An Opportunity Hiding in Plain Sight
The Government's new Tertiary Education Strategy arrives at a watershed moment for vocational education in Aotearoa. While the strategy's ambitions are clear—doubling down on economic impact, lifting completion rates, and better connecting education to employment—there's a striking gap between the scale of change envisioned and the practical tools available to achieve it.
The strategy explicitly acknowledges that "technological change is continuing to transform the economy and society" and calls for the sector to respond to "rapid advances in digital tools and artificial intelligence." Yet it stops short of recognising that AI isn't just reshaping what we teach—it's fundamentally transforming how we can deliver vocational education itself.
As a team that has spent years building AI infrastructure specifically for New Zealand's vocational education sector, we see the strategy through a different lens. We see not just ambitious goals, but actionable pathways. We see not just systemic challenges, but technological solutions already available. And we see a critical window of opportunity that New Zealand risks missing if we approach these priorities with yesterday's tools.
The Brutal Mathematics of the Status Quo
Let's start with the numbers that matter. The strategy sets an explicit target: higher completion rates, particularly for underserved groups, with a focus on improving first-year retention in multi-year qualifications. It's a worthy goal. It's also, under current conditions, nearly impossible.
Consider the economics facing a typical Private Training Establishment or polytechnic today. Developing a single unit standard—complete with learning materials, assessments, and resources—can take anywhere from 80 to 200 hours of instructional design time. For a Certificate-level qualification with 8-10 units, that's potentially 1,600 hours of highly skilled labour. At current market rates for instructional designers, that's between $80,000 and $160,000 per qualification, before any content is delivered to a single student.
The strategy calls for providers to "create in days what used to take months." It demands "pre-moderation-ready content that meets NZQA compliance standards." It expects "consistent instructional design quality across all content" while simultaneously requiring providers to "reduce content development time by 80%."
These aren't just stretch targets. Under traditional content development approaches, they represent mathematical impossibilities. You cannot simultaneously reduce development time by 80%, improve quality, ensure compliance, and cut costs—unless you fundamentally change the production function.
This is where AI becomes not optional, but essential.
Priority 1: Achievement Through Personalisation
The strategy's first priority addresses completion rates with admirable directness, particularly its call for "distance travelled" measures that recognise the journey students make from their starting points. This represents genuinely progressive thinking about educational equity.
But here's the uncomfortable truth: knowing that we should measure distance travelled is not the same as having systems capable of supporting those journeys. The gap between a school leaver with NCEA Level 1 and someone ready for Level 4 vocational study can be vast. Bridging it requires not just assessment, but adaptive support, personalised feedback, unlimited practice opportunities, and the kind of individualised coaching that has traditionally been impossible to scale.
Traditional models simply cannot deliver this. A single tutor managing 25 students cannot provide truly individualised pathways. They cannot offer every student unlimited practice with immediate feedback. They cannot be available 24/7 when a student, juggling work and family, finally has time to study at 9pm on a Wednesday.
AI can. Not as a replacement for human tutors, but as a force multiplier that extends their reach and impact.
Consider what becomes possible with AI-powered learning platforms. A student practising customer service scenarios can engage in realistic voice conversations, receiving instant, constructive feedback on their communication approach. They can practice the same scenario ten times, twenty times, until confidence replaces anxiety. The AI tracks not just whether they got the answer right, but how their confidence builds, where they hesitate, what patterns of improvement emerge.
For providers, this means moving from a model where practice is limited by tutor availability to one where practice is effectively unlimited. For students—particularly Māori, Pacific, and disabled learners who the strategy rightly highlights as needing better support—it means the freedom to learn at their own pace, in their own way, without the fear of judgment that can accompany asking the same question for the third time.
This isn't theoretical. The technology exists today. The question is whether New Zealand's vocational education sector will embrace it before our international competitors do.
