maeseeStart Check

Framework

The maesee AI Distribution Readiness Framework

AI visibility is useful. But appearing in an AI response is only part of the picture.

Five equally weighted dimensions describe related readiness conditions. Together, they contribute to the AI Distribution Score /100.

Five × /20

Five related questions, assessed together.

Each dimension asks a distinct question. Read them together; no dimension is a gate that must be passed before another can be measured.

Discovery

/20

Does AI surface your business in relevant buyer scenarios?

Observe whether you appear in company-blind discovery and consideration scenarios.

Understanding

/20

Does AI understand what you offer and who it is for?

Examine how accurately AI explains your offer, customers, use cases and differences.

Recommendation

/20

Does AI recommend you appropriately, for the right reasons?

Assess whether recommendations match customer suitability. Correct non-recommendation for a genuinely poor-fit customer can be positive evidence.

Reliability

/20

Can AI represent your business accurately and reliably?

Check factual support, consistency and appropriate uncertainty. This concerns reliability of AI representation, not whether your business itself is trustworthy.

Action

/20

Can AI move suitable customers towards the right next step?

Bring together AI Routing Readiness /10 and Agent Readiness /10, including useful qualification, action discovery and safe handoff.

AI Routing Readiness /10Agent Readiness /10

Action /20

Recommendation needs a route. Agents need usable evidence.

AI Routing Readiness /10

Observed AI behaviour: can the tested system identify the right next action, describe the journey and explain what a suitable customer needs to prepare?

Agent Readiness /10

Direct business/source evidence: can an agent understand the offer, determine basic suitability, identify the action and support safe initiation or handoff?

Explore Agent Readiness

Two sources of evidence

What AI says and what your business makes available.

What AI says

Responses from defined scenarios, named models and stated test channels.

What the business makes available

Direct evidence from your offer, suitability information and action routes.

  1. 01Structured evidence
  2. 02Validation
  3. 03Scoring rules
  4. 04Report

AI may assist evidence extraction. Defined rules calculate the score. Confidence stays separate.

How to read the result

Evidence sets the boundaries.

Defined rules calculate the score.

AI may assist structured evidence extraction. After validation, defined scoring rules calculate dimension and total scores. The model does not award the final score.

Confidence is descriptive and separate from score. Unavailable evidence remains visible as a limitation.

Observed behaviour needs context.

  • Recommendation includes appropriate non-recommendation for a genuine poor-fit buyer.
  • Reliability is about accuracy and support in AI representation, not business trustworthiness.
  • Results apply to the named model, stated test channel and evidence snapshot.
  • There is no universal ranking or guarantee of future recommendations.
Read the methodology note