EqwittyEqwitty AI Readiness
Pillar 8 of 9 · 9% of your score

Model Management readiness

This pillar asks what happens to an AI system after it is built. Is it tested before launch, and against what? Is anyone watching it in production? What happens when the world changes and its answers get worse?

The questions avoid tooling jargon and describe outcomes instead: whether a model that starts making mistakes is noticed in hours, weeks, or never.

What this pillar measures

Model lifecycle: versioning, testing, monitoring, retraining.

Model Management is weighted at 9% of the overall AI Readiness score, which makes it the 8th heaviest of the nine pillars. 2 scored questions feed its maturity score. See how the weights combine.

What we ask

Every scored answer describes a recognizable state of the world rather than an agree/disagree rating. These are the questions behind this pillar.

  1. Once an AI tool is live, how do you keep an eye on whether it's still working well?How you'd notice if a live tool started getting things wrong or drifting off over time.
  2. Before an AI tool is trusted, how thoroughly do you test that it actually works?How carefully you check an AI tool is reliable before trusting it with real work.

What each level looks like

Each answer maps to a maturity score from 0 to 4. Reading down a column shows what an organization at that level typically says.

Once an AI tool is live, how do you keep an eye on whether it's still working well?
1AwarenessWe don't really check
2ActiveWe just check it's switched on and responding
3OperationalWe track how accurate or useful it is
4SystemicWe track accuracy and get warned when its quality slips
5TransformationalIt's watched automatically and can correct itself
Before an AI tool is trusted, how thoroughly do you test that it actually works?
1AwarenessNo real testing
2ActiveA basic accuracy check before launch
3OperationalWe test it on held-back examples and write up the results
4SystemicWe test accuracy, fairness, and how it copes under stress
5TransformationalAutomated tests run every time anything changes

What a strong score unlocks

A strong score means AI systems stay trustworthy after the launch announcement. It is the difference between a portfolio that grows and one that quietly accumulates liabilities.

Other pillars

All nine pillars, their weights and the scoring math are on the methodology page.

Find out where you stand

A 15-minute diagnostic, then your nine-pillar score, peer benchmarks and a 90-day plan you can act on Monday. One-time payment of CA$19.80 per report.

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