Applied AI engagement
AI portfolio and governance
Help leadership invest consistently across many opportunities. Intake, prioritisation rules, architectural guardrails, evaluation standards, risk tiers, ownership and review cadence that speed up good projects and stop weak ones.
The problem
Once several teams are building, decisions are made inconsistently. Some projects get waved through, others stall in review, and nobody can say what the portfolio is worth or what it risks.
Target outcome
A practical system for deciding what to fund, how to build it safely and when to stop, applied the same way across the portfolio.
When this engagement fits
You have several initiatives at different stages, built by different teams, and leadership wants to understand and steer the whole rather than each one in isolation.
What we do
We design the intake so that every proposal arrives with a measure and an owner. We set prioritisation rules that reflect value, risk and dependency. We agree architectural guardrails and evaluation standards that teams can apply without a committee, and risk tiers so that controls are proportionate.
We define who owns what, how the portfolio is measured, and how often it is reviewed. Then we run the first reviews with you.
What you receive
A practical governance and investment system, documented in a few pages, that your leadership team runs after we leave. Governance is treated as a way to make better decisions earlier, never as a final compliance gate.
FAQ
Questions people ask
Is this an AI strategy?
It is the operating part of one. A strategy says what you want AI to do for the business. Governance is how you decide, build and review consistently so that happens.
Do we need a central AI team?
Not necessarily. The model fits around how your organisation already makes technology decisions. What it adds is consistency and the authority to stop.
Start with the outcome