Use of Generative AI for Automotive Industry in 2023: Mahindra & Mahindra
Mahindra & Mahindra, a prominent Indian automotive company, has embraced Generative AI in its operations to enhance efficiency
Written by- Rajeshwar Raj & Team
They have automated the maintenance of robots and heavy machinery on the factory shop floor, resulting in reduced downtime and improved worker morale. Additionally, the company has emphasized the use of Generative AI for the automotive industry. They are using this technology to train customer chatbots, saving time for agents and enhancing the customer experience. While they are optimistic about Generative AI’s potential, they currently use it in a co-pilot mode and believe that it has not reached full maturity for independent operation. Bhuwan Lodha, SVP and head of digital at M&M’s auto sector, discusses these use cases and emphasizes the importance of ensuring a return on investment in AI.
In an interview, Bhuwan Lodha, Senior Vice President and Head of Digital at Mahindra and Mahindra Auto Sector, highlighted the significance of artificial intelligence’s growing influence. He emphasized the specific focus on Generative AI and its diverse range of applications like this:-
AI’s impact on the automotive industry
Bhuvan provided an overview of his role as the Senior VP and Head of Digital at Mahindra and Mahindra Auto Sector. He underlined the three main pillars of his responsibilities, which encompassed the enhancement of customer and dealer experiences, the optimization of operations across various plants and supply chains, and the innovation and advancement of product development systems.
As the conversation shifted towards AI’s impact on the automotive industry, Bhuvan elaborated on its transformative effects. He explained how AI had already made its presence felt, both within and outside the vehicles. Inside the car, flagship vehicles now feature connected technologies that harness vehicle-generated data to provide customers with an array of personalized services. Beyond the vehicle, AI permeated every aspect of the customer journey, from initial engagement and lead generation to loyalty programs, while also significantly contributing to manufacturing and operational efficiencies.
Use of Generative AI
Bhuvan delved deeper into the subject of Generative AI, acknowledging its recent rise to prominence. He provided valuable insights into its diverse range of applications within their organization.
One specific application Bhuvan highlighted was the utilization of Generative AI within their manufacturing plants.
He outlined how these plants were equipped with large industrial machines and robots from various OEMs, each having its own maintenance lifecycle and error management processes. Maintenance teams had traditionally documented their knowledge and experiences in ‘why it happened’ (WHYI) sheets whenever issues arose. Over the years, they had collected these sheets, trained internal models, and created a bot that shop floor workers could rely on. When facing machine or robot malfunctions, workers simply input the error code, and the chatbot, powered by Generative AI, provides step-by-step instructions on how to resolve the issue. This innovative solution significantly reduced downtime and empowered shop floor workers to troubleshoot effectively.
Intriguing application of Generative AI
The enhancement of their chatbot operations. He described how their experts engaged with prospective customers discussing SUV needs. As customers interacted with the chatbot, Generative AI played a pivotal role in providing personalized responses based on individual inquiries. This seamless integration of AI has not only streamlined customer interactions but has also contributed to a more satisfying customer experience.
The conversation delved into the origins of these innovative solutions. Bhuvan was asked whether they had been provided by external solution providers or developed in-house. He emphasized their commitment to data security and the need for control over implementation, which led them to develop these solutions in-house. These custom models were meticulously deployed on their proprietary cloud infrastructure, often in collaboration with major tech companies.
Changes after the Use of AI & Gen AI
Bhuvan was then asked to shed light on the most significant challenges posed by AI, both in terms of technology and data. He offered a well-rounded perspective, stating that while AI technology itself had matured considerably, the primary challenge lay in ensuring a positive return on investment (ROI) for use cases. AI implementation incurred costs, and the expectations for ROI were substantial. With regard to Generative AI, he highlighted the inherent complexity of black-box models and the ongoing challenges in directly exposing them to customers. In most cases, they opted for a “co-pilot” approach, where human operators worked alongside AI systems.
The conversation further explored the roadmap for responsible AI and Generative AI use. Bhuvan emphasized the need to consider various factors, including technology maturity, use case relevance, ROI considerations, and the evolving regulatory landscape. He stressed the importance of fair and ethical AI usage, promoting its deployment as a tool to assist people rather than replace them. Bhuvan also highlighted data security, emphasizing a keen understanding of how these AI models utilized data in both the short and long term. He acknowledged the ongoing evolution of AI technology, its capabilities, and its limitations, underlining the importance of responsible AI usage, especially when considering potential inaccuracies and hallucinations in the results.
Insights
While Generative AI and artificial intelligence have significant potential to enhance efficiency and improve various aspects of business operations, it is crucial to ensure a positive return on investment (ROI) and consider ethical and responsible AI usage. The integration of AI in the automotive industry, as exemplified by Mahindra & Mahindra, has shown transformative effects, from optimizing manufacturing processes to enhancing customer experiences. However, there are challenges, including the cost of implementation and the need to address the complexity of AI models. It’s important to use AI as a tool to assist people rather than replace them, ensuring data security and ethical considerations are paramount in AI adoption and deployment.
The previous statement on the same theme, which was made a little earlier in time, was reported by the Financial Express on July 5, 2023, as per the following link,
References:
https://www.mahindra.com/blogs/mahindras-long-drive-on-the-tech-superhighway
https://www.techmahindra.com/en-in/?f=2180558080
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