Policies and Initiatives Supporting AI Adoption
AI Strategy for NZ
The government, in partnership with industry, is formulating a national AI Strategy (\”AI Strategy for Aotearoa\”) to guide the development and use of AI in New Zealand.
AI Action Plan
New Zealand launched an Artificial Intelligence Action Plan to prepare businesses and workers for AI’s impact, focusing on skills, innovation, and trust in AI.
Investing in Skills and Research
A new Public Research Organisation for advanced technologies was established, and initiatives (with partners like Microsoft) aim to upskill 100,000 Kiwis in AI and digital skills.
Regulatory Readiness
NZ is reviewing and updating laws (e.g., privacy, IP) to accommodate AI, and aligning with international AI standards to ensure safe and ethical AI deployment.
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National AI Strategy: In 2024, the government started working with the AI Forum and other stakeholders to craft an official AI Strategy for Aotearoa New Zealand. This high-level strategy aims to provide a coherent vision and roadmap for AI development in NZ, ensuring that AI is harnessed to drive economic growth and societal wellbeing. It covers aspects like investment in AI, research priorities, workforce development, and ethical guidelines. The AI Forum’s “AI Blueprint” efforts have fed into this process, with the Blueprint Working Group supporting government in strategy development. The strategy emphasizes creating an ecosystem where businesses can adopt AI responsibly, and New Zealand can become a leader in niche areas of AI application. As part of the strategic engagement, the government is reaching out to major NZ organizations to draft AI “Statements of Intent” aligning with national objectives, signaling a partnership approach between public and private sectors.
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AI Action Plan and Taskforces: The government has launched an Artificial Intelligence Action Plan that outlines practical steps to ready New Zealand for AI’s impacts. This includes initiatives to help businesses integrate AI and workers adapt to technological changes. For example, the Action Plan supports pilot programs and case studies to showcase AI benefits, and it calls for frameworks to identify and address AI-related workforce transitions (reskilling workers from shrinking roles into emerging ones). There have also been task forces and advisory panels (like the Digital Economy and Communications initiative) focusing on AI as part of the broader digital economy strategy. These groups advise on how to improve AI research, encourage private sector AI investment, and ensure inclusivity (such as considering the impact of AI on Māori and other communities). The AI Forum’s second “AI in Action” productivity report included, for the first time, a section on Te Ao Māori (the Māori world view) and AI, indicating alignment with government interest in inclusive AI progress.
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Investment in Skills and R&D: Government agencies have been channeling funds into AI research and talent development. A notable move is the creation of a new Public Research Organisation dedicated to advanced technologies, which includes AI, as mentioned by Microsoft NZ’s leadership. The goal is to boost domestic R&D in AI and related fields (like data science, robotics) and to foster collaboration between universities, government labs, and industry on AI projects. Additionally, recognizing the skills gap, the government has welcomed partnerships like Microsoft’s commitment to upskill 100,000 New Zealanders in AI and digital skills over two years. Programs under the Tech Futures Lab, Callaghan Innovation, and NZQA are aligning to offer micro-credentials and courses in AI. At earlier education levels, there’s an increasing push to include digital literacy and computational thinking (the foundations for AI skills) in school curricula. All these efforts are to ensure NZ has the human capital to support and sustain increased AI adoption.
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Regulatory and Ethical Frameworks: New Zealand is also actively working on the policy and regulatory settings for AI. While some countries create AI-specific laws, NZ has so far favored updating existing laws to cover AI contexts. For example, the Privacy Act 2020 is the primary legislation governing personal data; the government is examining whether it adequately covers AI-driven data processing or if amendments are needed (for instance, to address automated decision-making and algorithmic transparency). The government has indicated that over time, it will likely align certain regulations with international standards – meaning NZ is watching frameworks like the EU’s AI Act and will consider similar protections if suitable. On the ethics side, the Office of the Chief Science Advisor convened expert panels and made 22 recommendations for AI in healthcare and other domains, focusing on themes like transparency, accountability, and bias avoidance. The AI Forum’s advocacy for responsible AI is supported by government agencies, aiming to ensure that AI deployment in NZ comes with fairness and safety checks. Moreover, NZ is participating in global discussions – it contributed to the International OECD AI Policy Observatory and attends regional AI summits (it had representation at the Australian AI Leadership Summit, for example). This international engagement helps NZ stay informed and shape global norms, ensuring NZ companies aren’t left out as global AI governance evolves.
