SOP-1062-01-AI_Risk-Register-Management
Title: Risk Register Management
Revision: 1.0
Effective Date: (Date of Approval)
Previous Version: None
Reason for Update: New SOP
Owner: Delivery Operations Lead
Location: (Specify Repository or Portal)
Approvals:
| Name/Title | Signature | Date |
|---|---|---|
| AI-IRB Board Liaison | ____________ | _______ |
| Delivery Operations Lead | ____________ | _______ |
| Quality Assurance Lead | ____________ | _______ |
| Account/Engagement Manager | ____________ | _______ |
1. Objective
This Standard Operating Procedure (SOP) defines the process for creating, maintaining, and governing a Risk Register for AI transformation engagements under the AI-SDLC. The Risk Register serves as the central artifact for identifying, scoring, mitigating, and tracking risks that could prevent on-time, on-scope, compliant delivery and strong client outcomes.
This SOP ensures that:
- All material risks are identified early and tracked continuously
- Risks are scored consistently using a standardized methodology
- Mitigations and contingencies are defined and owned
- Escalation paths are clear and tied to AI-IRB gates
- Client-facing risk communication is managed appropriately
2. Scope
This SOP applies to all AI transformation engagements governed by the AI-SDLC, from initial scoping through post-implementation support. It covers:
- AI System Risks: Model drift, bias, performance degradation, compliance failures, data quality issues
- Operational Delivery Risks: Handoff gaps, capacity constraints, tooling failures, QA gaps, scope creep
- Client-Dependent Risks: Access delays, stakeholder availability, security review timing
- Commercial Risks: SOW ambiguity, change control failures, billing disputes
- Vendor/External Risks: Third-party outages, integration brittleness, regulatory changes
This SOP complements but does not replace:
- SOP-1053-01-AI (Ethical Risk Assessment & Mitigation) for deep ethical risk analysis
- SOP-1061-01-AI (Incident Tracking) for production defects and incidents
- SOP-1009-01-AI (Model Drift and Re-Validation) for model-specific monitoring
3. Roles and Responsibilities
| Role | Responsibility |
|---|---|
| Delivery Lead | Creates and maintains the Risk Register. Owns risk identification, scoring, and mitigation tracking. Facilitates weekly risk reviews. |
| Account Manager | Reviews client-facing risk summaries. Manages client communication on high-priority risks. Owns commercial and relationship risks. |
| AI-IRB Liaison | Reviews risks with ethical, regulatory, or compliance implications. Escalates to AI-IRB when thresholds are breached. Approves risk acceptance for high-severity items. |
| Technical Lead | Identifies and owns technology risks (integrations, tooling, infrastructure). Validates technical mitigations. |
| Onboarding Lead | Owns onboarding-phase risks during client setup. Hands off to Delivery Lead post-kickoff. |
| Quality Assurance | Validates that risk mitigations are implemented. Flags QA-related risks. Reviews risk register completeness at gate checkpoints. |
| Project Manager | Ensures risk review is scheduled and occurs. Tracks mitigation actions in project plan. Escalates blocked mitigations. |
| Client Sponsor | (External) Informed of high-priority risks. Owns client-side mitigations (access, data, approvals). |
4. Definitions
| Term | Definition |
|---|---|
| Risk | An uncertain event or condition that, if it occurs, has a negative effect on project objectives (timeline, scope, quality, cost, compliance). |
| Risk Statement | A structured description following the format: “If [cause], then [risk event] occurs, leading to [impact].” |
| Likelihood (L) | Probability that the risk will materialize. Scored 1-5. |
| Impact (I) | Severity of consequences if the risk materializes. Scored 1-5. |
| Risk Score | Likelihood × Impact. Used to prioritize risks. |
| Priority | Classification based on Risk Score: High (≥15), Medium (8-14), Low (≤7). |
| Mitigation | Preventive controls or actions that reduce likelihood or impact before the risk materializes. |
| Contingency | Response plan activated if the risk materializes despite mitigations. |
| Trigger/Early Warning | Observable indicator that a risk is becoming more likely or has materialized. |
| Risk Owner | The role accountable for monitoring the risk and executing mitigations. |
| Residual Risk | Risk remaining after mitigations are applied. |
| Risk Acceptance | Formal acknowledgment that a risk will not be further mitigated, with documented rationale. |
