Data Quality has a direct impact on which aspect of AI?

The quality of AI outputs is directly influenced by data quality because AI systems rely heavily on the data they are trained on. If the data used for training is inaccurate, incomplete, or biased, the outputs generated by the AI will reflect those flaws, leading to unreliable or misleading results. High-quality data ensures that the AI can learn patterns and relationships accurately, which in turn enhances its performance and the usefulness of its predictions.

While aspects such as data collection procedures, regulatory compliance, and data storage technologies are certainly relevant to the broader ecosystem surrounding AI, they do not directly influence the outputs produced by AI in the same way that data quality does. The direct correlation between data quality and AI outputs underscores the critical importance of ensuring that data is well-curated, consistent, and representative of the real-world scenarios the AI is meant to address.