In a new book titled "Designing the AI-Driven Data Foundations: Architecture, Principles, and Practice," veteran analyst Sanjeev Mohan, who headed Gartner's data and analytics research team before founding SanjMo in 2021, argues that there is no AI without a strong data foundation. According to the article, if agents and other AI tools can't access governed, high-quality data, they'll deliver inaccurate, untrustworthy results and AI projects will never make it past the pilot stage and into production. Mohan states that AI is fundamentally just the most modern use case for data, noting that data was long kept under wraps by specialists and largely used to inform business intelligence tools such as reports and dashboards, but the paradigm has evolved so that data is now earmarked to underpin agents and other AI tools and is becoming the infrastructure for widespread AI-driven analysis and process automation. In the coming years, he says, data will be the foundation for technologies such as robotics and quantum computing. In a recent interview with TechTarget, Mohan discussed what makes a good data foundation, how AI can play a role in preparing data for AI as well as benefitting from it, data governance's role in the evolving AI workflow, the barriers that still prevent some enterprises from building a strong data foundation, and how data for AI will continue to evolve. He said data doesn't have to be pristine for AI, but organizations at least have to know what they have, and that data estates