Understanding how to use data and AI-vision processing to identify and mitigate safety risks, improve engineering processes, and prevent workplace injuries is crucial learning in today’s world to be at the forefront of the industry and competition. Furthermore, deploying injury prevention technology in an organization involves a comprehensive and strategic approach that encompasses multiple stages and requires careful planning. In this case study, we will discuss how United Farmers of Alberta (UFA) planned, deployed and utilized the proficiency of data combined with AI-vision processing to support engineering changes and injury prevention. UFA had identified safety as a top priority and had a goal of reducing workplace injuries and improving safety measures. To achieve this, they carefully arranged a deployment plan, used data from wearables to identify and narrow down specific risks, display angles and frequencies of movements, and find patterns of trends faced by workers, prompting where the need was for further investigation. AI-vision processing technology was then used to dive deeper into the risk and reveal in real-time the root cause of the task issue. By utilizing these technologies, UFA was able to reduce workplace injuries and create a safer working environment.