AI assessment maturity – Data stories

Welcome to AI assessment maturity!
This interactive quiz helps organizations evaluate their AI maturity across four key levels: Infancy, Developing, Growth, and Optimized.

The questions are across five critical areas:

Strategy and Governance: Examines the presence of AI strategies, integration into business goals, and oversight structures.
Data Management: Assesses how data is collected, stored, governed, and ensured for quality.
Technology and Tools: Evaluates the scalability, complexity handling, and integration of AI technologies.
Skills and Expertise: Looks at organizational AI skills, training initiatives, and knowledge-sharing practices.
Process and Operations: Focuses on standardization, monitoring, and continuous improvement of AI workflows.

Select the answers which are describing well your company on that area. The quiz calculates a score and categorizes the organization into one of the four maturity levels, providing insights and recommendations for progress.

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Strategy and Governance

Is there a clear AI strategy in place that is aligned with business objectives?

Are there governance structures to oversee AI projects?

Is AI considered a part of the overall business strategy?

Is AI integrated into the broader business strategy and decision-making?

Data Management

Is data collected, stored, and managed to ensure accessibility and security?

Is there a robust data governance framework that addresses compliance and privacy?

Are there processes for ensuring data quality and integrity across systems?

Is the organization leveraging data for AI model training or models fine tuning?

Technology and Tools

Are AI technologies and tools in use selected based on organizational needs?

Are AI tools effectively integrated with existing systems and workflows?

Is there a roadmap for adopting emerging AI technologies?

Skills and Expertise

Does the organization have sufficient in-house AI expertise?

Are there training and development programs in place for employees?

Is knowledge sharing and cross-functional collaboration actively facilitated?

Does the organization leverage external expertise or partnerships for AI initiatives

Process and Operations

Are AI processes standardized and repeatable?

Are metrics and KPIs used to monitor and evaluate AI project success?

Is feedback regularly gathered to improve AI practices?

Are risks, failures, and biases in AI processes identified and mitigated?

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