AI Maturity Assessment
Evaluate your product team's AI readiness across 5 key dimensions. Rate each statement to get a personalized maturity score, radar visualization, and targeted recommendations.
Progress
0/15 questions answeredAI Strategy Alignment
Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree)
We have clearly defined AI use cases for our product.
AI initiatives are explicitly included in our product roadmap.
We have executive buy-in and budget allocated for AI initiatives.
Data Readiness
Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree)
Our data quality and governance practices are well-established.
We have access to sufficient, labeled training data for our AI use cases.
Our data pipelines are mature and can support ML model training and inference.
Team Capabilities
Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree)
We have ML engineers on the team or readily accessible.
Our product managers understand core AI/ML concepts and limitations.
Cross-functional team members (design, engineering, QA) have baseline AI literacy.
Process Maturity
Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree)
We have processes for evaluating and monitoring ML model performance.
We follow responsible AI guidelines (bias detection, fairness, transparency).
We have AI-specific QA and testing practices (e.g., adversarial testing, drift detection).
Customer Impact
Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree)
We track adoption and engagement metrics for AI-powered features.
We have structured feedback loops to capture user reactions to AI features.
We measure the ROI of AI investments with clear success criteria.