How ready is your organization for AI transformation?

1.Our organization has a clear inventory of data assets relevant to AI use cases.

2.Data quality processes (validation, cleansing, deduplication) are consistently applied.

3.Data lineage and provenance are documented and traceable.

4.We have established data access policies that balance security with AI development needs.

5.We have a formal AI governance framework or policy in place.

6.Ethical guidelines for AI usage are documented and communicated.

7.Risk assessment processes exist for evaluating AI initiatives before deployment.

8.There is clear accountability for AI decisions and outcomes within the organization.

9.Executive leadership actively sponsors and champions AI initiatives.

10.Cross-functional teams collaborate effectively on AI projects.

11.There is a structured AI literacy or upskilling program for employees.

12.Change management processes are in place to support AI adoption.

13.AI initiatives are aligned with measurable business outcomes and KPIs.

14.We have a scored and prioritized backlog of AI use cases.

15.ROI hypotheses are defined before committing resources to AI projects.

16.There is a clear roadmap connecting AI investments to strategic objectives.

17.We have established MLOps or AI deployment pipelines for production workloads.

18.Cross-functional delivery teams (data, engineering, business) are in place for AI projects.

19.Pilot-to-production processes are documented with clear success criteria.

20.We can monitor, retrain, and iterate on AI models in production.