You are an expert AI Governance and Sustainability Strategist specializing in Canadian public sector digital transformation. Create a comprehensive AI Service Sustainability Plan for [SERVICE_NAME] operated by [DEPARTMENT_AGENCY].

CONTEXT:
- AI Technology Type: [AI_TECHNOLOGY_TYPE]
- Implementation Scale: [SCALE_SCOPE]
- Planning Timeframe: [TIMEFRAME]
- Primary Stakeholders: [STAKEHOLDERS]

Your plan must address the following dimensions with specific attention to Canadian regulatory and operational contexts:

1. EXECUTIVE SUMMARY
   - Service overview and AI integration scope
   - Sustainability vision aligned with Canada's Digital Ambition and Greening Government Strategy
   - Key risk factors and mitigation priorities

2. REGULATORY & ETHICAL COMPLIANCE FRAMEWORK
   - Compliance with Directive on Automated Decision-Making (DADM) including Algorithmic Impact Assessment (AIA) maintenance
   - PIPEDA privacy considerations and provincial privacy law alignment
   - Accessibility Compliance (ACA) standards for AI-driven interfaces
   - Equity, diversity, inclusion (EDI) considerations and bias monitoring protocols

3. ENVIRONMENTAL SUSTAINABILITY
   - Carbon footprint baseline and ongoing assessment of AI compute requirements
   - Green computing strategies (cloud region selection with renewable energy, model optimization, edge computing)
   - Energy consumption monitoring dashboards and reduction targets aligned with Greening Government Strategy
   - Hardware lifecycle management and e-waste mitigation for on-premise infrastructure

4. OPERATIONAL RESILIENCE
   - Technical debt management and model versioning strategies
   - Data governance, quality assurance, and drift detection protocols
   - Business continuity/disaster recovery specific to AI model dependencies
   - Vendor lock-in mitigation and interoperability with GC standards (API Gateway, etc.)

5. FINANCIAL SUSTAINABILITY
   - Total Cost of Ownership (TCO) model including compute, licensing, talent, and ongoing training data costs
   - Funding model transitioning from innovation funds to operational budget
   - Resource optimization strategies (right-sizing infrastructure, batch processing optimization)

6. TALENT & KNOWLEDGE MANAGEMENT
   - AI literacy development for civil servants and technical upskilling pathways
   - Knowledge retention strategies for critical AI systems
   - Change management and user adoption frameworks
   - Succession planning for specialized AI technical roles

7. RISK MANAGEMENT MATRIX
   - Technical risks (model drift, data poisoning, concept drift)
   - Operational risks (staff turnover, vendor instability, compute cost volatility)
   - Reputational risks (public trust, media scrutiny, algorithmic bias incidents)
   - Indigenous data sovereignty considerations where applicable
   - Mitigation strategies, contingency plans, and escalation protocols

8. IMPLEMENTATION ROADMAP
   - Quarterly milestones for sustainability initiatives over the specified timeframe
   - Success metrics and KPIs (include sustainability-specific, ethical, and operational metrics)
   - Review schedules, audit cycles, and AIA re-assessment triggers
   - Stakeholder communication plan including public transparency initiatives

9. GOVERNANCE STRUCTURE
   - AI Ethics Advisory Board composition and mandate
   - Interdepartmental collaboration frameworks for shared services
   - Decision-making authority matrices (who can approve model updates?)
   - Integration with existing departmental governance (CIO, CFO, ATIP)

FORMAT REQUIREMENTS:
- Professional government report structure with executive summary
- Risk matrix presented as table with Probability/Impact ratings and mitigation owners
- Roadmap presented as quarterly milestone chart
- Use Canadian spelling conventions (e.g., behaviour, centre, analyse)
- Include specific references to Treasury Board policies, Canadian Digital Service standards, and relevant TBS directives
- Length: Comprehensive (15-25 pages equivalent) with appendices for technical specifications