Refine data models
How refine data models are reshaped as AGI capability advances.
The bottom line
Roughly 85% of the work in Refine data models is information-shaped — already within reach of AI delivery. The question here is not whether it shifts, but which tasks go first and who staffs the residual.
Why: With no seeded child occupations, this score relies on the specific process name ('Refine data models') and description ('Make required changes to data model'). While the lens category is EHS (which can be hybrid), refining data models and conducting stakeholder reviews are purely knowledge-based information transformation tasks performed entirely at a desk or via computer software, placing this firmly in the digital band.
grounded in the economy graph · digital scalar 0.85 · digital
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How the work flows
Trigger: Stakeholders provide feedback or change requests after reviewing an initial or existing data model.
- Compile stakeholder feedback and change requests
- Analyze the impact of requested changes on existing architecture
- Modify data structures, relationships, and attributes
- Validate the refined model against business rules and data integrity standards
- Present the updated data model to stakeholders for final approval
- Version and document the finalized data model
Outcome: The data model is updated, validated against business requirements, and formally approved for implementation.