AI data readiness check
Check the data behind one workflow across five areas, and get the three steps that would make it ready for AI.
0/10answered
How the scoring works
- This check covers the data behind one workflow. For your organization as a whole, use the AI readiness self-assessment.
- Each answer scores from 0 to 3. An area score is its two answers as a share of the maximum, and the overall score weights every question equally.
- 70% and above suggests the data can support a first build; below 40% suggests fixing the data first.
- The next steps come from your three weakest answers. When answers tie, ownership and access come first, because either one can stop a project.
- The scores are planning estimates from your own answers, not an audit of the data itself.
What to do next
Carry this into the next step, the full guide or the service behind it.
AI cloud readiness checkEight questions on running an AI workload on AWS or Azure. See your readiness by area and what to set up first.Open the tool Connecting AI to your ERP, CRM and data warehouseConnect AI to your ERP, CRM and data warehouse through the vendor's supported APIs, webhooks, event streams or an integration platform, not by writing straight to the database. Start with read access, send every write through a named approver until the workflow has proven itself, and check API limits, licenses, permissions and data quality before you commit to a design.Read AI & Cloud InfrastructureThe cloud, data and model foundations an AI workload needs to run in production.See the service
See how an idea becomes a working solution.
Explore how we scope, build and hand over AI projects, with clear decisions at each stage.