Methodology

How the readiness score is calculated

Every capability is rated on one 1-to-5 ladder, weighted into a pillar score, capped by a gate where a critical gap exists, and shown to clients as a letter grade.

The 1 to 5 scale

Every capability in the Ejentic AI Strategy Health Check is rated on one ladder of 5 levels, and each level has written wording so a rating means the same thing in any organization. Levels 1, 3 and 5 are described in full; 2 and 4 sit between them.

  1. Level 1

    Initial

  2. Level 2

    Emerging

  3. Level 3

    Defined

  4. Level 4

    Managed

  5. Level 5

    Optimized

How the pillars are weighted

Capability ratings are averaged by weight into a pillar score, and pillar scores are weighted into the overall figure. The weights are fixed for every engagement, running up to 5, so two organizations — and the same organization a year apart — are measured on the same instrument.

Pillar weights
PillarWeightWhat it asks
1 · Business strategy and AI value5Where AI attaches to the business, who owns it, and whether the value is proven.
2 · Data readiness4.8Is the data fit for an AI use case to consume?
3 · AI security and trust5Five domains protecting the data, the models and the people using them.
4 · People and change4.2Communication, collaboration and capacity when AI enters the work.
5 · AI operating governance4.4How governed the AI already running is, across five process domains.

Why a gate can cap a pillar

A weighted average can hide a catastrophic gap, so 5 gates are applied after the average is taken. Where a gate fires, the pillar is held at its ceiling no matter how well the rest of the pillar scored, and the report says which gate did it.

  • DLP / ingestion gate

    Caps at 2.0

    Data protection scores 1 — proprietary data reaches models with no control.

  • RAG authorization gate

    Caps at 2.5

    Identity and access scores 1 — retrieval runs on credentials broader than the user.

  • Guardrail / execution gate

    Critical flag

    Threat defence scores 1 — raw input reaches the model and raw output reaches systems.

  • Data classification gate

    Caps at 2.5

    Classification scores 1 — you cannot govern data you have not classified.

  • Change capacity gate

    Caps at 2.5

    Load honesty scores 1 — AI added on top of full workloads with no protected learning time. The single strongest stall predictor.

How scores become grades

Grades are a reading aid over the unchanged score, not a second calculation. The decimal is always shown alongside, and the bands never move.

Grade bands
GradeScore
F1.00 to 1.74
D1.75 to 2.49
C2.50 to 3.24
B3.25 to 3.99
A4.00 to 4.74
S4.75 and above

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