Snapshot: evidence-based shifts underway
New Zealand’s health workforce shortages are structural rather than temporary. Health NZ states that current initiatives will not resolve shortages by 2027 and that meaningful improvement requires longer-term workforce development. Current planning emphasises education and training, retention, rural distribution and new models of care. New Zealand may require approximately 3,450 additional doctors by 2033 if demand continues on its current trajectory. [1,3] Lightcast also identifies health as a sector in which labour demand is high but AI adoption remains comparatively low. [2]
Workforce implications: over the next 3–5 years
Demand should remain strong across clinical, allied-health, mental-health, public-health and community-care occupations. The fastest change is likely to be in how care is delivered, through digital health, remote monitoring, health analytics, AI-supported administration and more multidisciplinary community-based services. AI is more likely to augment clinical judgement and reduce administrative load than to eliminate substantial numbers of health professionals. Graduate skills in communication, cultural capability, teamwork, health data and technology-supported care should become more valuable. Rural and underserved workforce shortages are likely to persist.
Snapshot: evidence-based shifts underway
New Zealand has an infrastructure workforce of more than 100,000 FTE workers across over 100 occupations, spanning planning, design, construction, operation and maintenance. Te Waihanga identifies workforce size, productivity and capability as constraints on delivery. Its long-term modelling indicates that the infrastructure construction workforce could need to grow substantially to close New Zealand’s infrastructure gap. The sector also has relatively low digital and data maturity. Government investment requirements include transport, water, energy, housing-enabling infrastructure, health facilities and climate resilience. [4,5,6]
Workforce implications: over the next 3–5 years
Engineering demand should remain robust but fluctuate with public investment cycles and project sequencing. Employers are likely to place greater value on graduates who can combine technical expertise with digital engineering, data, building information modelling, project controls, systems thinking, sustainability and stakeholder management. Workforce growth alone will not meet infrastructure needs, increasing pressure for productivity improvements, modular construction, automation and better asset management. Civil, environmental, electrical and energy-related engineering should remain important, alongside construction management and infrastructure planning.
Snapshot: evidence-based shifts underway
New Zealand’s science and innovation system is being reorganised around clearer economic, environmental and national priorities. Current government direction emphasises biotechnology, public health, climate resilience, advanced technology, the bioeconomy and translating research into commercial and societal impact. Research is also becoming more computational, data-intensive and collaborative, with international programmes in areas such as Earth observation and Antarctic science. [7,8,9,10]
Workforce implications: over the next 3–5 years
Science employment is likely to grow most strongly at the interfaces between disciplines and between research and application, rather than solely in traditional laboratory roles. Likely areas include environmental monitoring, climate adaptation, biotechnology, biosecurity, geospatial and Earth-observation science, materials, health research and computational science. Employers should increasingly expect graduate scientists to use AI and advanced data methods, communicate findings to non-specialists, work with industry and regulators, and understand commercialisation or policy application. Purely technical expertise without data, communication or impact capability may be less required.
Snapshot: evidence-based shifts underway
AI is moving from experimentation into mainstream organisational use. Randstad reports that 63% of surveyed employers invested in AI during the previous year, while job postings requiring AI-agent skills increased sharply. It also identifies a gap between employer expectations and workers’ understanding of how significantly AI will affect their tasks. [11] Lightcast finds that AI-related work is spreading beyond the technology sector and that 56% of AI jobs are outside IT. It also finds weak alignment between degree titles and AI careers: only 6% of AI workers in its data hold an AI degree.[2] Australian projections, relevant to the trans-Tasman graduate market, show ICT security employment growing considerably faster than overall employment through 2029. [12]
Workforce implications: over the next 3–5 years
Demand should remain strong for cybersecurity, software engineering, data, cloud, AI implementation and digital-product roles, although the composition of entry-level work will change. Routine coding, testing, support and analytical tasks will increasingly be AI-assisted. Growth is likely to favour graduates who can integrate AI into business or scientific workflows, validate its outputs and operate across technical and non-technical teams. AI literacy will become relevant well beyond computing degrees. Specialist demand should increasingly distinguish between building AI systems and applying, governing, securing and auditing them, particularly for productivity gains.
Snapshot: evidence-based shifts underway
Employers are increasingly prioritising skills and experience alongside, and sometimes over, formal qualifications. In Randstad’s international survey, 87% of employers said they value skills and experience over formal qualifications, while 72% considered traditional linear careers outdated.[11] In accounting, IFAC identifies AI, automation, digital assurance, data and sustainability reporting as forces requiring professionals to redefine their roles. [13,14,15,16]
Workforce implications: over the next 3–5 years
Routine processing, reconciliation, standard reporting, basic financial analysis and parts of audit testing should become increasingly automated. Graduate opportunities should shift towards interpretation, assurance, risk, business partnering, analytics, advisory work, sustainability reporting and client communication. Accountants and finance graduates will still need strong technical foundations, but value will increasingly come from judgement, controls, explaining AI-supported analysis and translating financial information into decisions. Business graduates more generally should face growing expectations to show applied capability through projects, internships and portfolios.
