100+ AI Product Management SOPs (Excel XLSX)

BENEFITS OF THIS EXCEL DOCUMENT

1. Provides a complete, end-to-end framework for building, launching, scaling, and governing AI products across their entire lifecycle.
2. Delivers a standardized operating system for AI Product Management, enabling faster execution, clearer ownership, and measurable business impact.
3. Equips teams with enterprise-grade AI SOPs to reduce risk, ensure compliance, and turn AI initiatives into repeatable, scalable revenue engines.

ARTIFICIAL INTELLIGENCE EXCEL DESCRIPTION

This product (100+ AI Product Management SOPs) is an Excel template (XLSX), which you can download immediately upon purchase.

Curated by McKinsey-trained Executives


🚀 150+ AI Product Management SOPs Library

The Ultimate AI Product Operating System (Excel Template)

Build. Launch. Scale. Govern. Monetize AI products – without chaos.

This is not a "nice-to-have" checklist.
This is a battle-tested, end-to-end AI Product Management SOP Library built for AI Product Managers, Heads of Product, CTOs, Founders, AI Leaders, and Enterprise Teams who want speed, control, compliance, and ROI.

👉 150+ AI Product Management Standard Operating Procedures
👉 Structured Excel Template (ready-to-use, customizable, scalable)
👉 Covers strategy → data → models → UX → engineering → ethics → legal → GTM → ops → lifecycle

If you're building AI products without this, you're improvising.
And improvisation doesn't scale.


💥 Why This AI SOP Library Dominates the Market
•  100% AI-native (not generic PM fluff repurposed for AI)
•  Designed for real-world AI complexity: data, models, drift, bias, regulation
•  Enterprise-grade governance + startup-level speed
•  Instant operational maturity without hiring consultants
•  Excel-based → works everywhere, integrates with any workflow

This is your single source of truth for running AI products like a serious organization.


📦 What You Get (For Every Single SOP)

Each of the 150+ SOPs is fully structured and standardized with the following sections:
Every SOP Includes:
•  Purpose
•  Scope
•  Owner / Role
•  Inputs (Required Information & Documents)
•  Process Steps (Detailed Workflow)
•  Outputs / Deliverables
•  KPIs / Success Metrics
•  Risks / Controls
•  Review Frequency

No ambiguity. No interpretation wars. No "who owns this?" meetings.


🧠 COMPLETE SOP COVERAGE – ALL 15 CLUSTERS
Cluster 1: AI Product Vision & Strategy
1. Define AI Product Vision SOP
2. Align AI Strategy with Business Goals SOP
3. AI Opportunity Identification SOP
4. AI Use Case Prioritization SOP
5. AI Product Portfolio Management SOP
6. Competitive AI Landscape Analysis SOP
7. AI Differentiation Strategy SOP
8. Long-Term AI Roadmap Planning SOP
9. AI Value Proposition Definition SOP
10. AI Product Success Criteria SOP

Cluster 2: Market, User & Problem Discovery
11. AI User Research Planning SOP
12. Problem Framing for AI Solutions SOP
13. AI Jobs-to-be-Done Analysis SOP
14. AI Persona Development SOP
15. AI User Journey Mapping SOP
16. Market Validation for AI Products SOP
17. AI Problem-Solution Fit Assessment SOP
18. AI Customer Feedback Collection SOP
19. AI Assumption Mapping SOP
20. AI Discovery Sprint Execution SOP

Cluster 3: Requirements & Product Definition
21. AI Product Requirements Document SOP
22. Functional vs Non-Functional AI Requirements SOP
23. AI MVP Definition SOP
24. AI Feature Prioritization SOP
25. AI User Story Writing SOP
26. AI Acceptance Criteria Definition SOP
27. AI Edge Case Identification SOP
28. AI Constraints Documentation SOP
29. AI Dependency Mapping SOP
30. AI Scope Change Management SOP

Cluster 4: Data Strategy & Management
31. AI Data Requirements Definition SOP
32. Data Sourcing Strategy SOP
33. Data Collection SOP
34. Data Labeling & Annotation SOP
35. Data Quality Assessment SOP
36. Data Governance for AI SOP
37. Training vs Inference Data Management SOP
38. Data Versioning SOP
39. Bias Detection in Data SOP
40. Data Retention & Deletion SOP

Cluster 5: Model Development & Evaluation
41. Model Selection Criteria SOP
42. Build vs Buy Model Decision SOP
43. Model Training Coordination SOP
44. Model Evaluation Metrics Definition SOP
45. Offline Model Testing SOP
46. Model Benchmarking SOP
47. Model Interpretability Review SOP
48. Model Performance Sign-Off SOP
49. Model Iteration Planning SOP
50. Model Documentation SOP

Cluster 6: AI UX & Human-AI Interaction
51. AI Interaction Design SOP
52. Explainability UX Design SOP
53. Human-in-the-Loop Design SOP
54. Confidence & Uncertainty Communication SOP
55. AI Error Handling UX SOP
56. Prompt Design Management SOP
57. Conversational AI Flow Design SOP
58. AI Feedback Loop UX SOP
59. Accessibility for AI Products SOP
60. AI UX Validation Testing SOP

