New Delhi: Generative Artificial Intelligence (Gen AI), unveiled by Open AI in late 2022, has captivated digital consumers and Chief Experience Officers (CXOs) alike and drawn widespread attention. The State of AI 2023 Report by CB Insights reveals that Gen AI dominated 2023, attracting 48% of all AI investments with startups securing USD 42.5 billion across 2,500 equity rounds. This investment boom marks a new era in Artificial Intelligence, with companies rushing to adopt Gen AI to drive innovation and improve operational efficiency.Gen AI’s capabilities in image design, content creation, summarization, and conversational agents have led to its adoption across various industries, including retail and advertising. Companies like Adobe have introduced their own Gen AI tools as a supplement to their existing design software, while others have integrated enterprise AI solutions to boost internal productivity. Despite this, the manufacturing sector, and specifically product engineering and development (ER&D), has witnessed a more cautious approach to Gen AI adoption, primarily limited to proofs of concept in customer service and training.However, Gen AI could be the next EV moment for the automotive ER&D industry, as it could help companies reimagine the entire product development and realization process and reduce product development time and cost significantly to disrupt the market. Let us explore the possibilities across three key areas of Technology, Data and People.
Technology: Driving Innovation, Large Language Models (LLM) synthesize and innovate from extensive datasets, including product manuals and existing knowledge which is indexed properly. However, the product development process is fragmented across stages and spread across team/s, often using different software at various stages. A Gen AI application, whether based on an open-source LLM or a custom Small Language Model (SLM), that indexes internal design data could transform automotive design, testing, development, and realization process.
It would enable the creation of innovative designs and engineering solutions through simple commands, leveraging existing databases. This approach could produce multiple design variants and geometric engineering designs at unprecedented speeds, enhancing efficiency and innovation in automotive design like never seen before.
Imagine OEMs using Gen AI to analyze design data, performance metrics, and consumer insights, producing unique design blueprints rapidly. This method drafts new concepts and engineers design visions that align with market trends and exceed customer expectations, all at lower costs and higher speeds. With Gen AI, testing could leverage historical data for validation, testing outcomes, and synthetic data generation to deliver outcomes rapidly. Predictive and curative maintenance, powered by digital twins and Gen AI, could become the new norm, with Gen AI creating digital twins that predict breakdowns and offer solutions. Furthermore, Gen AI-powered vehicles could enhance customer experience by having intelligent conversations with drivers, assisting with travel plans, service visits, and support technicians easily in solving issues.
Data: Gen AI transforms historical data into an asset, creating design solutions that meet performance, safety, and consumer expectations. Automotive OEMs need to invest in data maturity to build an ecosystem that supports this transformation and creates consumable indexable reliable data. For Gen AI to succeed, it must learn from well-organized, high-quality data sets, requiring companies to invest in data collection, organization, and sanitization. Integrating AI with CAD and PLM systems requires technical innovation for seamless interoperability, while organizational changes, including AI adoption training and strict data ethics, are crucial for maintaining trust.
People: The shortage of AI talent poses a challenge, but Gen AI aims to democratize innovation, freeing creative minds from routine tasks and redirecting their focus to innovation. Gen AI enables non-coders to develop applications through simple interactions, unlocking productivity and cost efficiencies. As the automotive industry adopts Gen AI for electric vehicle development, challenges such as data maturity readiness arise.
Automotive OEMs that effectively utilize Gen AI can significantly shorten product development timelines, reduce costs, and surpass competitors. This new frontier offers traditional OEMs an unexpected advantage, allowing them to use their extensive data reserves to power SLMs and fully harness Gen AI’s potential. The future belongs to those who embrace Gen AI. The opportunity to redefine market leadership waits.
(Disclaimer: Santosh Singh is EVP and Global Head, Marketing and Business Excellence, Tata Technologies. Views are personal.)