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Supporting Business Adoption: Through agencies like Callaghan Innovation (NZ’s innovation agency), the government offers support to businesses looking to adopt Industry 4.0 technologies including AI. Callaghan’s programs provide co-funding for R&D projects, expert advice, and connections to AI solution providers, especially targeting manufacturers and tech startups. There are also government-sponsored challenges and grants (such as Innovation Challenges for agriculture or smart cities) that encourage development of AI solutions to national issues, thereby indirectly boosting AI uptake. On the export front, NZ Trade and Enterprise (NZTE) has been promoting NZ’s tech sector abroad, including AI products, helping AI startups find global markets – success which in turn motivates domestic adoption.
In essence, the NZ government plays a pivotal enabling role: setting strategy, facilitating collaboration, building talent pipelines, and creating a safe environment for AI innovation. These measures complement private sector efforts, addressing systemic issues like training and trust that single companies cannot solve alone. The coordinated approach is intended to ensure that AI contributes positively to New Zealand’s prosperity and that its benefits are widely shared – aligning with an ethos of an “inclusive and equitable AI future for Aotearoa”, as championed by the AI Forum and embraced by policymakers. While it’s still early in policy implementation, New Zealand’s proactive stance in 2025 indicates a clear commitment to leveraging AI for national productivity growth.
Case Studies: AI-Driven Success Stories in NZ
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- Momentum Consulting – A professional services firm that integrated an AI assistant into its internal operations. By deploying a chatbot to handle routine finance queries and guide staff to information, Momentum “freed up part of a full-time equivalent (FTE) role” in their finance department and reduced management time spent answering common questions by 15%. In effect, an AI system now performs a chunk of work that used to occupy staff, allowing those employees to focus on more complex tasks like client advisory. This small change translated to noticeable productivity and cost savings
- McLeod Cranes – An industrial equipment company (crane services) that leveraged AI for field operations and safety. McLeod implemented an AI-driven communication system that interfaces with crane operators and site workers. The AI can instantly access manuals, safety protocols, and sensor readings from the cranes. In the event of an issue, the AI “talks to field workers within seconds” and provides immediate guidance on corrective actions. This has greatly reduced downtime during incidents and improved safety response times, as workers get quick, informed instructions without having to call a supervisor and wait. McLeod attributes fewer delays and a safer work environment in part to this AI system – a clear productivity and quality win in a heavy-industry setting.
- Shape – A commercial furniture supplier (SME) that partnered with an AI consultancy to scale its business efficiently. Shape adopted AI tools for various administrative and sales functions: automating parts of their quoting process, managing inventory levels with predictive analytics, and using a customer service chatbot on their website. The results were impressive – Shape was able to increase its product pricing by 30% without losing customers, after AI improved their service speed and accuracy. By automating back-office tasks, orders were processed faster and with fewer errors, which improved customer satisfaction and justified the higher prices. Moreover, AI insights helped them identify their most valuable products and customers, clarifying business value. This case exemplifies how even mid-sized businesses can leverage AI to punch above their weight, growing revenue and productivity simultaneously.
