The Vector Method
Strategy Is a Filter, Not a Wish List
Most AI strategies fail before implementation starts. Not because the technology doesn't work — because the strategy was built backwards.
The question "what can AI do?" produces 47 potential use cases, confused leadership, and six months of pilots that never scale.
The question "where do we lose the most value?" produces 2–3 initiatives that actually matter.
Vector CXO's job isn't to find AI applications. It's to filter ruthlessly — so resources go toward what works and away from what won't.
"Here's everything you could do" isn't strategy. "Here's what to do first, and why" is.
What Makes This Work
Most AI initiatives fail because they optimise for the wrong things. Here's what actually matters.
Judgment Over Frameworks
Every business is different. Frameworks are starting points, not answers. The Vector Method applies structured thinking to your specific situation — not a generic template to your business.
The difference shows up in the output. Generic frameworks produce generic recommendations. Judgment produces decisions you can actually act on.
Kill More Than You Start
The most valuable part of any AI strategy isn't the list of what to build. It's the list of what not to.
Most organisations are already considering too many AI initiatives. Pursuing all of them dilutes focus, drains resources, and produces nothing that works at scale. The Vector Method cuts aggressively — so the initiatives that survive have a real chance.
Assumptions Visible
Every projection depends on assumptions. Most consultants bury them.
If the analysis assumes cleaner data than you have, or more capacity than currently exists, those assumptions belong on the table — before commitment, not after. Transparent reasoning produces better decisions.
You Already Know Something Isn't Right
The AI initiatives that keep stalling. The vendor pitches that all sound the same. The internal debates that go in circles. Let's cut through it.