Lesson 5.3: Management Review

Introduction

Management review is a critical governance mechanism in ISO 42001 that ensures top management maintains oversight of the AI Management System (AIMS). It provides a structured forum for evaluating AIMS performance, making strategic decisions, and driving continuous improvement. This lesson covers how to plan, conduct, and follow up on effective management reviews.

Understanding Management Review

Purpose and Importance

Management review serves as the strategic checkpoint where leadership:

Assesses Performance:

• Evaluates AIMS effectiveness
• Reviews achievement of AI objectives
• Analyzes key performance indicators
• Identifies performance trends

Makes Strategic Decisions:

• Allocates resources to AIMS priorities
• Approves significant changes or investments
• Sets direction for AI governance
• Addresses systemic issues

Ensures Alignment:

• Confirms AIMS supports business objectives
• Validates policy and objective relevance
• Ensures adequate resources
• Maintains management commitment

Drives Improvement:

• Identifies improvement opportunities
• Approves improvement initiatives
• Monitors improvement progress
• Celebrates successes

ISO 42001 Requirements (Clause 9.3)

Mandatory Elements

Frequency: Top management must review AIMS at planned intervals (typically quarterly or annually, depending on organizational needs).

Required Inputs (things to consider):

1. Status of actions from previous reviews

   • What was decided last time?
   • What has been implemented?
   • What remains outstanding?

2. Changes in external and internal issues

   • New AI regulations or standards
   • Technology developments
   • Organizational changes
   • Market dynamics

3. Information on AIMS performance

   • Achievement of AI objectives
   • KPI performance
   • Process effectiveness
   • Resource adequacy

4. Interested party feedback

   • Customer satisfaction and complaints
   • Regulator interactions
   • Employee feedback
   • Stakeholder concerns

5. Results of risk assessments

   • New or emerging risks
   • Risk treatment effectiveness
   • Residual risk levels
   • Risk appetite alignment

6. Opportunities for continual improvement

   • Process optimization ideas
   • Technology innovations
   • Best practice adoption
   • Benchmark findings

7. Audit findings

   • Internal audit results
   • External audit outcomes
   • Compliance status
   • Nonconformity trends

8. Performance of external providers

   • Vendor and supplier performance
   • Third-party AI services
   • Outsourced process effectiveness
   • Contract compliance

Required Outputs (decisions and actions):

1. Opportunities for continual improvement

   • Approved improvement initiatives
   • Innovation projects
   • Process enhancements

2. Any need for changes to AIMS

   • Policy updates
   • Process modifications
   • Resource adjustments
   • Scope changes

3. Resource needs

   • Budget allocation
   • Staffing requirements
   • Technology investments
   • Training needs

Planning Management Reviews

Determining Review Frequency

Quarterly Reviews (Recommended for most organizations):

• Frequent enough for timely oversight
• Allows tracking of quarterly objectives
• Aligns with business planning cycles
• Responsive to fast-changing AI landscape

Annual Reviews (Minimum requirement):

• Suitable for stable, mature AIMS
• Lower-risk AI applications
• Small organizations with limited resources

Ad Hoc Reviews:

• Triggered by significant incidents
• Major regulatory changes
• Organizational restructuring
• Certification preparation

Annual Management Review Schedule Example

2025 MANAGEMENT REVIEW SCHEDULE

Q1 Review - March 31, 2025
Focus: Annual performance review, strategic planning for year
Preparation: Week of March 24
Duration: 3 hours

Q2 Review - June 30, 2025
Focus: Progress on annual objectives, mid-year course corrections
Preparation: Week of June 23
Duration: 2 hours

Q3 Review - September 30, 2025
Focus: Risk landscape review, resource planning for next year
Preparation: Week of September 23
Duration: 2 hours

Q4 Review - December 15, 2025
Focus: Year-end performance, audit results, next year objectives
Preparation: Week of December 8
Duration: 3 hours

Special Review - As needed
Trigger events: Major incidents, regulatory changes, certification audit

