Data Science and AI Assisted Automotive Product Development Dr. Shankar Venugopal Vice President - Technology Innovation Dean Mahindra Technical Academy Mahindra & Mahindra Dr. Srinivas Gunti Deputy General Manager Mahindra & Mahindra About the Topic: Automotive Product Development process is very complex and involves decision making at various stages of the Product Development gateways. The decisions involve making a trade-off between various performance attributes that are often conflicting in nature. A typical vehicle development project involves meeting various performance (Acceleration, Fuel Economy, crash, durability, aesthetics, etc..) and regulatory requirements while meeting the stringent targets of Quality, Cost and Deliverables. Though, verification and validation processes are in place at various stages of the product design (from Conceptualization to Delivery), quite often the decision to clear the gateway is taken based on subjective and qualitative methods using limited data and this increases the number of design iterations. The multiple iterations lead to delay in project timelines and the risk of losing significant market share. We need technologies that will enable fast, accurate and inclusive decision making. Data Science (DS) and AI are disrupting the traditional product development methodologies and processes due to their efficacy and improved accuracy in decision making. There is a strong need to integrate the DS and AI based methods into our product development workflows to make the decision-making process more objective and precise. The present talk discusses various Use Cases in which DS and AI based technologies can be applied for precise and quick decision making at different stages of the Automotive Product Development.