Priority 2: The Economic Relevance Imperative
The strategy's second priority—increasing economic impact through skills relevance and research commercialisation—touches on one of New Zealand's most persistent challenges. Employers consistently report that graduates lack job-ready skills. The "skills mismatch" costs the economy in lost productivity and constrains growth.
The strategy's solution involves stronger employer input into programme design and greater emphasis on work-integrated learning. This makes sense. But it also creates a new problem: how do providers rapidly update content to reflect changing industry needs when content development cycles currently measure in months or quarters?
The introduction of Industry Skills Boards in 2026 will give industries a stronger voice in qualifications and programmes. That's progress. But voice without velocity creates frustration. Industry will tell us what skills are needed. Providers will nod in agreement. And then six months will pass while new content is developed, reviewed, approved, and finally delivered—by which time the industry need may have evolved again.
AI-powered content creation breaks this cycle. When Industry Skills Boards identify a new competency requirement, providers equipped with intelligent content generation can respond in days, not months. They can develop assessment materials, create learning resources, generate video content and interactive simulations, all while maintaining NZQA compliance and instructional design quality.
More importantly, AI enables a level of customisation that was previously impossible. The strategy notes that foundation education providers "should consider local industry needs to connect students with employment opportunities." But creating truly localised content—that reflects the specific workflows of Canterbury dairy operations versus Northland versions, or Wellington's hospitality sector versus Queenstown's—has been prohibitively expensive. With AI, customisation at this level becomes economically viable.
The strategy also calls for universities to strengthen research commercialisation. Here too, AI offers untapped potential. The same natural language processing capabilities that can generate learning content can also help researchers identify commercial applications, draft patent applications, create pitch materials for industry partners, and accelerate the translation of academic knowledge into practical applications.
Priority 3: Access Without Borders
The strategy's third priority—improving access and participation—recognises that too many New Zealanders face barriers to tertiary education. Geographic isolation is particularly acute. The commitment to rebuilding sustainable regional polytechnics is welcome, but physical infrastructure alone won't solve the access problem.
This is where the strategy's call for "high-quality online and blended learning options" becomes critical. But not all online learning is created equal. The first generation of digital education—essentially filmed lectures and PDF readings—has shown limited effectiveness, particularly for vocational students who need to develop practical, hands-on competencies.
The next generation is fundamentally different. AI-enabled platforms can simulate realistic workplace scenarios, provide voice-based practice for customer-facing roles, offer personalised learning pathways that adapt to individual progress, and create social learning experiences that combat the isolation of distance study.
Consider a forestry student in rural Northland. Traditional distance learning might provide reading materials about chainsaw safety. AI-powered learning can simulate decision-making scenarios, test hazard recognition in varied conditions, provide immediate feedback on safety protocol knowledge, and connect the student with peers and mentors through social learning features—all accessible from a mobile phone with modest data requirements.
The strategy emphasises that delivery must be "right-sized" and enable people to "earn and learn." Micro-credentials and cumulative qualifications are part of this vision. AI makes these approaches practical by dramatically reducing the cost of creating smaller, modular content pieces while ensuring they integrate coherently into larger qualification frameworks.
For disabled learners, AI offers particular promise through multimodal delivery—converting text to speech, providing visual alternatives to audio content, adjusting difficulty levels dynamically, and offering multiple ways to demonstrate competency. The strategy commits to implementing Disability Action Plans. AI should be central to that implementation.
Priority 4: Collaboration at Scale
The strategy's fourth priority calls for deeper collaboration between providers, employers, iwi, and communities. The vision is compelling: a system where industry has genuine input into qualification design, where regional partnerships respond to local needs, where wānanga, polytechnics, and PTEs work together rather than compete.
But collaboration has transaction costs. Coordinating between multiple institutions, achieving consensus on programme design, sharing resources and infrastructure, maintaining consistent quality across distributed delivery—all of this requires significant coordination effort.