Preparing for Management Review

Preparation Timeline

4 Weeks Before:

• Schedule meeting and confirm attendance
• Assign preparation responsibilities
• Request data and reports from process owners

2 Weeks Before:

• Compile input data and analyses
• Draft management review report
• Identify key discussion topics

1 Week Before:

• Finalize and distribute management review report
• Brief presenters on their sections
• Prepare presentation materials

Day Before:

• Confirm logistics and technology
• Review agenda and materials
• Prepare decision points

Data Collection and Analysis

Performance Data Sources:

Management Review Report Template

AI MANAGEMENT SYSTEM - MANAGEMENT REVIEW REPORT
Q1 2025 (January - March)

Prepared by: Jennifer Martinez, Quality Manager
Date: March 24, 2025
Review Date: March 31, 2025

EXECUTIVE SUMMARY
=================
The AIMS continues to mature with strong performance across most areas.
Key highlights:
- 3 of 4 annual objectives on track
- 1 major NC from internal audit requires attention
- Customer trust scores improving (7.2/10, up from 6.5)
- Resource constraints identified in data governance

Critical Decisions Needed:
1. Approval of additional data governance resources
2. Response to proposed EU AI Act requirements
3. Investment in automated fairness testing tools

---

1. ACTIONS FROM PREVIOUS REVIEW
================================

Review Date: December 15, 2024

| Action | Owner | Status | Comments |
|--------|-------|--------|----------|
| Implement bias monitoring dashboard | AI Lead | COMPLETED | Dashboard launched Feb 2025 |
| Hire AI Ethics Officer | HR | COMPLETED | Position filled Jan 2025 |
| Update AI policy for new regulations | Compliance | IN PROGRESS | Due April 2025 |
| Enhance vendor assessment process | Procurement | COMPLETED | New process implemented |

Summary: 3 of 4 actions completed, 1 on track.

---

2. CHANGES IN CONTEXT
======================

External Issues:
- EU AI Act implementation timeline announced (enforcement 2026)
- New state privacy law enacted (California AI Transparency Act)
- Industry competitors launching ethical AI certifications
- OpenAI GPT-5 release changing technology landscape

Internal Issues:
- Company acquired SmartData Inc. (brings 15 new AI systems)
- New product line launching Q3 requires AI capabilities
- Organizational restructure: AI team now reports to CTO
- Office expansion to London requires AIMS extension

Implications:
- Scope extension needed for acquired company's AI systems
- New regulatory requirements require policy updates
- Additional resources needed for compliance
- International operations add complexity

---

3. AIMS PERFORMANCE
===================

3.1 AI Objectives Performance

| Objective | Target | Q1 Status | YTD Trend | RAG |
|-----------|--------|-----------|-----------|-----|
| Improve model fairness (DI ratio) | <1.2 | 1.15 | ↓ Improving | 🟢 |
| Enhance transparency (% with explanations) | 100% | 85% | ↑ Improving | 🟡 |
| Reduce AI incidents | <5/year | 1 YTD | → Stable | 🟢 |
| Increase customer trust | >8.0/10 | 7.2 | ↑ Improving | 🟡 |

Overall: 2 objectives on track, 2 progressing but at risk

3.2 Key Performance Indicators

Performance Metrics:
- Model Accuracy: 94.8% (Target: >95%) - Nearly achieving 🟡
- Response Time: 115ms (Target: <150ms) - Exceeding 🟢
- System Uptime: 99.9% (Target: >99.5%) - Exceeding 🟢

Fairness Metrics:
- Disparate Impact Ratio: 1.15 (Target: <1.2) - Achieving 🟢
- False Positive Rate Parity: 1.06 (Target: <1.1) - Achieving 🟢

Privacy & Security:
- Data Breaches: 0 (Target: 0) - Achieving 🟢
- Privacy Incidents: 1 (Target: 0) - Below target 🔴
- Security Audits Passed: 4/4 (Target: 100%) - Achieving 🟢

Compliance:
- Policy Violations: 1 (Target: <5) - Achieving 🟢
- Training Completion: 97% (Target: >90%) - Exceeding 🟢
- Audit Findings Closed: 15/18 (Target: >90%) - Nearly achieving 🟡

