Design your AI stack
AI Marketing Stack Framework
The AI Marketing Stack Framework describes an AI marketing stack as six layers: data, models, tools, workflows, measurement and governance, and shows which layers are missing or weak in your current set-up.
The model
- Governance
- Measurement
- Workflows
- Tools
- Models
- Data
Developed by Markaigen · Updated
What each part means
- Data
- Customer, content and performance data that is clean, documented and allowed to be used.
- Models
- The AI models you rely on, whether inside tools or through an API, and how you evaluate them.
- Tools
- The applications people work in, chosen per task with the evaluation framework.
- Workflows
- How tools, data and people connect into repeatable processes.
- Measurement
- How you know what works: baselines, experiments and reporting.
- Governance
- Policy, roles, disclosure and risk controls across the whole stack.
How to use it
- Build from the bottom: data and models before tools, workflows before measurement.
- Prefer fewer tools with good integrations over many tools with none.
- Review the stack yearly; models and tools change faster than your processes should.
Map your stack
Rate each layer. The result shows the layers to strengthen and the order to do it in.
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