Building Blocks of Success: How Data Foundation Shapes the AI Journey
As organizations seek to integrate artificial intelligence (AI) into their processes, they must start by ensuring that the underlying data is robust and reliable. This principle was highlighted by global CTO at Xebia, Niels Zeilemaker, in a recent interview. According to Zeilemaker, "if you don't think about that, you can create AI agents that fail because of poor data quality."
In essence, Agentic AI scales on the strength of its data foundation. This means that if an organization lacks sufficient and accurate data, it will struggle to develop effective AI models. The consequences can be significant, as AI decisions often rely on the accuracy and relevance of the underlying data. As a result, organizations must prioritize data quality and availability in their AI initiatives.
By acknowledging the importance of data foundation, companies can begin to build more successful AI journeys. By making their data available for AI consumption, they can create more effective decision-making processes and drive business growth. For instance, by leveraging unstructured data such as documents and images, organizations can gain valuable insights that might otherwise go unnoticed. With a solid data foundation in place, companies are well on their way to harnessing the power of AI to achieve their goals.