Analysis: Strong performance overall, privacy incident requires attention

---

4. INTERESTED PARTY FEEDBACK
=============================

4.1 Customer Feedback

Satisfaction Score: 7.2/10 (up from 6.5 in Q4 2024)

Positive Themes:
- Improved chatbot accuracy and helpfulness
- Faster response times
- Better personalization

Concerns Raised:
- Desire for more transparency about AI use
- Questions about data usage
- Some bias concerns in recommendations

Action Required: Enhance transparency features in customer-facing AI

4.2 Regulatory Interactions

- FDA inquiry about AI medical device (resolved satisfactorily)
- State AG office request for AI impact assessments (in progress)
- Industry self-regulatory body audit scheduled Q2

4.3 Employee Feedback

Annual AI Ethics Survey Results:
- 92% understand AI policy (up from 85%)
- 88% feel empowered to raise ethical concerns
- 76% satisfied with AI training (improvement needed)
- 15 ethics concerns reported, all addressed

Action Required: Enhance AI training program based on feedback

---

5. RISK ASSESSMENT RESULTS
===========================

5.1 Risk Landscape Summary

Total Active Risks: 24 (High: 6, Medium: 12, Low: 6)

New Risks Identified (Q1):
- R-024: EU AI Act compliance risk (High)
- R-025: Talent retention in AI team (Medium)
- R-026: Third-party model dependency (Medium)

Risks Closed (Q1):
- R-018: Legacy system integration (treatment completed)

5.2 Top Risks Requiring Management Attention

| Risk ID | Description | Current Level | Trend | Action Needed |
|---------|-------------|---------------|-------|---------------|
| R-001 | Bias in customer-facing AI | High → Medium | ↓ | Continue monitoring |
| R-024 | EU AI Act compliance | High (New) | ↑ | Allocate compliance resources |
| R-008 | Model drift detection | Medium | → | Enhance automation |
| R-015 | Vendor lock-in | Medium | ↑ | Diversify suppliers |

5.3 Risk Appetite Alignment

Current risk-taking is aligned with approved risk appetite in most areas.
Exception: Data governance risks trending toward upper limit of appetite due
to rapid data growth and acquisition integration.

Recommendation: Consider increasing risk appetite for innovation, or increase
data governance resources to manage current risk levels.

---

6. OPPORTUNITIES FOR IMPROVEMENT
=================================

6.1 Identified Opportunities

From Internal Audits:
- Automate compliance documentation generation
- Implement predictive analytics for risk management
- Standardize AI system design patterns

From Benchmarking:
- Industry leaders using federated learning for privacy
- Competitors implementing real-time explainability
- Best practice: Dedicated AI ethics review board

From Team Suggestions:
- Developer request: Shared model repository
- Operations request: Enhanced monitoring automation
- Data team request: Data quality automation

6.2 Proposed Improvement Initiatives

| Initiative | Expected Benefit | Estimated Cost | Timeline | Priority |
|-----------|------------------|----------------|----------|----------|
| Automated fairness testing | Improve efficiency, consistency | $50K | Q2-Q3 | High |
| Federated learning pilot | Enhanced privacy, competitive advantage | $100K | Q3-Q4 | Medium |
| AI ethics board | Better governance, stakeholder trust | $25K/year | Q2 | High |
| Shared model repository | Reduce duplication, accelerate development | $30K | Q3 | Medium |

---

7. AUDIT FINDINGS
=================

7.1 Internal Audits (Q1)

Audits Completed: 3
- AI System Development (Jan 2025)
- Data Governance (Feb 2025)
- Risk Management (Mar 2025)

Findings Summary:
- Major Nonconformities: 1
- Minor Nonconformities: 3
- Observations: 8
- Strengths: 4

7.2 Key Findings

Major NC: Design review records missing for AI systems
Status: Corrective action plan approved, implementation in progress
Target closure: April 2025

Minor NCs:
1. Training records incomplete for 2 staff members
2. Data lineage documentation gaps for one dataset
3. Risk assessment review overdue for one low-risk system

All minor NCs have approved corrective action plans.

