Nicci Simmonds, a former High Commissioner and now a Principal Consultant at MartinJenkins, argues that AI can have a positive role helping Pacific governments and their partners to speed up critical investments through making better decisions more quickly.
In late 2021 I began my dream job as New Zealand’s High Commissioner to Vanuatu. I led a wonderful team of Kiwis and ni-Vanuatu who cared deeply about making a difference for both Vanuatu and New Zealand.
Our main partner, the Vanuatu Government, was determined to chart their own development path on their own terms. Like many governments in the Pacific they know they need partners to achieve their ambitions, and they know that after just 43 years of independence their small population size presents serious obstacles to achieving the capabilities and capacity they need to reach their goals.
I knew we would face delivery challenges because of those constraints, but what was confronting was the compounding challenge of the different business process requirements of each development partner layering on top of Vanuatu’s own process requirements. Very often this meant major delays to critical investments, from health to infrastructure.
In the current context of tighter aid funding, rising costs, public discontent with government, and the fuel crisis cutting into Pacific government budgets, those process obstacles and delays really matter. Making financing go further, and turning it into results more quickly, is now central to being a good development partner.
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Slow, fragmented business processes make delivering public services harder than it should be
A persistent but uncomfortable truth across many public systems is that governments struggle to spend allocated funding well and on time.
This isn’t unique to the Pacific. In both developing and developed contexts, decision-making processes can be slow and fragmented, and amplify risk-averse behaviour. Valuable time is lost moving from an initial idea to an approved, contracted, and delivered project.
Procurement is often singled out as the problem, but it’s only one part of a longer chain. Delays also happen in proposal development, approvals, contracting, and design. Each step introduces opportunities for delay.
What is often missing is an accurate, shared understanding of how the chain of processes works in practice. Where are the bottlenecks? Which steps add value, and which simply add time? Where are risks genuinely being managed well?
Without that visibility, it’s very difficult to improve delivery, regardless of how much funding is available.
Understanding your business processes well is a precondition for increasing efficiency through AI
AI offers real gains in efficiency, but only when it’s applied deliberately after the relevant humans have developed an accurate understanding of their business process.
Too often, organisations or well-meaning officials within organisations start with the AI tool. They experiment with ChatGPT or Copilot in a scattergun way without an accurate shared understanding of existing processes, hoping efficiency gains will follow. This can introduce new risks and inefficiencies.
It’s better to start by mapping and understanding those processes. Once agencies know where time is being lost and decisions are getting stuck, they can identify where and how AI tools will reduce the problem.
For example, the AI tool Nolia was designed to address the specific process challenges related to procurement. By improving the quality and consistency of documentation, surfacing relevant information earlier, and enabling better, faster, and more compliant decision making, Nolia reduces delays without compromising transparency or robustness. In fact it improves transparency and accountability.
The key lesson is that AI is effective when it’s applied to a defined problem. It’s an accelerator for good process design, not a substitute for it.
AI can ease the tension between providing transparency and accountability and making better decisions more quickly
At its core, the delivery challenge is a decision-making challenge.
Governments are rightly focussed on ensuring that decisions are transparent and evidence-based, and that the decision makers are accountable. But these objectives can mean delays in decision making if processes become complex or duplicative. Citizens want transparency and accountability, but their immediate need is for good-quality services and for infrastructure that supports economic development.
AI has the potential to ease this tension. Used well, it can support faster analysis, better access to information, and a stronger evidence base for decisions.
Importantly, reducing project delays helps build trust. When citizens see decisions being transparently made and followed through into delivery, confidence in public institutions grows.
The principle to apply here is this: support human judgement, don’t replace it or allow AI to erode or undermine it. Officials need to understand how outputs are generated, make sure data is handled safely, and maintain accountability for decisions.
Questions of AI sovereignty and resilience are posed more sharply in the Pacific
Beyond immediate gains in efficiency, AI raises deeper questions for Pacific governments and their partners.
What does “sovereign AI” mean in small economies with limited resources and with distinct languages and cultures? How can these systems be shaped to reflect local priorities and enable democratic governance, rather than importing models developed elsewhere?
There are also questions about resilience. As AI becomes more embedded in public systems, how can governments protect against misuse while still enabling innovation?
These aren’t uniquely Pacific challenges, but they are bigger in smaller systems with fewer resources to absorb risk. Working in trusted partnerships will help small governments safely deal with the AI and governance risks that are coming at us fast.
There is an interesting divergence in attitudes to AI between “the West” and the rest of the world. Stanford University’s 2025 AI Index shows that in developed economies the public sentiment tends towards nervousness, while in developing countries people tend to be more optimistic and enthusiastic about the opportunities AI presents. If development partners are overly cautious, they risk frustrating the same governments they are trying to partner with and support.
AI could support greater trust in public institutions by increasing transparency and participation
Globally, trust in public institutions is under pressure. Social media and digital technologies, including AI, have contributed to that trend, through often amplifying misinformation and increasing polarisation.
But government agencies and officials need to learn how the technology can play a positive role. Used well, AI can increase transparency, allow them to engage more effectively with the public, and make it easier for citizens to participate in decision making. AI offers a way to reinforce democratic norms while also improving services.
The challenge is getting from ambition to results
Pacific governments aren’t short of ambition. Their challenge is to quickly turn that ambition into visible, sustainable results.
AI on its own will not achieve this. But it can help unlock meaningful gains if its use is grounded in principled intent and a clear understanding of how systems work, and is also supported by partners who are willing to adapt.
In an environment where every decision counts and every dollar matters, that’s an opportunity worth taking.