5. Scoring Methodology
5.1 Likelihood Scale
| Score | Label | Definition |
|---|---|---|
| 1 | Rare | Unlikely to occur; no historical precedent |
| 2 | Unlikely | Could occur but not expected; few precedents |
| 3 | Possible | May occur; some precedents or warning signs |
| 4 | Likely | Probably will occur; multiple precedents or active warning signs |
| 5 | Almost Certain | Expected to occur; currently occurring or imminent |
5.2 Impact Scale
| Score | Label | Definition |
|---|---|---|
| 1 | Minor | Negligible effect on timeline, cost, or quality; easily absorbed |
| 2 | Moderate | Some effect; requires adjustment but recoverable within sprint/phase |
| 3 | Major | Significant effect; requires re-planning, client communication, or scope adjustment |
| 4 | Severe | Serious effect; threatens milestone delivery, SLA breach, or client relationship |
| 5 | Critical | Project-threatening; potential termination, compliance violation, or reputational damage |
5.3 Priority Thresholds
| Risk Score | Priority | Required Response |
|---|---|---|
| 15-25 | High | Immediate action required. Escalate to Account Manager and AI-IRB Liaison. Weekly review minimum. |
| 8-14 | Medium | Active monitoring. Mitigations must be in place. Bi-weekly review minimum. |
| 1-7 | Low | Monitor during standard reviews. Mitigations optional but recommended. |
6. Risk Register Structure
The Risk Register is maintained using the following template:
6.1 Required Columns
| Column | Description |
|---|---|
| ID | Unique identifier (e.g., R-01, R-02) |
| Phase | Onboarding / Fulfillment / Both |
| Risk Name | Short, readable name (2-4 words) for quick scanning |
| Risk Statement | Structured as: “If [cause], then [risk] occurs, leading to [impact]” |
| Category | People / Process / Technology / Client / Compliance / Vendor / Financial / Data |
| Likelihood | Score 1-5 (see Scoring Reference) |
| Impact | Score 1-5 (see Scoring Reference) |
| Score | Likelihood × Impact (calculated) |
| Priority | High / Medium / Low (derived from Score) |
| Primary Mitigations | Preventive controls and actions |
| Contingency/Response | Plan if risk materializes |
| Owner | Role responsible for this risk |
| Triggers/Early Warnings | Observable indicators |
| Status | Open / Mitigating / Accepted / Closed |
| Client-Facing | Yes / No (whether to include in client risk summary) |
| AI-IRB Flag | Yes / No (whether AI-IRB review is required) |
| Date Identified | When risk was added |
| Last Reviewed | Date of most recent review |
| Notes/History | Running log of status changes and decisions |
6.2 Client-Facing vs. Internal
- Client-Facing (Yes): Risk ID, Phase, Risk Statement (simplified), Priority, Status, Owner (role only). Shared in governance meetings.
- Internal Only: Detailed mitigations, contingencies, triggers, AI-IRB flags, scoring rationale, history notes.
7. Procedure Activities
7.1 Risk Register Initialization
Trigger: Engagement kickoff or SOW signature
- Delivery Lead creates a new Risk Register from the template.
- Delivery Lead conducts initial risk identification session with:
- Account Manager (commercial/relationship risks)
- Technical Lead (technology/integration risks)
- Onboarding Lead (setup/access risks)
- Delivery Lead populates initial risks using:
- SOW review (scope ambiguity, assumptions, exclusions)
- Client profile (industry, maturity, known constraints)
- Historical patterns from similar engagements
- Standard risk catalog (see Section 9)
- Delivery Lead scores each risk and assigns owners.
- AI-IRB Liaison reviews any risks flagged for ethical/compliance implications.
- Quality Assurance validates register completeness against checklist.
- Initial register is baselined and stored in engagement repository.
Output: Populated Risk Register with initial risks scored and owned.
7.2 Ongoing Risk Identification
Trigger: Continuous throughout engagement
New risks may be identified through:
- Weekly team standups
- Client interactions (complaints, delays, scope questions)
- Technical discovery (integration issues, data quality findings)
- AI-IRB reviews at gate checkpoints
- Incident reports (per SOP-1061-01-AI)
- Model monitoring alerts (per SOP-1009-01-AI)
Process:
- Any team member can submit a risk via Slack, email, or directly in the register.
- Delivery Lead triages within 24 hours: validates, scores, assigns owner.
- If Priority = High, immediate notification to Account Manager and AI-IRB Liaison.
- If AI-IRB Flag = Yes, AI-IRB Liaison reviews within 48 hours.
