Dr Guy Bate
MIT Sloan Management Review recently coined the term “all-company AI literacy” to suggest that the real productivity gains from AI will not come from a small group of specialists. They emerge when AI capability is distributed across the organisation, from frontline teams through to senior leadership and boards. The value of AI, in this framing, is unlocked through shared understanding rather than centralised expertise.
In the New Zealand edtech context, this way of thinking almost forces a broader question: If value emerges when literacy is distributed within organisations, what might be possible when that literacy is distributed across an ecosystem as tightly coupled as ours?
If we take the ecosystem seriously, AI literacy is not just a capability; it is a connective catalyst. It shapes how founders, educators, researchers, policymakers, investors, and learners understand one another’s constraints, assumptions, and ambitions. When that literacy is shared, the ecosystem itself becomes more adaptive and responsive.
Four ecosystem-level AI literacy opportunities stand out to me:
Coordinated experimentation rather than fragmented pilots
When AI literacy is uneven across the ecosystem, experimentation fragments. Firms run pilots that educators cannot meaningfully interrogate, while educators trial tools without a clear sense of technical constraints or adaptation pathways. Shared AI literacy gives ecosystem members a common understanding of how AI systems behave in practice, allowing them to align assumptions, evaluation criteria, and expectations so that pilots become comparable and cumulative rather than isolated.
Concretely, this means agreeing reusable pilot building blocks that rely on shared AI literacy: common success measures, a lightweight evaluation rubric that includes pedagogical and safety considerations, and a shared way of documenting model limits and data dependencies. Here, I refer readers to Dr Nuddy Pillay’s thought-provoking article in our last newsletter on Co-Designing EdTech, which clearly articulates the power of ecosystem-spanning pilots.
Learning that accumulates across the ecosystem, not just within organisations
Ecosystem-level AI literacy changes how learning travels by giving members the conceptual tools to recognise, interpret, and reuse one another’s insights. When educators, product teams, and system actors share a working understanding of AI behaviour and limits, observations from classroom use, product iteration, and implementation challenges can be translated across roles and contexts rather than remaining local.
In practical terms, this allows learning to accumulate through shared artefacts that depend on literacy to make sense: short pilot reflections, de-identified implementation notes, and a common language for recurring AI issues such as hallucination patterns, overconfidence, bias in examples, privacy edge cases, and accessibility concerns. Literacy is what allows these signals to be recognised as meaningful and reused elsewhere in the ecosystem.
Collective judgement about readiness, risk, and educational value
AI literacy at scale supports collective judgement because it enables ecosystem members to ask better, more precise questions together. Rather than relying on intuition or vendor claims, literate actors can jointly assess when a capability is educationally useful, what failure modes matter in a given context, and which safeguards are sufficient for real-world use.
This shared literacy makes it possible to converge on a small set of readiness signals that travel across the ecosystem: evidence of learning impact rather than engagement alone, clarity on where human judgement must remain in the loop, acceptable error rates for different settings, and clear responses when systems behave unexpectedly. Judgement improves not because rules are imposed, but because more actors understand what they are judging.
Export propositions that reduce adoption friction for offshore partners
In export markets, edtech buyers rarely assess products in isolation. They look for evidence that tools can be implemented, evaluated, and governed in real educational settings. Ecosystem-level AI literacy ensures that this surrounding knowledge is not held by firms alone, but is shared across educators, implementers, and partners who shape how products are used.
As a result, firms can draw on ecosystem-wide AI literacy to produce clearer implementation guidance, more credible evaluation evidence, and more transparent accounts of constraints and safeguards. For offshore partners, this reduces the work of interpretation and risk assessment, because the product arrives with intelligible practices and expectations that reflect a literate system behind it, not just a single vendor.
Closing
For the New Zealand edtech ecosystem, AI literacy can be understood as a shared capability to design, test, interpret, and responsibly scale AI-enabled education technology solutions together, drawing on the combined expertise of educators, developers, policy-makers and sector partners. As we head into 2026, there is a genuine opportunity for us as EdTechNZ members to build this kind of AI literacy together and strengthen the ecosystem we all rely on.
Bio:
Guy chairs the AI in Education Technology Stewardship Group for EdTechNZ. He is also Thematic Lead for Artificial Intelligence, Director of the Master of Business Development (MBusDev) programme, and Professional Teaching Fellow in Strategy and Innovation at the University of Auckland Business School.
With two decades of international industry experience in health technology, biotechnology and pharmaceuticals, Guy has held leadership roles in strategy, business transformation, and new product development. A passionate advocate for the transformative power of AI in education, he is a frequent speaker and workshop facilitator for both academic and practitioner audiences. He focuses on using AI to enhance student engagement and support personalised, self-directed learning.
Guy holds PhD degrees in both Management and Biomedicine and is a Fellow of the Royal Society of Biology in the UK (FRSB), a Fellow of the Higher Education Academy (FHEA), and a Member of the Institute of Directors in New Zealand (MInstD)