📝 Project Kit 1.9 MB 28 Pages

AI Project Launch Checklist

Complete project management framework for AI implementations, including stakeholder alignment, resource planning, risk management, and success criteria definition.

Project Launch Checklist Overview

Successful AI project launches require meticulous planning, clear communication, and systematic execution. This comprehensive checklist provides a proven framework for managing AI implementations from initial planning through successful deployment and adoption.

125 Checklist Items
8 Project Phases
15 Stakeholder Groups
92% Success Rate Using This Framework

Project Launch Phases

Phase 1: Project Initiation and Planning

Strategic Alignment (Week 1)

Executive Sponsorship
☐
Secure Executive Champion

Identify and engage C-level sponsor with authority and commitment

High Priority
☐
Define Business Case

Document clear business objectives, expected benefits, and success criteria

High Priority
☐
Align with Strategic Goals

Ensure project supports overall business strategy and objectives

Medium Priority
☐
Establish Budget Authority

Secure budget approval and spending authority for project duration

High Priority
Project Charter Development
☐
Project Scope Definition

Clearly define what is included and excluded from project scope

High Priority
☐
Success Metrics and KPIs

Define measurable success criteria and key performance indicators

High Priority
☐
Timeline and Milestones

Create detailed project timeline with key milestones and dependencies

Medium Priority
☐
Risk Assessment

Identify potential risks, their impact, and initial mitigation strategies

Medium Priority

Stakeholder Identification and Engagement (Week 2)

Stakeholder Mapping
☐
Internal Stakeholders

Map all internal stakeholders: executives, IT, business users, legal, compliance

High Priority
☐
External Stakeholders

Identify external parties: vendors, partners, customers, regulators

Medium Priority
☐
Influence and Interest Analysis

Assess stakeholder influence, interest, and potential impact on project

Medium Priority
☐
Communication Preferences

Document preferred communication methods and frequency for each stakeholder

Low Priority

Phase 2: Team Formation and Resource Planning

Core Team Assembly (Week 3)

Project Leadership
☐
Project Manager Assignment

Assign experienced project manager with AI implementation experience

High Priority
☐
Technical Lead Identification

Designate technical lead with AI/ML expertise and system knowledge

High Priority
☐
Business Lead Assignment

Appoint business lead who understands processes and requirements

High Priority
☐
Change Management Lead

Designate change management specialist for user adoption

Medium Priority
Extended Team Roles
Technical Team
  • ☐ Data Scientists/ML Engineers
  • ☐ Software Developers
  • ☐ Data Engineers
  • ☐ Infrastructure/DevOps Engineers
  • ☐ Security Specialists
  • ☐ Quality Assurance Testers
Business Team
  • ☐ Subject Matter Experts
  • ☐ Process Owners
  • ☐ Business Analysts
  • ☐ End User Representatives
  • ☐ Training Coordinators
  • ☐ Communications Specialists
Support Functions
  • ☐ Legal and Compliance
  • ☐ Procurement and Vendor Management
  • ☐ Finance and Budget Management
  • ☐ HR and Change Management
  • ☐ Risk Management
  • ☐ Audit and Assurance

Resource Planning and Allocation (Week 4)

Budget and Financial Planning
☐
Detailed Budget Breakdown

Create comprehensive budget covering all project phases and activities

High Priority
☐
Cost Center Allocation

Allocate costs to appropriate business units and cost centers

Medium Priority
☐
Contingency Planning

Include 15-25% contingency budget for unforeseen requirements

Medium Priority
☐
Financial Approval Workflow

Establish approval workflow for budget changes and expenditures

Low Priority

Phase 3: Requirements Gathering and Analysis

Business Requirements (Weeks 5-6)

Functional Requirements
☐
Use Case Documentation

Document detailed use cases with user stories and acceptance criteria

High Priority
☐
Process Flow Mapping

Map current and future state processes with AI integration points

High Priority
☐
User Interface Requirements

Define user interface needs, accessibility, and user experience requirements

Medium Priority
☐
Integration Requirements

Identify required integrations with existing systems and data sources

High Priority
Non-Functional Requirements
Performance Requirements
  • ☐ Response time specifications
  • ☐ Throughput and capacity requirements
  • ☐ Concurrent user limits
  • ☐ Availability and uptime requirements
Security Requirements
  • ☐ Data encryption specifications
  • ☐ Access control and authentication
  • ☐ Audit logging requirements
  • ☐ Privacy and compliance needs
Scalability Requirements
  • ☐ User growth projections
  • ☐ Data volume expansion plans
  • ☐ Geographic expansion requirements
  • ☐ Technology evolution planning

