AI GRCAPractice Lab
Step 5 of 5Evidence
05 · Practitioner output · SaaS

Approve the operating model and monitoring plan

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Your conclusion should show whether security, contractual and operational evidence supports launch to customers.

PRACTICE MODELoading

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SAAS WORKING CONTEXT

Write the SaaS release record

A fast-growing software provider is embedding third-party AI into a multi-tenant product. Enterprise customers expect security, reliability and contractual clarity.

Evidence bar
  • Release decision
  • Security sign-off
  • Customer assurance pack
REVIEW CHECKPOINTS

Operating Model Decision Pack

Operating Model Decision Pack

Complete the fields against the saas operating context. Your work saves automatically in this browser.

Write at least 20 characters of your own answer to unlock the review guide.

Write at least 20 characters of your own answer to unlock the review guide.

Write at least 20 characters of your own answer to unlock the review guide.

Write at least 20 characters of your own answer to unlock the review guide.

Write at least 20 characters of your own answer to unlock the review guide.

Write at least 20 characters of your own answer to unlock the review guide.

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ASSURANCE WORKPAPER

Test whether the controls actually operate

Move beyond policy design: define a population, select a defensible sample, test evidence, document exceptions and write the conclusion an audit committee would need.

01Define

Objective, population and period.

02Sample

Risk-based and representative items.

03Test

Inspect, observe and reperform.

04Conclude

Rate findings and communicate.

STRUCTURED ARTEFACT

Risk → control → evidence traceability

Build an auditable decision trail. A risk without a control—or a control without evidence—remains visible as a gap.

No traceability rows yet. Add the first priority risk and connect it to a control, test and evidence.

SCENARIO INJECT

The situation has changed

Choose an event and update the governance response as if the system were already operating.

NEW EVENT

Unannounced model change

The supplier upgrades the underlying model and cannot confirm whether prior validation remains representative.

The business wants to keep the original approval because users have not complained.

Write at least 40 characters to unlock the response criteria.

PRACTITIONER MATURITYLevel 1 · Initial

Work has started, but material evidence and ownership are missing.

Why this level?
  • Workflow is 0% complete.
  • Worksheet answer coverage is 0%.
  • No complete risk-control-evidence row is ready for review.
  • Rubric ratings are not yet consistently strong or competent.
READINESS GATENot ready
Workflow
0%
Answers
0%
Traceability
0 rows
Why this gate?
  • Workflow completion is 0%.
  • Answer coverage is 0%.
  • Add at least one traceability row marked ready for review.
TRAINER FEEDBACK

What to strengthen next

  • Name the affected people and explain the pathway from system behaviour to impact.
  • Assign an accountable human role; responsibility cannot sit with the AI system.
  • Define the evidence and acceptance criteria needed to support the conclusion.
  • Add post-deployment monitoring, escalation thresholds and a reassessment trigger.
SELF-ASSESS BEFORE EXPORT

Practitioner quality rubric

Rate the work honestly. “Needs revision” is a useful result when it identifies what to strengthen before review.

Context and scope

Strong: States the system, decision, actors, people affected, boundaries and material assumptions.

Improve: Avoid generic statements or conclusions that depend on unstated facts.

Risk reasoning

Strong: Links a credible cause and event to a specific impact, then assesses likelihood, severity and uncertainty.

Improve: Do not list harms without explaining how they could arise in this scenario.

Proportionate controls

Strong: Selects preventive, detective and corrective controls that address the identified risks and assigns owners.

Improve: Avoid control lists with no connection to a risk, trigger or responsible role.

Evidence and decision

Strong: Defines testable evidence, acceptance criteria, residual risk and a clear, conditional recommendation.

Improve: A confident conclusion is not defensible when evidence, thresholds or escalation routes are missing.

EVIDENCE-QUALITY GATES
Practitioner evidence pack

OperateAI

Helix Advisory Cloud · SaaS overlay · Integrated operating model and sector judgement

Prepared by
Learner name not added
Course coverage
Weeks 22–23
Training simulation only · Fictional scenario and data

Executive assignment

Helix Advisory Cloud plans a multi-tenant AI assistant that retrieves customer documents, drafts answers and prepares CRM tasks after user confirmation. It uses a hosted proprietary language model, embeddings and role-filtered retrieval.

In simple terms: The software company wants an AI assistant that can search each customer's private files, draft work and prepare actions. Users confirm actions, but weak permissions or malicious instructions could expose data or trigger the wrong task.

Assignment: Design the integrated operating model, complete supplier and lifecycle controls, and make defensible decisions across six sector case stations.

Sector overlay: SaaS

Decision pressure: The steering committee meets in 10 working days. The launch slot will be lost if the decision is deferred beyond this meeting.

Ownership gap: Product, Risk and Operations each believe another function owns final residual-risk acceptance. The governance charter is silent.

Known facts

  • The assistant retrieves documents from separate customer tenants
  • A hosted proprietary model generates answers and draft actions
  • Role permissions should filter retrieval before content reaches the model
  • Users must confirm CRM or email actions
  • Tenant-isolation, prompt-injection and rollback testing are incomplete

Integrated Governance Operating Model

Use-case intake and inventory
Not completed
Risk tiering and specialist triggers
Not completed
Decision gates and approvals
Not completed
Operating-model RACI
Not completed
Evidence repository and dashboard
Not completed
Exceptions and waivers
Not completed

Supplier & Buy-v-Build Review

Supplier AI due diligence checklist
Not completed
Vendor/licensing agreement risk review
Not completed
Buy vs build risk comparison
Not completed
Model and hosting comparison
Not completed
Supplier recommendation
Not completed

Lifecycle & Sector Judgement Record

Financial services case
Not completed
Healthcare case
Not completed
Recruitment and HR case
Not completed
Public sector case
Not completed
Insurance case
Not completed
Internal copilot case
Not completed
Incident and external communication workflow
Not completed
Deactivation and localisation policy
Not completed

Operating Model Decision Pack

Operating-model recommendation
Not completed
Post-deployment monitoring plan
Not completed
Periodic review and material change
Not completed
Retirement and exit plan
Not completed
Governance dashboard and board report
Not completed
Implementation roadmap
Not completed

Assurance testing workpaper

Assurance objective
Not completed
Population and period
Not completed
Sampling approach
Not completed
Test procedure
Not completed
Exceptions and root cause
Not completed
Finding and severity
Not completed
Management action
Not completed
Board / audit summary
Not completed

Quality review and sign-off

Reviewer: AI governance committee

Decision challenge: Can the operating model make consistent build, buy, release, monitor and retire decisions across sectors?

Context and scope
Not rated
Risk reasoning
Not rated
Proportionate controls
Not rated
Evidence and decision
Not rated

Reviewer sign-off: ____________________   Date: __________   Version: 1.0

Prepared as a learning artefact. Validate legal and regulatory conclusions against current authoritative sources before real-world use.
TRAINER REVIEW

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