7.3 Audit Trends

Positive Trends:
- Fewer findings than previous quarter (12 vs. 15)
- Faster corrective action implementation
- More strengths identified (4 vs. 1)

Areas for Attention:
- Documentation quality remains a recurring theme
- Training compliance needs consistent oversight

---

8. EXTERNAL PROVIDER PERFORMANCE
=================================

8.1 AI Vendors and Suppliers

| Vendor | Service | Performance Rating | Issues | Action |
|--------|---------|-------------------|--------|--------|
| CloudAI Inc. | ML Platform | 4.2/5 | Minor uptime issues | Performance review scheduled |
| DataSource Corp | Training Data | 4.8/5 | None | Continue |
| ModelHost Ltd | Model Hosting | 3.9/5 | Security concerns | Audit requested |
| BiasCheck Pro | Fairness Testing | 4.5/5 | None | Continue |

8.2 Vendor Compliance

All vendors completed required security assessments.
2 vendors completed AI-specific assessments.
1 vendor audit pending (ModelHost Ltd).

Recommendation: Require AI governance assessments for all AI vendors by Q3.

---

9. RESOURCE ADEQUACY
====================

9.1 Human Resources

Current AI Team: 28 FTE
- AI Engineers: 15
- Data Scientists: 8
- AI Operations: 3
- AI Ethics: 2

Vacancies: 2 (Data Scientist, AI Security Specialist)
Recruitment in progress.

Skill Gaps Identified:
- Federated learning expertise
- EU AI Act compliance knowledge
- Advanced explainability techniques

Training Plan: Q2 upskilling program planned.

9.2 Technology Resources

Infrastructure Utilization: 78% (Adequate headroom)
Tool Licensing: All current, renewals on schedule
Budget Utilization: 85% of annual budget (on track)

Constraints:
- Data governance tools reaching capacity
- Monitoring infrastructure needs upgrade

9.3 Budget Status

Annual AIMS Budget: $1.2M
YTD Spend: $285K (24%, on track)
Committed: $650K
Available: $265K

Unbudgeted Needs Identified:
- EU AI Act compliance: ~$150K
- Data governance expansion: ~$100K
- Fairness testing automation: ~$50K

Total Additional Needed: $300K (exceeds available by $35K)

Decision Required: Budget reallocation or supplemental funding approval.

---

RECOMMENDATIONS FOR MANAGEMENT DECISION
========================================

1. RESOURCE ALLOCATION [CRITICAL]
   Approve additional $300K for:
   - EU AI Act compliance program
   - Data governance expansion
   - Fairness testing automation

2. POLICY UPDATES [HIGH PRIORITY]
   Approve updates to AI policy addressing:
   - EU AI Act requirements
   - Acquisition integration
   - International operations

3. IMPROVEMENT INITIATIVES [MEDIUM PRIORITY]
   Approve and fund:
   - AI Ethics Board establishment
   - Automated fairness testing implementation
   - Federated learning pilot

4. ORGANIZATIONAL CHANGES [HIGH PRIORITY]
   Approve:
   - Expansion of AIMS scope to include acquired company
   - London office inclusion in AIMS
   - Creation of AI Compliance Officer role

5. VENDOR MANAGEMENT [MEDIUM PRIORITY]
   Approve:
   - Enhanced vendor governance requirements
   - ModelHost Ltd audit and potential replacement
   - Vendor diversification strategy

---

CONCLUSION
==========

The AIMS demonstrates good performance and maturity in Q1 2025. The system is
generally effective with opportunities for enhancement. Critical decisions are
needed regarding resources and regulatory compliance to maintain and improve
AIMS effectiveness.

Key Strengths:
✓ Strong technical performance
✓ Improving customer trust
✓ Good audit results
✓ Engaged leadership

Key Challenges:
⚠ Resource constraints for expanding requirements
⚠ Privacy incident requires corrective action
⚠ Training completion target not fully met
⚠ Acquisition integration complexity

Overall Assessment: AIMS is suitable and effective with identified improvements.

