“As the saying goes: ‘Garbage in, garbage out,’” Lakhani says in AI Essentials for Business. “If your data isn't set up in a way that enables you to learn from across your enterprise or your customers, you're going to have garbage coming out of your AI factory.”
For example, Amazon uses a sophisticated data pipeline to manage and analyze vast amounts of customer data, including browsing histories and purchase behaviors. Through cleaning and organizing that data, its AI models can accurately predict customer preferences and personalize recommendations.
Establishing a strong data pipeline requires setting up systems and processes. Without a foundation of clean, well-organized data, the AI factory can’t effectively support decision-making and innovation.