- Volpara Health Technologies – A Wellington-based health tech company that develops AI software for medical imaging (notably for breast cancer screening and analysis of scans). Volpara’s AI tools assist radiologists by automatically assessing mammogram images for signs of cancer, significantly speeding up the screening process and improving detection rates. While Volpara’s products primarily serve healthcare providers (in NZ and internationally), they also reflect an internal success story: the company has grown rapidly by capitalizing on AI, showing how NZ firms can create high-value intellectual property that improves productivity in the health sector. Volpara’s AI solutions are now used globally, putting New Zealand on the map in the medical AI arena. The productivity angle: clinics using Volpara’s tools can screen more patients in a day with the same radiologist workforce, and potentially catch issues earlier, which is a productivity gain in both a clinical and economic sense (early treatment is less costly than late-stage).
- Xero – New Zealand’s flagship accounting software company. Xero has integrated machine learning into its cloud accounting platform to automate routine bookkeeping tasks. For instance, Xero’s AI features can learn from a business’s past transactions how to categorize expenses (utilities, travel, etc.) and then auto-suggest or auto-code new transactions. This reduces the manual effort business owners or accountants spend on data entry and reconciliation. By embedding AI into accounting workflows, Xero enables small business users to reconcile their accounts much faster and with fewer mistakes, effectively enhancing financial productivity across tens of thousands of customer companies. As a broader impact, Xero’s successful use of AI showcases NZ’s fintech innovation. It is highlighted alongside healthtech and agritech as a local company delivering AI-powered solutions globally.
- In professional services and finance (e.g., Momentum), AI handles knowledge retrieval and routine inquiries, boosting white-collar productivity.
- In industrial operations (e.g., McLeod), AI accelerates information flow and decision support in the field, leading to less downtime.
- In SME operations (e.g., Shape), AI can automate administrative burden and reveal strategic insights, allowing small businesses to grow revenue and efficiency simultaneously.
- In tech/innovation (Volpara, Xero), NZ companies have turned AI into products that improve productivity for their clients worldwide, while also achieving business success themselves.
New Zealand vs. the World: How Do the Productivity Gains Stack Up?
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- Higher Reported Productivity Gains: New Zealand businesses report very high rates of AI impact on productivity — for instance, 93% of NZ firms see improved worker productivity from AI, which “far outpaces global averages.” Many international surveys show lower figures; for example, a global study might find 50-60% of companies seeing noteworthy productivity boosts, indicating NZ companies are either more effective at leveraging AI or more optimistic in their assessment. One specific regional comparison: 70% of NZ CEOs say AI has made their workforce more efficient, versus only 42% of CEOs in Australia. This suggests NZ organizations might be deriving more value from AI (or perceiving more value) than some of their close peers, hinting at a lead in practical outcomes.
- Enthusiastic Adoption by Workers: Kiwis have embraced certain AI tools at rates among the world’s highest. For example, 84% of New Zealand knowledge workers are already using generative AI (like ChatGPT or similar tools), making NZ one of the top countries globally for gen-AI adoption in the workplace. This high adoption could be due to English-language proficiency, cultural openness to new tech, and perhaps the recent push for productivity tools. By contrast, many larger economies report anywhere from 50% to 70% of office workers using such tools, putting NZ near the forefront in this aspect. This grass-roots uptake of AI by employees can partially explain the strong productivity reports.
- Global Economic Impact: At a macro level, AI is expected to contribute significantly to all economies, and New Zealand is no exception. A PwC Global AI Study has projected AI could add up to $15.7 trillion to the global economy by 2030. For New Zealand, estimates are understandably smaller but still substantial when scaled to NZ’s economy. Microsoft and Accenture research suggested that generative AI alone could contribute between NZ$76 and $108 billion to NZ’s economy each year by 2038 if fully harnessed. While these figures are forward-looking, they imply NZ’s productivity (and GDP) growth could heavily benefit from AI – similar to other developed nations – and that NZ must keep pace to claim its share of that uplift. However, there is also a cautionary note: Microsoft’s analysis found NZ trailing comparable small nations (Singapore, Norway, Finland, Estonia, etc.) on many AI readiness measures, from research activity to startup ecosystem strength. This indicates NZ has ground to cover in nurturing an AI innovation environment relative to some peers.