---

APPENDICES
==========

A. Detailed KPI Dashboard
B. Complete Audit Reports
C. Risk Register
D. Financial Analysis
E. Stakeholder Feedback Summary

Conducting the Management Review Meeting

Meeting Structure

Recommended Duration: 2-3 hours for quarterly reviews

Agenda Template:

AI MANAGEMENT SYSTEM - MANAGEMENT REVIEW
March 31, 2025 | 9:00 AM - 12:00 PM | Executive Conference Room

ATTENDEES
Required: CEO, CTO, CFO, CISO, AI Director, Quality Manager
Optional: Compliance Officer, HR Director, Risk Manager

AGENDA

9:00 - 9:10 | Welcome and Objectives (CEO)
             - Review meeting purpose and objectives
             - Confirm agenda

9:10 - 9:25 | Previous Actions Review (Quality Manager)
             - Status of previous decisions and actions
             - Outstanding items discussion

9:25 - 9:40 | Context and External Environment (Compliance Officer)
             - Regulatory developments
             - Market and technology changes
             - Organizational changes

9:40 - 10:10 | AIMS Performance (AI Director)
              - AI objectives status
              - KPI review and trends
              - Process effectiveness

10:10 - 10:20 | BREAK

10:20 - 10:40 | Risk and Audit Results (Quality Manager)
               - Risk landscape update
               - Internal audit findings
               - Corrective action status

10:40 - 11:00 | Stakeholder Feedback (Customer Success / HR)
               - Customer feedback and satisfaction
               - Employee feedback
               - Regulatory interactions

11:00 - 11:20 | Resource Assessment (CFO / HR Director)
               - Budget status and needs
               - Human resource adequacy
               - Technology infrastructure

11:20 - 11:50 | Discussion and Decision-Making (All)
               - Key decisions required
               - Improvement initiatives
               - Resource allocation
               - Strategic direction

11:50 - 12:00 | Summary and Action Items (CEO)
               - Decision recap
               - Action assignments
               - Next review date

POST-MEETING
Within 5 days: Distribute management review minutes
Within 10 days: Communicate decisions to organization
Ongoing: Track action item completion

Facilitation Best Practices

1. Set the Right Tone

CEO opening example:

"Good morning everyone. Thank you for making this management review a priority.
As we've discussed, our AI systems are increasingly central to our business
strategy and customer value proposition. This review is our opportunity to
ensure we're managing AI responsibly and effectively.

I want this to be a candid discussion. We're here to make informed decisions
about our AI governance, not just check a compliance box. Please share your
perspectives openly, especially on challenges and risks.

Let's begin."

2. Focus on Strategic Discussion

• Don't just present data; discuss implications
• Encourage questions and debate
• Connect AIMS to business objectives
• Make the meeting valuable for executives

3. Drive to Decisions

Frame decision points clearly:

DECISION POINT 1: EU AI Act Compliance Resources

Background: New EU AI Act requires significant compliance efforts

Options:
A) Allocate $150K from existing budget (delay other initiatives)
B) Request supplemental budget of $150K
C) Phase implementation over 2 years with $75K annually
D) Limit EU market presence to avoid classification as high-risk

Recommendation: Option B - Request supplemental budget

Discussion points:
- EU market represents 25% of revenue
- Compliance delays risk market access
- Phased approach increases overall cost and risk
- Reducing EU presence contradicts growth strategy

Decision: [To be recorded]

4. Capture Actions Clearly

Use SMART action format:

• Specific: Clear description of what needs to be done
• Measurable: How will completion be verified?
• Assigned: Who is responsible?
• Realistic: Is it achievable?
• Time-bound: When is it due?