Snapshot: evidence-based shifts underway
New Zealand’s courts and justice services face pressure from population growth, demographic change, rising complexity, timeliness problems and constrained system capacity. The Ministry of Justice’s long-term briefing describes the system as under-resourced and over-burdened, with changing user needs affecting court operations and access to justice. [17,18] Across legal work, AI can increasingly support research, summarisation, discovery, document review and contract analysis. Lightcast’s wider analysis indicates that editing and administrative work, important components of junior professional roles, contains high concentrations of potentially automatable skills. [2]
Workforce implications: over the next 3–5 years
AI should alter the task mix of junior legal work rather than remove the need for lawyers. Graduates are likely to spend less time on first-pass research and document production and more on verification, legal reasoning, client interaction, advocacy, negotiation and managing technology-supported workflows. Demand may grow in privacy, cybersecurity, technology regulation, environmental and resource law, regulatory compliance, dispute resolution and AI governance. In the wider justice sector, digital case management and remote participation should increase the need for graduates who understand both legal processes and service design, evidence, data and vulnerable users.
Snapshot: evidence-based shifts underway
The public sector is under pressure to improve service quality and productivity while operating within fiscal constraints. The 2025 State of the Public Service report identifies expanding uses of AI in policy, tax administration, biosecurity and citizen-facing services. A New Zealand government AI-assistant pilot found strong user demand for simpler access across government services.[19] Public-sector futures work also highlights AI, cybersecurity, privacy, public trust and digital capability as major workforce issues. [20,21]
Workforce implications: over the next 3–5 years
Employment is likely to shift away from some transactional and administrative activities towards policy analysis, implementation, commissioning, data analysis, digital service design, regulation, assurance and community engagement. Graduates should be expected to use AI and data tools while applying public-law, ethical and evidential standards. Fiscal pressure may constrain overall headcount, making recruitment more selective and increasing the premium on people who can work across agencies and disciplines. Skills in systems thinking, evaluation, Māori–Crown relationships, consultation and communicating complex issues should remain central.
Snapshot: evidence-based shifts underway
New Zealand’s official food-and-fibre workforce modelling presents three possible futures to 2032: business as usual, increased technology, and broader transformation driven by economic, technological and environmental change.[22,23] The technology scenario assumes greater adoption of existing and emerging technologies and associated productivity gains.[24] Government science priorities also link food, fibre, bio-processing, biofuels, environmental sustainability and resource resilience. [25]
Workforce implications: over the next 3–5 years
Graduate employment growth may not occur uniformly in traditional production roles, but the sector should require more graduates in agritech, environmental science, biosecurity, food science, GIS, automation, supply-chain analytics, sustainability and resource management. Technology should reduce some repetitive and labour-intensive tasks while increasing demand for people who can deploy technology in field settings and interpret environmental and production data. Climate adaptation, freshwater, emissions, land-use change and market assurance should generate work spanning science, policy, business and regulation.
Snapshot: evidence-based shifts underway
New Zealand’s latest projections indicate different national patterns for primary and secondary teaching. The Ministry of Education projects a modest primary-teacher surplus increasing through 2028, while the national secondary shortfall is forecast to reduce but not disappear over that period. Subject and regional shortages may persist even when national supply appears broadly balanced. [26,27] At the same time, AI is changing curriculum, assessment, academic integrity, learning support and teachers’ professional practice.
Workforce implications: over the next 3–5 years
The employment outlook should vary more by subject, location and learner need than headline national teacher numbers imply. Secondary STEM, technology, te reo Māori and some specialist areas may remain harder to staff. Teaching roles should increasingly incorporate AI-supported planning and feedback, digital pedagogy, learner analytics and explicit teaching of AI literacy. Outside schools, graduate demand should expand in learning design, educational technology, workplace learning, professional development and short-form adult education as organisations respond to continuous reskilling needs.
Snapshot: evidence-based shifts underway
Digital technology and generative AI are already materially changing creative practice. A 2025 New Zealand survey found that 65% of creators who use digital tools had used generative AI, including for developing ideas, producing work and widening distribution. [28,29] The Ministry for Culture and Heritage’s long-term briefing identifies opportunities in new forms of production and expression but also risks involving copyright, cultural appropriation, authenticity, misinformation and control of New Zealand stories. [30,31] The national creative strategy expects responsible AI uptake to change creative opportunities rather than simply eliminate them.[32]
Workforce implications: over the next 3–5 years
Production workflows in design, journalism, marketing, publishing, film and content creation should become significantly faster and more AI-assisted. Some routine production and junior content tasks may contract or be bundled into broader roles. Growth and graduate opportunities should favour creative direction, distinctive storytelling, audience strategy, user experience, interactive media, gaming, virtual production and culturally grounded content. Copyright, provenance, consent, misinformation and protection of Māori cultural knowledge should become more prominent areas of professional practice. Portfolio and freelance careers are likely to remain common, making commercial, client-management and intellectual-property capability increasingly important.
In deciding the “Sectors”, a combination of ANZSIC (Australia/New Zealand Standard Industry Classifications), Government Agency splits, and UC Faculty alignment has been used.