AI can reduce these transaction costs dramatically. A shared AI platform can serve as common infrastructure, enabling multiple providers to create content that aligns with agreed standards while still reflecting their unique contexts and specialisations. Moderation becomes more efficient when AI can pre-check materials for standards alignment, flag potential issues, and generate moderation reports that focus human expert attention where it's most needed.
The strategy notes that Industry Skills Boards will "temporarily manage some work-based training." This transitional role could be supported by AI systems that standardise quality while allowing flexibility in delivery. Employers offering workplace training could access tools that help them create assessment materials, track learner progress, and document competency development—without requiring them to become educational experts.
For partnerships between providers and iwi, AI offers the potential for content that genuinely reflects te ao Māori perspectives, includes te reo Māori where appropriate, and respects tikanga. But this requires that AI systems themselves are developed in partnership with Māori, trained on appropriate content, and governed in ways that honour mātauranga Māori.
This is not about AI replacing the human relationships that make collaboration meaningful. It's about AI handling the administrative and content production work that currently consumes so much time that deep partnership becomes difficult to sustain.
Priority 5: International Education's Hidden Lever
The strategy's fifth priority sets an ambitious target: doubling international education revenue to $7.2 billion by 2034. The International Education Going for Growth Plan focuses primarily on marketing, promotion, and immigration settings.
These are necessary. They are not sufficient.
New Zealand competes in a global market where students have unprecedented choice. They compare not just reputation and location, but learning experience. International students increasingly expect sophisticated digital platforms, personalised support, flexible delivery, and clear pathways to employment. Universities and providers in competing countries are investing heavily in educational technology to meet these expectations.
Here's an uncomfortable question: when an international student compares New Zealand's vocational education offerings with Australia's, Singapore's, or Canada's, what will they find? Will they see modern, AI-enhanced learning platforms that rival consumer apps in their user experience? Or will they see learning management systems that feel a decade out of date?
The strategy notes that "global student expectations are shifting towards more flexible, digitally enabled learning experiences." It suggests that providers need to adapt. But adaptation requires investment, capability, and time—all of which are in short supply across much of the sector.
An AI-native approach to international education offers several advantages. It can provide 24/7 support across time zones through intelligent chatbots that never sleep. It can offer personalised learning pathways that help students with varying English proficiency levels. It can create culturally adaptive content that respects diverse student backgrounds. And critically, it can deliver all of this at a quality level that positions New Zealand as a technology leader in education, not just a scenic location with good universities.
The strategy emphasises maintaining and enhancing education quality to sustain long-term benefits from international students. AI should be recognised as central to this quality assurance, not peripheral to it.
The Implementation Gap
The Tertiary Education Strategy sets out clear expectations for providers. They must align their activities with TES priorities. They must strengthen relationships with employers, industry, iwi, and communities. They must embed evidence-based approaches to learner success. They must adapt delivery models to support lifelong learning. They must ensure research contributes to economic growth.
All of this is reasonable. All of it is necessary. Very little of it is currently achievable at the pace and scale required using traditional approaches.
The strategy acknowledges that providers face "pressing challenges" including fiscal constraints, technological change, evolving student expectations, and demographic shifts. It calls for providers to "evolve their practices to meet changing learner needs" and "align with national research and innovation priorities."
But evolution requires tools. You cannot ask an organisation to transform without providing the means of transformation. The strategy gestures toward AI and technological change but doesn't explicitly recognise that AI represents enabling infrastructure for achieving its own priorities.
This creates a dangerous gap between aspiration and implementation. Providers understand what's expected. Many lack practical pathways to deliver it. The risk is that the strategy becomes another document expressing worthy goals that prove frustratingly difficult to achieve.
A Path Forward
New Zealand stands at a genuine inflection point. We have articulated a clear vision for vocational education and workforce training. We have identified the right priorities—achievement, economic relevance, access, collaboration, and international competitiveness. We have committed to measurement and accountability.