Management Review Minutes

Minutes Template

AI MANAGEMENT SYSTEM - MANAGEMENT REVIEW MINUTES

Meeting Date: March 31, 2025
Time: 9:00 AM - 12:00 PM
Location: Executive Conference Room

ATTENDEES

Present:
- Robert Martinez, CEO (Chair)
- Linda Chen, CTO
- David Kim, CFO
- Sarah Johnson, CISO
- Michael Rodriguez, AI Director
- Jennifer Martinez, Quality Manager
- Emily Thompson, Compliance Officer

Absent:
- None

---

1. PREVIOUS ACTIONS REVIEW

All actions from December 2024 review completed except:
- Action 2024-Q4-03: AI policy update (in progress, due April 2025)

Status accepted by management.

---

2. CONTEXT AND ENVIRONMENT

Compliance Officer presented regulatory developments:
- EU AI Act enforcement timeline: 2026
- California AI Transparency Act: Effective July 2025
- FDA guidance on AI medical devices: Published March 2025

CTO presented organizational changes:
- SmartData acquisition brings 15 AI systems into scope
- London office expansion requires AIMS extension
- New product launch Q3 will use AI extensively

Discussion: Management agreed context changes are significant and require AIMS
adaptation.

---

3. AIMS PERFORMANCE

AI Director presented performance data:
- 2 of 4 annual objectives on track
- KPIs mostly green, some yellow
- Overall performance assessed as good

CEO questioned transparency objective status (85% vs. 100% target).
AI Director explained technical challenges with legacy systems.

DECISION 1: Accept current transparency progress, but require acceleration plan.

ACTION 2025-Q1-01: AI Director to develop plan to reach 100% transparency by
Q3 2025. Due: April 15, 2025.

---

4. RISK AND AUDIT RESULTS

Quality Manager presented:
- 1 major NC from internal audit (design reviews)
- Corrective action in progress
- New high risk identified: EU AI Act compliance

Discussion: CEO expressed concern about design review finding. CTO explained
root cause and corrective actions. CEO accepted explanation and emphasized
importance of completion.

CFO raised concern about increasing compliance costs. Discussion of risk
appetite and resource prioritization followed.

DECISION 2: Risk appetite remains appropriate. Resource constraints to be
addressed through budget discussion.

---

5. STAKEHOLDER FEEDBACK

Customer Success presented improving trust scores (7.2/10).
Positive feedback noted, transparency concerns highlighted.

HR Director presented employee survey results. Training satisfaction
identified as improvement area.

DECISION 3: Approve investment in enhanced AI training program.

ACTION 2025-Q1-02: HR Director to develop comprehensive AI training program
for all staff. Budget: $50K. Due: Q2 2025.

---

6. RESOURCE ASSESSMENT

CFO presented budget status and additional needs ($300K unbudgeted).

Detailed discussion of priorities:
- EU AI Act compliance: Critical, cannot delay
- Data governance: Important for acquisition integration
- Fairness testing: Valuable but could delay to next year

DECISION 4: Approve supplemental budget of $250K for EU AI Act compliance
($150K) and data governance ($100K). Fairness testing to be funded in 2026
budget.

CFO: Motion to approve supplemental budget
CISO: Second
Vote: Unanimous approval

ACTION 2025-Q1-03: CFO to process supplemental budget allocation. Immediate.

---

7. IMPROVEMENT OPPORTUNITIES

AI Director presented proposed improvement initiatives:
- AI Ethics Board
- Automated fairness testing
- Federated learning pilot
- Shared model repository

Discussion of priorities and resources.

DECISION 5: Approve AI Ethics Board establishment (Q2 2025). Other initiatives
to be reconsidered in Q2 or Q3 when resources available.

ACTION 2025-Q1-04: AI Director to establish AI Ethics Board with charter,
membership, and meeting schedule. Budget: $25K annual. Due: June 30, 2025.

---

8. POLICY AND SCOPE UPDATES

Compliance Officer recommended policy updates for regulatory changes and
acquisition integration.

DECISION 6: Approve AI policy update to address EU AI Act, California
regulations, and acquired company integration.

ACTION 2025-Q1-05: Compliance Officer to finalize policy updates with legal
review. Due: May 31, 2025.

