Abstract :This case study examines the journey of UltraTech Cement, an industry leader in the cement manufacturing segment, as it integrates Artificial Intelligence (AI) and Machine Learning (ML) into its workplace safety protocols. Despite being an early adopter of advanced technologies for productivity, quality enhancements, and demand forecasting, the company faced a critical gap in leveraging these tools for safety. Occurrence of safety incidents in the past two years served as the catalyst for change, prompting the leadership to explore AI/ML solutions across pilot locations to proactively identify risks, improve incident response, and strengthen overall resilience.

Six months into the rollout, K.N.V. Kiran Kumar, Vice President and Head of Safety at UltraTech Cement, along with his team members, was faced with the decision of evaluating the effectiveness of these interventions, while deciding on the next steps before beginning large-scale deployment across all locations. The case explores the decision-making process of adopting AI/ML over traditional safety measures, and the challenges encountered in its implementation on a wider scale. By leveraging technology for revamping safety processes, could UltraTech be a trendsetter in the employee health and safety (EHS) segment.

Learning Objectives

• To understand the role of AI/ML interventions and predictive safety modeling in enhancing workplace safety and surveillance.
• To evaluate the challenges anticipated while attempting to transition to technology-enabled workplace safety.
• To design strategies and recommendation plan for mitigating challenges while dealing with the change management process.