- AI Readiness and Investment: Many countries have national AI strategies and are pouring resources into AI. New Zealand’s government efforts, while earnest, are smaller in scale compared to giants like the US, China, or even mid-sized countries like Canada or South Korea. For instance, the number of AI startups and research publications in NZ is lower per capita than in nations known for AI leadership. NZ is ranked lower in AI research environment and talent availability compared to countries of similar size that heavily invested early (e.g., Singapore’s AI initiative or Finland’s AI education of citizens). On the other hand, New Zealand’s strength is in practical adoption and agility. NZ companies, especially “frontier firms,” are quick to implement proven AI solutions, whereas in some larger markets bureaucracy or legacy systems slow down enterprise adoption. This agility might be why NZ scores high in usage metrics but not as high in creation of AI tech.
- Job Market Comparison: Globally, there’s fear of AI causing unemployment, but many studies now suggest a net positive or neutral job effect, with job transformation rather than destruction. New Zealand’s experience aligns with the optimistic side of that debate, similar to findings in places like the US and EU where, so far, unemployment is at historic lows even as AI adoption grows. The PwC 2025 Global AI Jobs Barometer highlights that industries most exposed to AI saw three-times higher growth in revenue per employee and still experienced job growth. NZ’s own data (7% replacing workers, but new AI roles being created) mirrors this trend of augmentation. Additionally, the wage premium for AI-skilled workers is high everywhere – PwC noted a 56% wage premium globally for AI skills – and NZ companies also report increasing salaries or competition for people with AI expertise. Thus, NZ is part of the global pattern of increasing demand (and reward) for AI talent.
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Trust and Ethics: Culturally, New Zealanders approach AI with a bit more caution compared to some societies. Surveys found New Zealanders among the least confident and least trained in using AI, and near the bottom in trust in AI tools, whereas countries like India, China, or the US exhibit higher confidence or at least higher usage despite concerns. This suggests that NZ’s strong emphasis on ethical AI and risk may slow adoption in sensitive areas (like healthcare as noted), but it could also ensure more deliberate, acceptable implementations. It’s a contrast with, say, the United States where tech adoption can be more aggressive with a “move fast and break things” ethos. Ultimately, NZ might achieve a steadier, if slightly slower, integration that carries public support.
In summary, New Zealand’s productivity gains from AI in 2025 are notable and in some respects outshine those of other countries, especially in terms of workforce uptake and efficiency improvements reported. NZ companies are seeing real benefits, sometimes even more explicitly than businesses elsewhere, and Kiwi workers are broadly embracing AI tools at a high rate. However, New Zealand also faces the challenge of scaling up its AI development ecosystem and training to match world leaders. The nation is determined not to fall behind; the collaborative initiatives and global engagements are designed so NZ can keep pace with innovation while leveraging its unique strengths (like a flexible business sector and renewable energy for datacentres) to carve a niche in the global AI economy. The competitive stakes are high: as the Microsoft NZ director warned, if NZ doesn’t address its gaps urgently, it risks its productivity growth “falling further behind” those more aggressive nations. Fortunately, the current momentum in adoption and supportive policy measures indicate that New Zealand is aware of where it stands and is striving to elevate its AI capabilities to ensure long-term competitive productivity.
Future Outlook: AI-Driven Productivity Beyond 2025
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- Continued Productivity Growth: Economists project that widespread AI adoption could raise New Zealand’s productivity growth rate significantly. In fact, it’s expected that AI could boost NZ’s productivity by around 1.5% per year on average over the coming years, above baseline. This is a substantial lift for a country whose productivity growth has historically been modest. If realized, it means more output per worker and higher GDP for NZ annually, compounding over time. By 2030 and beyond, AI – including advances like more mature generative AI and more autonomous systems – could help overcome NZ’s geographic and scale disadvantages by enabling small teams to have global reach and automating physical processes in ways previously not feasible.