DECISION 7: Extend AIMS scope to include:
- All AI systems from SmartData acquisition
- London office operations
- New product line AI components

ACTION 2025-Q1-06: Quality Manager to update AIMS scope document and implement
extension plan. Due: June 30, 2025.

---

9. VENDOR MANAGEMENT

CISO raised concerns about ModelHost Ltd security practices.

DECISION 8: Approve audit of ModelHost Ltd. If significant issues found,
initiate vendor replacement process.

ACTION 2025-Q1-07: CISO to conduct ModelHost audit and report findings. Due:
May 31, 2025.

---

SUMMARY OF DECISIONS

1. Accept transparency objective progress with acceleration plan
2. Maintain current risk appetite
3. Invest in enhanced AI training program
4. Approve $250K supplemental budget for compliance and data governance
5. Establish AI Ethics Board
6. Update AI policy for regulatory and organizational changes
7. Extend AIMS scope for acquisition and expansion
8. Audit ModelHost vendor and prepare replacement if needed

---

SUMMARY OF ACTIONS

| Action | Description | Owner | Due Date |
|--------|-------------|-------|----------|
| 2025-Q1-01 | Transparency acceleration plan | AI Director | Apr 15, 2025 |
| 2025-Q1-02 | Enhanced AI training program | HR Director | Q2 2025 |
| 2025-Q1-03 | Process supplemental budget | CFO | Immediate |
| 2025-Q1-04 | Establish AI Ethics Board | AI Director | Jun 30, 2025 |
| 2025-Q1-05 | Update AI policy | Compliance Officer | May 31, 2025 |
| 2025-Q1-06 | Extend AIMS scope | Quality Manager | Jun 30, 2025 |
| 2025-Q1-07 | Audit ModelHost vendor | CISO | May 31, 2025 |

---

NEXT REVIEW

Date: June 30, 2025
Focus: Mid-year objectives review, action item progress, Q2 performance

---

MEETING CONCLUSION

CEO thanked participants and emphasized the importance of AIMS to organizational
strategy. Expressed confidence in team's ability to address challenges and
capitalize on opportunities. Meeting adjourned at 12:05 PM.

Prepared by: Jennifer Martinez, Quality Manager
Date: April 2, 2025
Reviewed by: Robert Martinez, CEO
Approved: April 3, 2025
Distribution: All attendees, Document Management System

Following Up on Management Review

Action Tracking

Action Tracking System:

Monitoring Process:

• Monthly status updates from action owners
• Red/yellow/green status reporting
• Escalation of overdue or at-risk actions
• Review at next management review

Communicating Decisions

Communication Plan:

Sample All-Hands Communication:

Subject: AI Management System - Key Decisions from Management Review

Dear Team,

Our leadership team completed our quarterly AI Management System review last
week. I wanted to share some key decisions that affect all of us:

WHAT WE DECIDED:
1. Expanded our AI Ethics Board to provide stronger governance
2. Invested in enhanced AI training for everyone
3. Extended our AIMS to include our new SmartData colleagues
4. Committed resources to ensure EU AI Act compliance

WHAT THIS MEANS FOR YOU:
- You'll have access to better AI training resources starting in Q2
- New team members from SmartData will be joining our AIMS community
- We're maintaining our commitment to responsible AI practices
- Your feedback continues to shape our AI governance approach

Thank you for your continued dedication to ethical and effective AI. If you
have questions, please reach out to your manager or the AI Director.

Best regards,
Robert Martinez, CEO

Common Management Review Challenges

Challenge 1: Low Engagement

Symptoms:

• Executives multitasking during review
• Minimal discussion or questions
• Rubber-stamp approvals without scrutiny

Solutions:

• Keep presentations concise and strategic
• Pre-read materials sent in advance
• Focus on decisions, not just information
• Connect AIMS to business priorities
• Use visual dashboards instead of dense reports

Challenge 2: Inadequate Preparation

Symptoms:

• Data not available or incomplete
• Last-minute scrambling for information
• Presenters unprepared

Solutions:

• Establish clear preparation timeline
• Assign data gathering responsibilities early
• Use templates and standardized reporting
• Automate data collection where possible

