Paula Riano

The build is roughly a third of what enterprise AI costs over 3 years. The 5 questions boards should ask before approving the budget.

Structured data is owned. Unstructured data isn't — and that gap is what stalls AI. Why SMEs, not IT, should own the data in their domain.

Copilot came with M365. Gemini came with Workspace. Most NZ boardrooms didn't choose their AI strategy — they inherited it. Here's the alternative.

Your AI strategy has an executive alignment problem, not a technology problem. When leadership isn't aligned on AI, the rest of the organisation doesn't know which way to face. Why AI fluency at the top — not technical expertise — determines whether adoption scales, and what the shift from AI spectator to practitioner actually requires of NZ leaders.

Hiring an AI expert will not make your organisation AI-ready. Your people will. In 10 years, AI fluency will be assumed in every job, the same way knowing how to use a computer is today. But right now, most leaders are still delegating AI to whoever has "AI" in their title and hoping for the best. What I see across NZ enterprises: the specialists build something, the rest of the organisation doesn't trust it or use it, and the initiative fades quietly. The real risk isn't external. It's internal IP walking out the door. Most organisations have no clean data, no documented processes. The knowledge lives in your people. Upskill them, or lose both the expertise and the institutional memory. Leaders need to roll their sleeves up. You cannot delegate your own AI fluency. Your team is watching what you do, not what you say.

Most leaders are focused on the AI sceptics. I'd argue that's the wrong place to look. In my experience, enterprise teams split into thirds. One third are already experimenting with AI on their own. One third are curious but waiting for direction. And one third aren't there yet. That middle third is ready. They just need a leader who's gone first. The real cost of busy work isn't the hours lost to spreadsheets. It's the cognitive load that follows. A team that spends its morning reformatting data doesn't bring its best thinking to the afternoon. That's the productivity loss no dashboard captures. AI won't fix this on its own. Process redesign will. And that starts with leaders asking a simple question: how would we do this if we built it AI-first today?

The 4-Day Work Week (4DWW) has shifted from a wellbeing perk to a critical business strategy for New Zealand enterprises. Recent data shows that companies integrating advanced AI into their 4DWW pilots achieve a 22% improvement in output efficiency and a 15% reduction in costs. To move beyond small pilots and successfully scale, leaders must use strategic AI roadmaps to automate mundane tasks and focus human talent on high-value work.

Measuring AI impact by prompts written misses the entire point. Globally, the C-suite conversation has shifted. We're moving past deployment figures to concrete results: increased revenue, reduced costs, and enhanced satisfaction for customers and employees. This isn't just about doing AI, it's about AI doing something meaningful. I've consistently observed that for New Zealand organisations, especially, ethical integration is a non-negotiable KPI. Trust and compliance are fundamental for long-term adoption and success in our market. True value often comes from augmenting human capabilities, streamlining workflows and empowering teams. We need to assess how AI elevates our people, not merely how many tasks it automates. Pragmatic leaders understand that AI investments must directly align with strategic business metrics.