A recent EY India report, “How much productivity can Generative AI (GenAI) unlock in India? The AIdea of India: 2025,” predicts a major shift in the Indian automotive sector, with GenAI expected to drive a 30-32% productivity boost by 2030. The report underscores GenAI’s transformative potential across key areas such as product development, customer engagement, autonomous driving, and sustainability initiatives, paving the way for enhanced operational efficiency and industry growth.
The automotive sector, which contributes 7.1% to India’s national GDP and employs over 19 million people, is leveraging advanced technologies such as autonomous driving, real-time analytics, and AI-driven optimization. As per the EY report, the integration of GenAI is expected to drive innovation and improve efficiency across the entire value chain, from manufacturing to customer experiences.
Key highlights from the report reveal that GenAI is projected to increase productivity in the Indian auto sector by 30% to 32% by 2030, with significant gains in areas like product development, process optimization, and customer engagement. In terms of investment, 33% of respondents report that their organizations are actively investing in GenAI, with budgets either allocated or in the process of being invested. Additionally, 57% of respondents have initiated Proof of Concept (POC) initiatives, with 14% already moving these POCs into production. Furthermore, AI is showing a substantial impact on customer satisfaction, with its ability to revolutionize customer engagement through personalized and real-time interactions.
Vinay Raghunath, Partner and Automotive Sector Leader at EY-Parthenon, commented: “GenAI offers a tremendous opportunity for innovation across the entire automotive value chain and can help unlock new potential across manufacturing processes, customer interactions and aspects related to vehicle autonomy, safety and personalisation. Integrating real-time data processing with autonomous features can reshape personal and public transportation systems. Incorporating GenAI capabilities can help streamline production processes, leading to increased efficiency, reduced waste, and improved product quality. Predictive models can help enhance vehicle reliability and lower repair frequency and associated costs. The industry can leverage GenAI to reshape the future of mobility but will also need to address challenges related to investment, data security concerns, regulatory compliance and workforce training”
Impact across the automobility value chain
According to the EY report, GenAI is expected to deliver significant productivity improvements across various functions within the automotive sector. With an expected productivity increase of 37% to 39%, AI-powered solutions are set to revolutionize customer interactions, improving customer satisfaction and engagement.
Production and assembly: GenAI is projected to enhance productivity in production and assembly by 35% to 37%, streamlining processes and reducing operational costs. Automation and predictive maintenance powered by GenAI could lead to a productivity boost of 34% to 36%, helping manufacturers achieve cost efficiency and extend the lifespan of their assets.
Other key functions such as quality assurance, control, and marketing are also expected to experience notable productivity improvements as AI-driven innovations reshape the automotive value chain.
Way forward for the adoption GenAI adoption in automotive industry
The EY report underscores the fact that GenAI is poised to revolutionize the automotive industry by enhancing vehicle autonomy, safety, and personalization. Its advanced cognitive functions enable real-time data processing and analysis, allowing vehicles to make informed driving decisions, which significantly reduces accident risks. This advancement also paves the way for the creation of fully autonomous vehicles, potentially reshaping both personal and public transportation systems. In manufacturing, GenAI can optimize and streamline production processes, leading to increased efficiency, reduced waste, and improved product quality. AI-enabled predictive maintenance can detect potential issues before they arise, enhancing vehicle reliability and lowering both repair frequency and associated costs. Nevertheless, the transition to GenAI in the automotive sector presents a transformative outlook for the future, characterized by smarter, safer, and more efficient vehicles. Achieving this vision, however, necessitates addressing considerable challenges, such as investment expenses, data security concerns, regulatory compliance, and workforce training.
