Amid the ongoing fifth industrial revolution, manufacturing organizations are urged to adopt AI solutions rapidly to maintain a competitive edge, which involves the integration of unstructured data into centralized data lakes to dismantle data silos and enhance operational efficiency. Data lakes, serving as robust storage systems, allow companies to harness structured and unstructured data from diverse sources like IoT devices, production machines, and document repositories, promoting data democratization and enabling enterprise-wide analytics. The process requires a strategic approach, encompassing clear objectives, data governance, scalable architecture, metadata management, security, and optimized data storage and processing. Labelbox offers a comprehensive platform to streamline data structuring and model development, facilitating the transition from raw data to trained models for various manufacturing applications, including predictive maintenance and quality control. The effective adoption of these technologies promises substantial financial benefits and positions organizations to thrive in an era of advanced industrial automation.