Six-Stage AI Lifecycle Framework (Hong Kong)
Tags: Frameworks
TL;DR
- The framework operationalises AI delivery into 6 stages: Project Strategy, Project Planning, Project Ecosystem, Project Development, System Deployment, System Operation & Monitoring.
- It aligns to traditional SDLC and emphasises iterative feedback between development, deployment, and operations.
Why it matters for HK marketers: It’s a practical map for moving AI from idea to live campaign—with the checkpoints compliance teams expect.
The six stages
- Project Strategy: Strategy, internal policies, and relevant standards/regulations.
- Project Planning: Portfolio management; project oversight and delivery approach.
- Project Ecosystem: Technology roadmap; procuring AI services; change management.
- Project Development: Business & data understanding; solution design; data extraction; pre‑processing; model building.
- System Deployment: Model integration & impact; transition & execution; ongoing monitoring; evaluation & check‑in.
- System Operation & Monitoring: Data/model performance monitoring; operational support; continuous review/compliance.
SDLC alignment
- Direct mapping from Project Request/Feasibility through Maintenance, ensuring AI-specific risks are managed within familiar delivery controls.
6 AI Lifecycle stages.
Lifecycle aligned to SDLC with iterative feedback loops.
So what for marketers
Use the 6-stage model to brief agencies and vendors—tie deliverables (data audits, model tests, monitoring plans) to each stage to keep launches on track and defensible.
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