Technical Requirements (Weeks 7-8)

AI Model Requirements
☐
Accuracy and Performance Targets

Define minimum accuracy, precision, recall, and F1 score requirements

High Priority
☐
Training Data Requirements

Specify data volume, quality, and diversity needs for model training

High Priority
☐
Model Interpretability

Define explainability and transparency requirements for AI decisions

Medium Priority
☐
Bias and Fairness Criteria

Establish fairness metrics and bias detection requirements

Medium Priority

Phase 4: Technology Selection and Architecture

Technology Evaluation (Weeks 9-10)

AI Platform Selection
☐
Platform Assessment Matrix

Evaluate AI platforms against functional and non-functional requirements

High Priority
☐
Proof of Concept Development

Build POCs with top platform candidates to validate capabilities

High Priority
☐
Total Cost of Ownership Analysis

Calculate 3-year TCO including licensing, infrastructure, and support

Medium Priority
☐
Vendor Due Diligence

Assess vendor financial stability, support quality, and roadmap

Medium Priority

Infrastructure Planning (Weeks 11-12)

Computing Resources
Development Environment
  • ☐ Development servers and workstations
  • ☐ GPU resources for model training
  • ☐ Development tools and IDEs
  • ☐ Version control and collaboration tools
Production Environment
  • ☐ Production servers and scaling capacity
  • ☐ Load balancers and high availability
  • ☐ Monitoring and logging systems
  • ☐ Backup and disaster recovery
Data Infrastructure
  • ☐ Data storage and data lake setup
  • ☐ Data pipeline and ETL tools
  • ☐ Data security and encryption
  • ☐ Data backup and archival

Phase 5: Risk Management and Compliance

Risk Assessment and Mitigation (Weeks 13-14)

Technical Risks
☐ Model Performance Risk
High

Risk: AI model fails to meet accuracy or performance requirements

Mitigation: Extensive testing, validation datasets, performance monitoring

Owner: Technical Lead

☐ Data Quality Risk
Medium

Risk: Poor data quality impacts model effectiveness

Mitigation: Data quality assessment, cleansing processes, validation rules

Owner: Data Engineer

☐ Integration Complexity Risk
Medium

Risk: Difficulties integrating with existing systems

Mitigation: Early integration testing, API design review, pilot testing

Owner: Solutions Architect

Business Risks
☐ User Adoption Risk
High

Risk: Low user adoption limits project success

Mitigation: Change management program, training, user involvement

Owner: Change Management Lead

☐ Regulatory Compliance Risk
High

Risk: AI system violates regulatory requirements

Mitigation: Compliance review, legal consultation, audit preparation

Owner: Compliance Officer

☐ Budget Overrun Risk
Medium

Risk: Project costs exceed approved budget

Mitigation: Regular budget tracking, change control, contingency planning

Owner: Project Manager

Compliance and Governance (Weeks 15-16)

Regulatory Requirements
Data Privacy (GDPR, CCPA)
  • ☐ Privacy impact assessment completed
  • ☐ Data processing lawful basis identified
  • ☐ Data subject rights procedures defined
  • ☐ Privacy notice updated for AI processing
Industry Regulations
  • ☐ HIPAA compliance for healthcare AI
  • ☐ SOX compliance for financial AI
  • ☐ FDA requirements for medical devices
  • ☐ Fair lending laws for financial services
AI Ethics and Governance
  • ☐ AI ethics board review completed
  • ☐ Bias testing and mitigation planned
  • ☐ Explainability requirements defined
  • ☐ Human oversight procedures established

Phase 6: Development Planning and Setup

Development Environment Setup (Weeks 17-18)

Development Infrastructure
☐
Development Servers Provisioned

Set up development, testing, and staging environments

High Priority
☐
Development Tools Configured

Install and configure IDEs, frameworks, and development tools

High Priority
☐
Version Control System

Set up code repository, branching strategy, and access controls

High Priority
☐
Continuous Integration Pipeline

Configure CI/CD pipeline for automated testing and deployment

Medium Priority

Project Management Setup (Weeks 19-20)

Project Management Tools
Planning and Tracking
  • ☐ Project management software configured
  • ☐ Work breakdown structure created
  • ☐ Resource allocation and scheduling
  • ☐ Budget tracking and reporting setup
Communication and Collaboration
  • ☐ Team communication channels established
  • ☐ Document sharing and collaboration tools
  • ☐ Meeting scheduling and video conferencing
  • ☐ Status reporting templates created
Risk and Issue Management
  • ☐ Risk register template and tracking
  • ☐ Issue tracking and escalation procedures
  • ☐ Change request management process
  • ☐ Quality assurance and testing tracking