Challenge 3: No Decisions Made

Symptoms:

• Review becomes information session only
• Issues discussed but not resolved
• Actions deferred to "offline" discussions

Solutions:

• Frame decision points explicitly
• Provide recommendations, not just options
• Chair actively seeks decisions
• Document decisions immediately
• Limited scope to allow time for decision-making

Challenge 4: Poor Follow-Through

Symptoms:

• Action items not completed
• No accountability for actions
• Same issues appear in every review

Solutions:

• Clear action ownership and deadlines
• Monthly action tracking and reporting
• Escalate overdue actions to executives
• Celebrate completed actions
• Include action completion rate as KPI

Management Review Best Practices

1. Make It Strategic

Focus on:

• How AIMS supports business objectives
• Strategic risks and opportunities
• Major investments and resource decisions
• Long-term AI governance direction

Avoid:

• Excessive technical detail
• Operational minutiae
• Information without analysis
• Blame or finger-pointing

2. Use Data Effectively

Good Data Presentation:

• Visual dashboards and charts
• Trend analysis, not just point-in-time
• Benchmarks and comparisons
• Red/yellow/green status indicators
• Focus on exceptions and outliers

Poor Data Presentation:

• Dense tables of numbers
• Inconsistent metrics across reviews
• Data without interpretation
• No context or baselines

3. Maintain Continuity

• Consistent format across reviews
• Same KPIs tracked over time
• Follow-up on previous decisions
• Track trends and patterns
• Build institutional memory

4. Ensure Independence

Quality Manager or similar independent role should:

• Prepare review materials objectively
• Present audit findings without bias
• Highlight issues even if uncomfortable
• Provide independent assessment of AIMS effectiveness

5. Document Thoroughly

Good minutes include:

• Who was present
• What was discussed
• What was decided
• Who will do what by when
• Rationale for decisions

Poor minutes:

• Vague or ambiguous language
• Missing decision rationale
• No clear action items
• Unclear responsibilities

Integrating Management Review with Other Processes

Connection to Strategic Planning

Management review informs:

• Annual strategic planning
• Budget development
• Resource allocation
• Technology roadmap

Strategic planning informs:

• AI objectives
• AIMS priorities
• Risk appetite
• Investment decisions

Connection to Risk Management

Management review:

• Approves risk appetite and tolerance
• Reviews high-level risks
• Approves risk treatment strategies
• Allocates risk management resources

Risk management provides:

• Risk assessment results
• Treatment effectiveness reports
• Emerging risk identification
• Risk landscape analysis

Connection to Performance Management

Management review:

• Sets objectives and KPIs
• Reviews performance results
• Adjusts targets as needed
• Recognizes achievements

Performance management provides:

• KPI data and trends
• Objective status
• Process effectiveness measures
• Improvement opportunities

Preparing for Certification Audit

Auditors will review:

• Management review schedule and compliance
• Quality of review inputs
• Substantive decision-making
• Action follow-through
• Minutes documentation

Certification Readiness Checklist:

• Reviews conducted at planned intervals
• All required inputs addressed
• Decisions and actions documented
• Action items tracked and completed
• Minutes approved and retained
• Evidence of management engagement
• Link between review and improvements

Summary

Management review is the strategic governance mechanism for AIMS. Key takeaways:

1. Leadership Engagement: Top management must actively participate and make decisions
2. Comprehensive Inputs: Consider all required elements from ISO 42001
3. Strategic Focus: Connect AIMS to business objectives and strategy
4. Decision-Driven: Use review to make meaningful decisions and allocate resources
5. Thorough Documentation: Capture decisions, actions, and rationale clearly
6. Effective Follow-Up: Track actions and ensure completion
7. Continuous Improvement: Use review to drive AIMS enhancement

Remember: Management review is not just a compliance checkbox—it's a powerful tool for strategic AI governance and business value creation.

Next Steps

In the next lesson, we'll cover the Certification Audit Process, where you'll learn what to expect during Stage 1 and Stage 2 audits and how to successfully achieve ISO 42001 certification.