Executive Strategy

CEO's AI Decision Framework

A decision guide for Boards and Executives to filter AI initiatives, manage risk, and allocate capital.

The 4 Strategic Pillars

Before approving any pilot, the Board should check alignment on these four constraints.

Does this create real business value or is it just innovation theatre? It must solve a real problem costing real money.

Do we own the data? Is it clean? Data quality is the hidden constraint that makes or breaks every AI project.

If this hallucinates or leaks, is it reputation-ending? Understand the blast radius of failure.

Does sensitive data leave our verified environment? This is non-negotiable.

Interactive Tool

Test your project idea against our 3-Gate approval process. Save time by stopping bad projects fast.

Does this initiative involve Taonga (culturally or commercially sensitive) data, and will that data leave your organisation's verified environment?

Default to buying (SaaS/Copilot). Only build custom when it creates a genuine competitive advantage or meets a sovereignty requirement.

Factor

Buy (SaaS / Copilot)

Build (Custom Cloud)

Use Case

Productivity tools, Office tasks, General coding

Unique IP, Proprietary data processing, Customer-facing apps

Cost Structure

Lower per-seat cost. Predictable OpEx.

Higher (Dev costs + variable infra). CapEx heavy.

Time to Value

Fast (Days). Immediate productivity gains.

Slow (Months). Requires iteration and testing.

Data Privacy

Vendor Managed. Trust-based relationship.

Fully Controlled (Your tenant). Complete sovereignty.

VERDICT

Default Choice for 80% of tasks

Only for core competitive advantage

If you're unsure about your data sovereignty risks or can't quantify the value of an initiative, don't proceed to build.