Summary: The article discusses the current state of AI adoption in businesses and the challenges they face, including data complexity and difficulty in integration. It highlights the need for effective data management and the scarcity of data scientists and ML engineers. The concept of ML democratization is introduced as a solution to these challenges, enabling non-technical analysts to become effective ML practitioners. Capital One’s journey towards ML democratization is presented as an example, emphasizing a problem-first approach and the importance of making ML accessible to a broader audience through user-friendly interfaces and no-code solutions.