Cluster 7: Engineering & Integration
61. AI Architecture Alignment SOP
62. API Integration for AI Models SOP
63. Model Deployment Readiness SOP
64. Scalability Planning for AI SOP
65. Latency & Performance Requirements SOP
66. Infrastructure Cost Management SOP
67. MLOps Collaboration SOP
68. Feature Flagging for AI SOP
69. Dependency Risk Management SOP
70. Release Readiness Review SOP

Cluster 8: Experimentation & Validation
71. AI Experiment Design SOP
72. A/B Testing for AI Features SOP
73. Online Model Evaluation SOP
74. Experiment Success Metrics SOP
75. Shadow Mode Deployment SOP
76. Pilot Program Execution SOP
77. Experiment Results Analysis SOP
78. Learnings Documentation SOP
79. Go / No-Go Decision SOP
80. Experiment Rollback SOP

Cluster 9: Responsible AI & Ethics
81. Responsible AI Principles Definition SOP
82. AI Bias Risk Assessment SOP
83. Fairness Evaluation SOP
84. Transparency & Disclosure SOP
85. Human Oversight Definition SOP
86. Ethical Review Process SOP
87. Harmful Output Mitigation SOP
88. Responsible Prompt Management SOP
89. AI Incident Response SOP
90. Ethics Sign-Off SOP

Cluster 10: Legal, Privacy & Compliance
91. AI Regulatory Landscape Monitoring SOP
92. Privacy-by-Design for AI SOP
93. Consent Management SOP
94. PII Handling in AI Systems SOP
95. Model IP Ownership SOP
96. Third-Party Model Compliance SOP
97. Audit Readiness for AI SOP
98. AI Risk Register Management SOP
99. Legal Review Coordination SOP
100. Compliance Sign-Off SOP

Cluster 11: Go-To-Market & Launch
101. AI Product Positioning SOP
102. AI Messaging & Narrative SOP
103. Pricing for AI Features SOP
104. Packaging & Tiering SOP
105. Launch Readiness Checklist SOP
106. Internal Enablement SOP
107. Sales & Support Training SOP
108. Public AI Disclosure SOP
109. Launch Monitoring SOP
110. Post-Launch Review SOP

Cluster 12: Adoption & Change Management
111. AI Adoption Strategy SOP
112. User Education & Onboarding SOP
113. Trust-Building Communication SOP
114. Change Management Planning SOP
115. Stakeholder Enablement SOP
116. Resistance Handling SOP
117. Adoption Metrics Tracking SOP
118. Internal AI Advocacy SOP
119. Feedback-Driven Adoption Iteration SOP
120. Adoption Risk Mitigation SOP

Cluster 13: Monitoring & Operations
121. Model Performance Monitoring SOP
122. Data Drift Detection SOP
123. Model Degradation Response SOP
124. AI Logging & Observability SOP
125. Cost Monitoring SOP
126. SLA Management SOP
127. Incident Management SOP
128. Customer Issue Escalation SOP
129. Retraining Triggers SOP
130. Operational Review Cadence SOP

Cluster 14: Metrics, Analytics & Outcomes
131. AI North Star Metric Definition SOP
132. Business Impact Measurement SOP
133. Model vs Product KPI Alignment SOP
134. Usage Analytics SOP
135. Quality vs Cost Tradeoff Analysis SOP
136. ROI Tracking SOP
137. Leading vs Lagging Indicators SOP
138. Executive Reporting SOP
139. Insight-to-Action SOP
140. Metrics Review & Adjustment SOP

Cluster 15: Lifecycle, Scaling & Sunset
141. AI Roadmap Reprioritization SOP
142. Feature Scaling Decision SOP
143. Market Expansion for AI SOP
144. Model Upgrade Planning SOP
145. Technical Debt Management SOP
146. Product Lifecycle Review SOP
147. End-of-Life Criteria SOP
148. AI Feature Deprecation SOP
149. Customer Migration SOP
150. Post-Sunset Retrospective SOP


🏆 Who This Is Built For
•  AI Product Managers
•  Senior Product Leaders
•  SaaS Founders & CTOs
•  Enterprise AI Teams
•  MLOps & Data Leaders
•  Regulated Industry AI Teams (FinTech, HealthTech, GovTech, InsurTech)


⚡ Bottom Line

This is not documentation.
This is operational power.

If you want:
•  Faster AI launches
•  Fewer production failures
•  Stronger compliance posture
•  Clear ownership
•  Measurable AI ROI

Then this 150+ AI Product Management SOP Library becomes your unfair advantage.
👉 Plug it in. Customize it. Run AI like a grown-up organization.




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Source: Best Practices in Artificial Intelligence, Product Management Excel: 100+ AI Product Management SOPs Excel (XLSX) Spreadsheet, SB Consulting