7.3 Risk Review Cadence
| Review Type | Frequency | Participants | Focus |
|---|---|---|---|
| Weekly Risk Review | Weekly | Delivery Lead, Technical Lead, PM | All open risks; status updates; new risks |
| Client Governance | Bi-weekly or per SOW | Account Manager, Client Sponsor | High/Medium client-facing risks; escalations |
| Gate Checkpoint | Per AI-SDLC gate | All + AI-IRB Liaison | Comprehensive review; gate-blocking risks |
| Quarterly Portfolio | Quarterly | Senior Management | Cross-engagement patterns; systemic risks |
7.4 Risk Scoring Updates
Risks are re-scored when:
- Mitigations are implemented (may reduce Likelihood or Impact)
- New information emerges (triggers observed, situation changes)
- Time passes without mitigation progress (may increase Likelihood)
- Client or external conditions change
Process:
- Risk Owner proposes score change with rationale.
- Delivery Lead validates and updates register.
- If Priority changes (especially Low→Medium or Medium→High), notify relevant stakeholders.
- Document change in Notes/History column.
7.5 Risk Escalation
Escalation Triggers:
- Any risk scores ≥20 (L×I)
- Risk Priority increases to High
- Mitigation blocked for >5 business days
- Trigger/early warning observed
- AI-IRB flags unresolved ethical or compliance concern
Escalation Path:
- Delivery Lead → Account Manager (all High priority risks)
- Account Manager → Client Sponsor (client-dependent risks blocking progress)
- Delivery Lead → AI-IRB Liaison (compliance, ethical, or regulatory risks)
- AI-IRB Liaison → AI-IRB Board (per SOP-1006-01-AI thresholds)
- Account Manager → Senior Management (engagement-threatening risks)
7.6 Risk Closure
A risk may be closed when:
- Mitigated: Controls are in place and verified effective
- Avoided: Scope or approach changed to eliminate the risk
- Transferred: Risk shifted to client or third party (with documentation)
- Accepted: Residual risk formally accepted by appropriate authority
- Occurred: Risk materialized; now tracked as incident (per SOP-1061-01-AI)
Process:
- Risk Owner proposes closure with rationale.
- Delivery Lead validates closure criteria are met.
- If Priority was High, Account Manager and AI-IRB Liaison approve closure.
- Status updated to Closed; closure date and rationale documented.
- Risk retained in register for historical reference.
7.7 AI-IRB Gate Integration
The Risk Register is reviewed at each AI-IRB gate checkpoint:
| Gate | Risk Review Focus |
|---|---|
| G-12 (Vision) | Strategic and scoping risks; ethical alignment |
| G-11 (Data Readiness) | Data quality, bias, privacy risks |
| G-10 (Tool Selection) | Technology, integration, vendor risks |
| G-8 (Team Readiness) | Resourcing, skill gap, collaboration risks |
| G-4 (Pilot Validation) | Pilot scope, assumption validation risks |
| G-2 (Scalability) | Scaling, performance, amplification risks |
| G-0 (Governance) | Ongoing monitoring, drift, compliance risks |
Gate Blocking: Any High priority risk with AI-IRB Flag = Yes must be resolved or formally accepted before gate passage.
8. Metrics
| Metric | Definition | Target |
|---|---|---|
| Risk Identification Rate | New risks identified per week during active delivery | 1-3 (indicates healthy vigilance) |
| High Priority Risk Count | Number of open High priority risks | ≤3 at any time |
| Mitigation Implementation Rate | % of mitigations completed within planned timeframe | ≥80% |
| Risk Review Compliance | % of scheduled risk reviews completed | 100% |
| Escalation Response Time | Time from escalation trigger to stakeholder notification | <24 hours |
| Risk Closure Rate | % of risks closed per month (excluding new) | Trending positive |
| Risks Materialized | Count of risks that became incidents | Minimize; track for learning |
9. Standard Risk Catalog
The following risks should be evaluated for inclusion in every new engagement. Not all will apply; score and include those relevant to the specific context.