What we need now is to connect that vision to practical implementation. That means recognising AI not as a futuristic add-on, but as foundational infrastructure for modern vocational education.
The good news is that New Zealand doesn't need to invent these solutions from scratch. The technology exists. Local teams with deep expertise in both AI and vocational education have built platforms specifically designed for our qualification frameworks, compliance requirements, and cultural contexts. These aren't overseas systems adapted to New Zealand—they're built here, by New Zealanders, for New Zealand's unique educational ecosystem.
What's needed is a shift in how the sector and government think about technology investment. Rather than viewing AI as one more expense in stretched budgets, it should be recognised as the lever that makes everything else possible—higher completion rates, faster content development, better employment outcomes, genuine personalisation, sustainable regional delivery, and international competitiveness.
The Tertiary Education Commission's role in giving effect to the strategy through investment decisions is crucial here. If TEC funding priorities explicitly recognise and reward providers who adopt AI-enhanced delivery models, the sector will move faster. If investment plan assessments ask how providers will leverage technology to achieve distance-travelled improvements, personalised learning, and rapid content updates, providers will prioritise these capabilities.
Industry Skills Boards, once established, should be encouraged to think about AI not just as content they teach about, but as infrastructure they rely on to keep vocational education responsive to industry needs.
The Ministry of Education's monitoring framework should include measures of technological capability and adoption, recognising that in 2025, these are fundamental to quality delivery, not optional extras.
The Alternative
What happens if New Zealand doesn't embrace this shift? The answer is visible in international comparisons. Australia's vocational education sector is already investing heavily in AI-enhanced delivery. Singapore's SkillsFuture initiative integrates sophisticated personalised learning platforms. Canada's apprenticeship systems are adopting digital tools that New Zealand's equivalents lack.
The risk isn't dramatic collapse. It's slow, steady decline in competitiveness. International students will choose institutions with better learning platforms. Domestic students will become frustrated with dated delivery models. Employers will grow impatient with qualifications that take too long to update. Completion rates will remain stubbornly low for underserved groups because we'll lack the tools to provide truly personalised support at scale.
Meanwhile, the government will have articulated a compelling strategy that proves difficult to deliver, not because the priorities were wrong, but because we asked providers to achieve transformation without providing transformational tools.
Conclusion: Matching Ambition with Capability
The Tertiary Education Strategy 2025-2030 represents genuine ambition for New Zealand's vocational education sector. It asks the right questions, sets appropriate priorities, and creates accountability for outcomes. These are all positive developments.
What the strategy needs now is an implementation framework that matches its ambition with practical capability. That framework must recognise AI as essential infrastructure, not optional enhancement. It must support providers in adopting these tools through funding, training, and clear expectations. It must measure not just outcomes, but the capability development that makes outcomes achievable.
The goal isn't to replace human expertise with machines. It's to free educators, trainers, and instructional designers from tedious production work so they can focus on what humans do best—mentoring, inspiring, adapting to individual needs, making contextual judgments, and building the relationships that transform education from information transfer to genuine development.
The strategy speaks of being "brave" and "hungry" in pursuing better outcomes. That bravery should extend to embracing technological change not as a threat to educational quality, but as the foundation for achieving it. That hunger should drive us to adopt tools that make the seemingly impossible—personalised learning at scale, content development at speed, truly equitable access—not just possible, but practical.
New Zealand has an opportunity to lead in AI-powered vocational education. We have local expertise, appropriate technology, and now a strategic framework that articulates clear priorities. What we need is the courage to connect these pieces and the wisdom to recognise that in 2025, achieving our educational ambitions requires more than dedication and hard work. It requires leveraging the most powerful educational technology humans have ever created.
The question is not whether AI will transform vocational education. It's whether New Zealand will lead that transformation or watch it happen elsewhere while wondering why our own goals remained frustratingly out of reach.
The Tertiary Education Strategy has given us the vision. Now we need to provide the tools to make it real.
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