Recent advances in AI and increased accessibility to machine learning models that power them have got many organizations excited about how they can be applied to create more value. In fact, in a recent survey by Dataiku and Databricks, 64% of respondents said that they were “likely” or “very likely” to use generative AI for their business over the next year,2 while a report from Segment found that 92% companies are using AI-driven personalization to drive business growth.3

However, AI is only as good as the data behind it. No amount of tuning a model will help if the data is of poor quality, which is why the same survey from Dataiku and Databricks identified lack of quality data as the primary obstacle to generating value. An inferior model with superior data will always outperform a superior model with inferior data.

There are other data issues that can affect...