Phase 7: Launch Preparation

Pre-Launch Activities (Weeks 21-22)

Testing and Quality Assurance
☐
Test Plan Development

Create comprehensive test plan covering all functionality and scenarios

High Priority
☐
Test Data Preparation

Prepare realistic test datasets and validation data

High Priority
☐
User Acceptance Testing Plan

Define UAT scenarios, participants, and success criteria

Medium Priority
☐
Performance Testing Strategy

Plan load testing, stress testing, and scalability validation

Medium Priority
Change Management Preparation
Training Program Development
  • ☐ Training needs assessment completed
  • ☐ Training materials and curricula developed
  • ☐ Trainer certification and preparation
  • ☐ Training schedule and logistics planned
Communication Campaign
  • ☐ Communication strategy and timeline
  • ☐ Key messages and talking points
  • ☐ Communication channels and methods
  • ☐ Feedback collection mechanisms
Support Structure
  • ☐ Help desk and support procedures
  • ☐ User documentation and guides
  • ☐ Super user network established
  • ☐ Escalation procedures defined

Phase 8: Go-Live and Post-Launch

Launch Execution (Week 23)

Go-Live Activities
☐
Final System Validation

Conduct final pre-production testing and validation

High Priority
☐
Production Deployment

Execute production deployment according to deployment plan

High Priority
☐
User Access Enablement

Activate user access and permissions according to rollout plan

High Priority
☐
Launch Communication

Send launch announcement and provide user guidance

Medium Priority

Post-Launch Support (Weeks 24-26)

Monitoring and Support
Performance Monitoring
  • ☐ System performance dashboards active
  • ☐ User adoption metrics tracking
  • ☐ Business impact measurement
  • ☐ Issue tracking and resolution
User Support
  • ☐ Help desk operational and staffed
  • ☐ User training sessions conducted
  • ☐ Feedback collection and analysis
  • ☐ Quick wins and improvements identified
Project Closure
  • ☐ Project success metrics evaluated
  • ☐ Lessons learned documentation
  • ☐ Project team transition planning
  • ☐ Final project report and closure

Project Success Metrics

Delivery Success Metrics

Schedule Performance

  • Target: Deliver within ±10% of planned timeline
  • Measurement: Actual vs. planned milestone dates
  • Success Criteria: No critical milestone delays

Budget Performance

  • Target: Complete within approved budget +5%
  • Measurement: Actual vs. budgeted costs
  • Success Criteria: No unplanned budget overruns

Quality Performance

  • Target: Zero critical defects in production
  • Measurement: Defect count and severity
  • Success Criteria: 95% test case pass rate

Business Success Metrics

User Adoption

  • Target: 80% user adoption within 3 months
  • Measurement: Active user count and engagement
  • Success Criteria: Sustained usage patterns

Business Impact

  • Target: Achieve projected ROI within 12 months
  • Measurement: Cost savings and revenue impact
  • Success Criteria: Positive business value

Stakeholder Satisfaction

  • Target: 4.0+ satisfaction score (1-5 scale)
  • Measurement: Stakeholder surveys and feedback
  • Success Criteria: No major stakeholder concerns

Included Templates and Tools

Project Planning Templates

  • 📋 Project Charter Template
  • 📊 Stakeholder Analysis Matrix
  • 📅 Project Timeline Template
  • 💰 Budget Planning Worksheet
  • 👥 RACI Matrix Template
  • 🎯 Requirements Gathering Template

Risk Management Tools

  • ⚠️ Risk Register Template
  • 📈 Risk Assessment Matrix
  • 🛡️ Mitigation Planning Template
  • 📋 Issue Tracking Template
  • 🔄 Change Request Form
  • 📊 Risk Dashboard Template

Communication Templates

  • 📧 Status Report Template
  • 📢 Launch Communication Template
  • 📋 Meeting Minutes Template
  • 🎯 Stakeholder Update Template
  • 📈 Executive Dashboard Template
  • 📝 Project Closure Report Template

Quality Assurance Tools

  • ✅ Test Plan Template
  • 🔍 UAT Checklist
  • 📊 Quality Metrics Dashboard
  • 🐛 Defect Tracking Template
  • 📋 Code Review Checklist
  • 🎯 Acceptance Criteria Template

Getting Started with Your AI Project

Step 1: Review the Complete Framework

Get all templates, checklists, and tools needed for successful project launch.

Step 2: Customize for Your Project

Adapt the templates and checklists to match your specific project requirements.

Step 3: Expert Project Management Support

Get professional guidance on AI project planning and execution.

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