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This page is generated by scripts/generate_coverage_matrix.py --type frontier from assessment/manifest/frontier-readiness.json. Do not edit by hand.
It is the honest answer to what does the Frontier Readiness assessment actually automate today? In the current manifest, 6 of 25 questions (24.0%) are telemetry-backed, 19 remain facilitator-answered by design, and 0 still declare automation that is not yet wired.
Evaluator states
State
Icon
Meaning
auto_evaluable
✅
Evaluator is registered AND auto_evaluable: true in the manifest. Score derived from telemetry.
unimplemented_evaluator
⚠️
Manifest declares a pass_condition but the question is marked auto_evaluable: false and no evaluator function exists. (Most common state in v1.)
manual_only
📝
Question is manual by design (collection_methods: ["Manual"] and auto_evaluable: false). Facilitator-answered only.
Summary
By question
State
Count
Share
✅ Auto
6
24.0%
📝 Manual
19
76.0%
⚠️ Unimplemented
0
0.0%
Total
25
100%
Per-driver breakdown
Driver
Total Questions
Auto
Manual
Unimplemented
AI Strategy & Experience
5
2
3
0
Business Strategy
5
0
5
0
AI Governance & Security
5
1
4
0
Technology & Data
5
3
2
0
Organization & Culture
5
0
5
0
Per-question detail
AI Strategy & Experience
Q ID
Level
Question
State
Pass Condition
Notes
Q01
100
Has the organization identified at least one named individual responsible for...
✅ Auto
ai_initiative_owner_identified
Q02
200
Within at least one business unit, do AI agent investments follow recurring, ...
📝 Manual
bu_level_repeatable_intake_pattern
Facilitator-answered.
Q03
300
Has the organization published an enterprise AI strategy reviewed by a Govern...
✅ Auto
enterprise_ai_strategy_published_with_portfolio
Auto-evaluator capped at 'partial' — site naming heuristic detects strategy publication, but governance review + portfolio scope are facilitator-only.
Q04
400
Is the AI strategy refreshed on a documented cadence aligned to the firm's go...
📝 Manual
strategy_refresh_cadence_with_board_reporting
Facilitator-answered.
Q05
500
Do named executive sponsors provide quarterly outcome attestation for each pa...
Auto-evaluator caps suggested answer at 'partial' because model-risk overlay (the third L300 signal) is not telemetry-verifiable. Facilitator must confirm model risk separately to upgrade to 'yes'.
Q14
400
Do risk metrics flow into a risk committee on a documented cadence, supported...
📝 Manual
risk_metrics_to_committee_with_tested_runbooks
Facilitator-answered.
Q15
500
Does the organization operate continuous control monitoring with risk-tier-ba...
Is there any visibility into which Power Platform environments host AI agents...
✅ Auto
any_environment_visibility_for_agents
Q17
200
Are some environments tagged or grouped for agent workloads, with basic telem...
✅ Auto
tagged_environments_with_basic_telemetry
Q18
300
Are Environment Groups with tier classification operational, with automated a...
✅ Auto
env_groups_with_inventory_siem_rag_and_lineage
Auto-evaluator capped at 'partial' — 3/5 signals are telemetry-verifiable (env groups, SIEM, SP scan), but agent inventory is not collected and RAG-integrity + lineage are facilitator-only.
Q19
400
Does the platform provide integrated telemetry across Sentinel, the Agent 365...
The remaining manual questions already carry pass_condition strings in the manifest, so the per-question table above is the live backlog for future evaluator work. Add an explicit shortlist here when a specific implementation wave is planned.
No separate future-evaluator shortlist is maintained yet.
How to wire up an evaluator (future)
Add a _eval_<name>(collected, source_key) function to a new assessment/engine/score_frontier.py evaluators block, returning (passed: bool | None, evidence: str).
Update the question entry in frontier-readiness.json: set auto_evaluable: true, change collection_methods to include the API source (Graph_API, SharePoint_PnP, etc.).
Re-run python scripts/generate_coverage_matrix.py --type frontier and commit the regenerated docs/reference/frontier-assessment-coverage.md.