- Economic Impact and New Industries: As mentioned, AI could add tens of billions to NZ’s economy in the long run. By 2035, certain AI segments like AI-powered applications (healthtech, agritech, fintech) and AI-supporting infrastructure (data centers) are projected to contribute around NZ$3.4 billion in new revenues and cost savings to NZ’s economy. Entire new industries or sub-industries may flourish – for example, AI in creative media, given Wellington’s strengths in digital content, could become a niche where AI tools enable small studios to produce world-class film/gaming content efficiently. Similarly, AI in energy management might help NZ maximize its renewable energy use, boosting productivity in the energy sector and possibly making NZ an exporter of AI-driven energy solutions.
- Broader AI Adoption (Ubiquity): By the late 2020s, AI is likely to be as commonplace in business as the internet or smartphones are today. In New Zealand, one can anticipate near-ubiquitous use of AI across organizations. The current figure of 82% might approach 100% of businesses using AI in some form by 2030, meaning even the smallest local enterprises (like a local cafe or tradesperson) might use AI scheduling or AI marketing tools as a norm. The nature of AI use will also shift from experimental add-ons to deeply integrated systems. For instance, rather than an office worker choosing to use ChatGPT occasionally, their entire office suite might have AI co-pilots embedded that automatically draft emails, schedule meetings, and prepare analytics in the background. This could further push productivity up, though measuring it might become harder as AI becomes intertwined with every task.
- Advances in AI Technology: The AI of 2025, while powerful, is still limited in many ways. Future iterations – think next generations of GPT models, more intuitive AI assistants, better robotics, and improved AI-driven analytics – will unlock new productivity frontiers. Generative AI is in its early stages; as it matures, it could handle more complex writing, design, and coding tasks reliably, possibly handling first drafts of policies or entire marketing campaigns for review. Autonomous vehicles and drones could become reliable enough for mainstream use in NZ’s farming and transport, automating logistics and crop management to a higher degree. In healthcare, approved AI diagnostics might routinely handle initial screening of patients or even treatment recommendations under supervision, massively increasing throughput in the health system. These advancements would amplify the productivity gains seen so far, as AI moves from assistant to a true collaborator in various fields.
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Workforce Evolution: The New Zealand workforce in the future will likely be working “smarter, not harder” with AI. We may see the average workweek structure change if productivity skyrockets – perhaps enabling more flexible hours or remote work, as AI ensures continuity and support. New job categories will appear: by 2030, roles like “AI ethicist,” “machine supervisor,” or “AI-enhanced creative” could be common on job boards, reflecting how humans will work alongside AI. Education and training systems are poised to evolve too: universities and trade schools are expected to incorporate AI into all relevant disciplines, producing graduates who are “AI-native.” This will address the skills gap over time. However, for those in roles highly susceptible to automation, continuous reskilling will be imperative. Government and businesses will need to continue investing in adult education and transition programs to ensure no region or demographic is left behind as AI tools become standard.
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Addressing the Digital Divide (Urban-Rural): By addressing connectivity and training, NZ aims to reduce any urban-rural adoption gap (discussed next). The government’s Rural Broadband Initiative and future network improvements (perhaps low-earth orbit satellites) could bring high-speed internet (and thus cloud AI services) to all rural communities, enabling farmers and rural SMEs equal access to AI tools. If successful, we could see rural productivity climbing significantly, powered by AI in agriculture and local businesses, narrowing the current disparity with urban areas.
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Ethical and Regulatory Developments: In the future, NZ will have more concrete regulations around AI, likely aligned with global standards. This might include requirements for certain AI systems to be audited for bias, or certifications for AI products (imagine a government “AI safety mark” for AI-driven machinery or software). Such frameworks can increase trust in AI and thereby encourage even wider adoption. Public acceptance of AI could grow as people become accustomed to AI in daily life (much as smartphones went from novel to necessary). That said, the discourse around AI’s societal impact (data privacy, job displacement, etc.) will continue, and NZ’s policy approach – balancing innovation with caution – will evolve as AI itself evolves.
