AI in Data & Analytics

Below is the criteria for Global AI Awards in Data & Analytics Category:

1. Design (25%)

• Quality and robustness of the AI system’s architecture for handling data at scale.
• Integration with existing data ecosystems (cloud, databases, enterprise platforms).
• Transparency, explainability, and ethical design in analytics outputs.
• Scalability, interoperability, and security of the solution.

2. Impact (35%)

• Demonstrated improvements in decision-making, efficiency, or business performance.
• Measurable outcomes such as faster insights, improved forecasting accuracy, or cost reduction.
• Industry or domain transformation through data democratization and AI-driven intelligence.
• Broader societal or environmental contributions (responsible data use, sustainability).

3. Creativity (25%)

• Innovative applications of AI in data collection, cleaning, visualization, or predictive analytics.
• Unique methodologies for extracting insights from complex, unstructured, or real-time data.
• Pioneering integrations of AI with emerging fields (IoT, digital twins, edge computing).
• Differentiation from conventional BI (business intelligence) or analytics tools.

4. Ease of Use (15%)

• Accessibility for both technical and non-technical users (self-service analytics, intuitive dashboards).
• Low barriers to adoption with clear workflows and user-friendly interfaces.
• Support for collaboration across roles (data scientists, analysts, business leaders).
• Quality of documentation, training, and community support.