Use mapping
Tools, teams, data, decisions, outputs and dependencies.

DOSSIER 1101
Give teams freedom to use AI without making data, decisions and accountability invisible.
Operational briefOperational brief
Risk appears in real practices: copying data, delegating a decision, publishing without control or depending on a supplier. Governance must be understandable, testable and usable every day.
MEASUREMENT WORKSHOP
The denominator changes the interpretation. Of 50 planned trials, 40 finish and 32 pass: success among completed trials is 80%, but success across the whole programme is 64%. Keep the ten unfinished trials visible.

AI-generated illustration
Fictional example · no measurement of this site or a client
| Indicator | Calculation or threshold | What the result establishes |
|---|---|---|
| Programme completion | 40 / 50 × 100 = 80 % | 40 / 50 = 80%: ten trials still lack a completed outcome. |
| Success across all planned trials | 32 / 50 × 100 = 64 % | 32 / 50 = 64%: an unfinished trial is not a success. |
| Success among completed trials | 32 / 40 × 100 = 80 % | 32 / 40 = 80%: this conditional rate excludes ten unfinished trials. |
Write the expected outcome, allowed access, time limit and critical errors.
Separate success, completed failure and non-completion. Critical failures are a subset of completed failures.
Examine each incident and recovery path. A favourable average cannot authorize deployment.
Before testing, the programme sets a limit of zero unauthorized actions. Of 50 tasks, 40 finish; one forbidden action occurs during a completed task.
| Observed unit | Fictional data |
|---|---|
| Completed tasks | 40 / 50 = 80 % |
| Observed unauthorized actions | 1 |
| Maximum agreed before testing | 0 |
No: the incident exceeds the agreed limit even though its task is complete. Keep completion and permissions separate; apply the stopping rule and verify the fix on that scenario.
Sources, permissions, evaluation, validation, logs and stopping conditions are designed with the system. Performance matters only while data, decisions and reversibility remain governable.
Transparent panels and documents in a control workspace. Illustrative scene.
02 / Intervention areas
Tools, teams, data, decisions, outputs and dependencies.
Impact, sensitivity, autonomy, recipients and correction potential.
Authorised, supervised and prohibited actions plus traceability duties.
Quality, robustness, bias, security, cost and out-of-scope behaviour.
Validation points, required skill and authority to stop.
Detection, shutdown, evidence preservation, notification and correction.
03 / FIELD NOTES
As soon as use moves beyond individual experimentation and touches data, clients or decisions.
Teams use multiple assistants without a common framework or inventory.
A system can publish, send, modify data or trigger a process.
Prompts or documents contain personal, strategic or contractual material.
An important function relies on a model, API or terms that may change.
04 / OUTPUTS
Short rules, a maintained register and concrete evaluation are better than an unusable charter.
Purpose, tool, owner, data, risk and status.
Principles, allowed cases, prohibitions and validation duties.
Common criteria and proportionate control levels.
Data, retention, jurisdiction, security, cost and reversibility.
Test sets, thresholds, critical failures and frequency.
Shutdown, escalation, evidence, correction and lessons learned.
WORKING RECORDS
Three practical records connecting diagnosis to a traceable decision.
Minimum content : For each use: purpose, owner, data, provider, affected people and any automated decision.
Check : Was a new use introduced without an owner?
Minimum content : Connect each risk to a safeguard, operating evidence, review frequency and repair owner.
Check : Does the control work in production or exist only in policy?
Minimum content : Trace trigger, effects, stop decision, people notified, recovery and incorporated lesson.
Check : Can the event be reconstructed and a close recurrence prevented?
05 / Method
The framework is designed with users, tested on real cases and reviewed as tools or risks evolve.
DECISION CHECKS
Two checks that change the next decision.
Ask teams which data they submit, which decisions receive AI support and which tools are connected. Classify cases by potential impact before choosing controls.
Record its reason, scope, owner and expiry date. Review it after an incident or model change; an indefinite exception bypasses the policy.
Two approaches to distinguish
The right method depends on the question and the decision it must inform.
Defines allowed data, tasks, tools and responsibilities. It provides a shared frame but does not alone show that real use follows the rules.
Samples actual tasks, logs, exceptions and incidents. Checks permissions, output quality and human takeover; findings change the policy or tool.
Adapt this outline to the agreed scope. It describes a proposed method, not a completed mission, measured result or guaranteed schedule. Record your observations and decisions as checks proceed.

AI-generated illustration
Proposed uses, responsible actors, data and known vendors. Identify sensitive decisions and review mechanisms.
Inventory each use with purpose, owner and affected groups. Show dependencies and information still unknown.
Associate risks, checks and an approval owner. Prepare escalation and stopping rules before starting the system.
Review incidents, changes and check results on a defined schedule. Retain decisions and reasons for exceptions.
A use without an owner or checkable control remains unapproved. A governance register is not compliance certification.
06 / FAQ
Clear answers on scope, limits, methods and engagement conditions.
Not systematically. Uses and data should be classified, with suitable alternatives.
Shared responsibility with one accountable decision-maker and business, technical and security owners.
No. It needs inventory, controls, evaluation and an incident mechanism.
Through regular tests, version monitoring and reassessment thresholds.
Only if the person has the time, skill and information needed.
Depending on purpose, legal basis, contracts, security and applicable rules; specialist analysis may be needed.
Concentrate controls on risky uses and provide safe paths for experimentation.
Official documents explaining methods, review criteria and their limits. These references do not certify the service or guarantee search rankings.
08 / CONTACT
State the context and objective. You will receive a clear initial reading.
DEEPER READING / PRACTICE
A tool is adopted by several teams without common rules. Governance begins with the inventory of uses, processed information and decisions that can be affected.
Updated on .
Define the owner of the use, user, validation manager and person responsible for the incidents. Document the data categories and the conditions of maintenance or stop.
A general policy can remain abstract if it does not specify who controls the outputs. A human validation without sufficient information can become a simple formality.
The usage register connects purpose, data, tool, responsibility and control. Incidents and scope changes trigger a system re-evaluation.
Define authorised uses, the review owner and suspension conditions. A nonexistent reference in a documentary synthesis should trigger verification before distribution.
Evaluate representative tasks and consequences. Document model changes, incidents and the fallback to a controlled process rather than extending one successful result to all uses.