Urban vs. Rural: AI Adoption and Productivity Across Regions
- Urban Centers: Cities host the majority of NZ’s corporate offices, tech companies, and service industries, which have been quickest to adopt AI. Urban businesses benefit from better infrastructure (ubiquitous high-speed internet, access to cloud data centers, etc.) and a larger pool of tech talent. As a result, AI adoption in urban NZ is very high, approaching the levels seen in other developed cities globally. In Auckland’s financial district, for example, it’s commonplace to see AI-driven fintech solutions in banks or AI-powered logistics optimizations in the ports. Professional services, finance, and ICT companies (mostly urban-based) lead AI usage – often 85–90% of such firms use AI, by some estimates (globally, information industries in cities have over 90% tech adoption, a pattern likely mirrored in NZ). Because of this, productivity gains from AI are being strongly realized in urban areas. An office in Wellington using AI assistants and analytics might serve more clients or produce more output than a similar-sized office without AI in a smaller town.Urban businesses also have more resources to invest in AI experimentation, meaning they can implement custom solutions that give them an edge. Network effects are at play too: in tech hubs, companies learn from each other’s AI initiatives (through industry groups or shared talent), accelerating adoption. Auckland’s burgeoning AI startup scene and university programs contribute to a vibrant urban AI ecosystem that further propels usage in city-based businesses. Consequently, urban workers are more likely to be augmenting their daily work with AI – whether it’s a marketing team using AI for campaign analysis or a city hospital using AI scheduling – driving up per-worker efficiency in cities.
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Rural Areas: Rural New Zealand, characterized by small towns and farming communities, has a different dynamic. The primary industries (agriculture, horticulture, forestry, etc.) form the economic base here, and as we discussed, these sectors are gradually adopting AI in the form of agritech. However, beyond large or more progressive farms, many smaller rural businesses have been slower to adopt advanced AI tools. Factors include limited awareness, smaller scale of operations (making some AI solutions seem costly or unnecessary), and until recently, less reliable broadband connectivity. Indeed, globally there’s a tech adoption gap: only about 22% of rural firms have adopted AI/ML technologies vs ~45% of urban firms. New Zealand likely reflects a similar divide – though precise local stats are not available, one can infer that a family-owned farm in a remote area is less likely to use AI beyond perhaps a tractor GPS, whereas an agribusiness conglomerate in Canterbury might use drone analytics and AI-driven irrigation.That said, rural NZ is beginning to see pockets of high-tech adoption thanks to targeted efforts. The government and industry groups have been promoting precision agriculture and digital tools to farmers – for example, workshops on using AI for pasture management or showcasing successful cases of dairy farms using AI-enabled robots. As these examples show clear cost savings or yield improvements, word spreads in farming communities, and more farmers become open to trying new tech. Additionally, rural broadband initiatives have expanded internet access (with the Rural Broadband Initiative Phase 2, coverage and speeds have improved for many rural districts), which is a prerequisite for cloud-based AI services.
Where AI is applied in rural industries, the productivity impact is significant. A farm that adopts, say, an AI-based fertilizer optimization system could see increased output with reduced fertilizer input, effectively boosting productivity per hectare. A forestry operation using AI for predictive maintenance on logging equipment will have less downtime, raising log volumes per month per crew. Over time, these enhancements contribute to rural productivity growth. However, these gains are not yet uniformly distributed – they’re currently more evident in well-resourced rural enterprises or those engaged with forward-looking industry programs.
Conclusion:
These sources provide a quantitative and qualitative basis for assessing how AI is boosting productivity in New Zealand and how it compares internationally. Each statistic or quote in the text is linked to its source for reference.
(This report was prepared by the Copilot Researcher agent)