9.1 Onboarding Phase
| ID | Risk Name | Risk Statement |
|---|---|---|
| R-ONB-01 | Incomplete sales handoff | If sales-to-delivery handoff is incomplete, then delivery team lacks critical context, leading to mis-scoped onboarding and rework. |
| R-ONB-02 | Vague acceptance criteria | If SOW/SLA acceptance criteria are vague, then expectations diverge, leading to scope disputes and delayed sign-off. |
| R-ONB-03 | Client access delays | If client delays access/credentials/data, then setup stalls, leading to missed go-live and reduced confidence. |
| R-ONB-04 | Late security review | If security/privacy review starts late, then approval delays occur, leading to blocked data transfer and onboarding stalls. |
| R-ONB-05 | Rushed discovery | If discovery is rushed or stakeholders unavailable, then requirements are incomplete, leading to wrong configuration and rework. |
| R-ONB-06 | Slow internal provisioning | If internal tooling/provisioning is slow, then setup is delayed, leading to late start and missed milestones. |
| R-ONB-07 | Insufficient training | If onboarding documentation/training is insufficient, then client users struggle, leading to low adoption and early churn risk. |
9.2 Fulfillment Phase
| ID | Risk Name | Risk Statement |
|---|---|---|
| R-FUL-01 | Capacity overload | If effort is underestimated and capacity planning is weak, then team overload occurs, leading to delivery delays and burnout. |
| R-FUL-02 | Key person dependency | If there’s a single point of failure (key person dependency), then absence causes disruption, leading to service interruption. |
| R-FUL-03 | Brittle integrations | If integrations/automations are brittle, then failures go unnoticed, leading to silent data/process breaks and incorrect outputs. |
| R-FUL-04 | Weak QA gates | If QA gates are weak, then defects reach client, leading to trust erosion and rework. |
| R-FUL-05 | Uncontrolled scope creep | If change requests aren’t controlled, then scope creeps, leading to timeline/budget overrun. |
| R-FUL-06 | Missing SLA instrumentation | If SLA and operational metrics aren’t instrumented, then breaches occur unexpectedly, leading to penalties and dissatisfaction. |
| R-FUL-07 | Poor reporting inputs | If reporting is based on poor-quality inputs, then insights are wrong, leading to bad decisions by client. |
9.3 AI System Risks
| ID | Risk Name | Risk Statement |
|---|---|---|
| R-AI-01 | Training data bias | If training data contains bias, then model outputs perpetuate inequities, leading to ethical violations and reputational damage. |
| R-AI-02 | Unmonitored model drift | If model drift is not monitored, then performance degrades silently, leading to incorrect predictions and lost trust. |
| R-AI-03 | Insufficient explainability | If explainability is insufficient, then stakeholders cannot validate decisions, leading to compliance failures and rejection. |
| R-AI-04 | Degraded data quality | If data quality degrades post-deployment, then model inputs become unreliable, leading to degraded outputs. |
| R-AI-05 | Regulatory changes | If regulatory requirements change, then existing compliance may lapse, leading to legal exposure. |
9.4 Cross-Cutting Risks
| ID | Risk Name | Risk Statement |
|---|---|---|
| R-XCT-01 | Unclear roles/RACI | If roles/responsibilities are unclear, then work falls through cracks, leading to missed tasks and SLA/quality issues. |
| R-XCT-02 | Vendor/tool outage | If a critical third-party vendor/tool has outage/changes, then operations break, leading to service disruption. |
| R-XCT-03 | Compliance mishandling | If compliance obligations (PII, SOC2, GDPR) are mishandled, then violations occur, leading to legal and reputational damage. |
| R-XCT-04 | Billing mismatch | If billing/invoicing doesn’t match delivered scope, then disputes arise, leading to delayed revenue and relationship damage. |
10. Forms and Records
| Form/Record | Purpose | Location |
|---|---|---|
| Risk Register Template | Master risk tracking artifact | Template |
| Risk Escalation Log | Documents escalations and resolutions | Tab within Risk Register |
| Client Risk Summary | Filtered view for client governance | Generated from Register |
| Gate Checkpoint Risk Review | Snapshot for AI-IRB gate passage | Exported PDF per gate |
11. References
- SOP-1000-01-AI: Mind Matrix Governance Navigation Hub
- SOP-1006-01-AI: AI-IRB Engagement and Ethical Review Procedure
- SOP-1009-01-AI: AI Model Drift and Re-Validation Procedure
- SOP-1053-01-AI: Ethical Risk Assessment and Mitigation
- SOP-1061-01-AI: Incident Tracking
12. Revision History
| Version | Date | Changes | Approved By |
|---|---|---|---|
| 1.0 | (Date) | Initial release of SOP-1062-01-AI | Delivery Operations Lead |
13. Sequence Diagram
Short textual explanation: This sequence diagram illustrates the Risk Register Management process. It begins with initialization at engagement kickoff, where the Delivery Lead gathers risks from stakeholders, scores them, and flags any requiring AI-IRB review. Ongoing identification allows any team member to submit risks, with High priority items triggering immediate escalation. Weekly reviews track mitigation progress and re-score as conditions change. The escalation path routes client-dependent risks through the Account Manager to the Client Sponsor, and compliance risks through the AI-IRB Liaison. Gate checkpoint reviews ensure all flagged risks are resolved or accepted before passage. Finally, risk closure requires validation and, for High priority items, approval from Account Manager and AI-IRB Liaison.