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  3. Leveraging Generative AI in the Automotive Product Design Lifecycle (PDLC): Redefining Creativity and Efficiency

Leveraging Generative AI in the Automotive Product Design Lifecycle (PDLC): Redefining Creativity and Efficiency

Ravindra Singh
Ravindra Singh

Practice Head – Vehicle Engineering

Annapureddy Veera Reddy
Annapureddy Veera Reddy

Practice Head, Data & AI, Mobility

Automotive
Artificial Intelligence

Published on 11 Mar 2025

min read

Automotive Product Design Lifecycle

The emergence of Generative AI (Gen AI) is reshaping how products are imagined, developed, and refined across industries. From being a futuristic concept in the realm of science fiction, it has, today, evolved into a practical tool for driving significant transformations, especially in product development. It compresses time-to-market, enables out-of-the-box thinking, and enhances creativity.

By leveraging Gen AI, global automotive companies can drive new standards in efficiency, innovation, and customer experience.

Success, however, depends on precision, thoughtful implementation, and a robust balance between AI and human engineering and technology expertise.

Transforming the Automotive Industry’s PDLC with Gen AI

The automotive product design lifecycle (PDLC) includes multiple stages, from advanced engineering and concept design to final product launch. Traditionally, this process is labor-intensive, time-consuming, and resource-heavy.

Gen AI serves as a catalyst for speed, innovation, and operational excellence. Its ability to process large datasets, simulate complex scenarios, and provide actionable insights helps improve every stage of this lifecycle.

Advanced Engineering and Concept Development

By accelerating idea generation, enabling the exploration of overlooked concepts, Gen AI helps optimize Design Verification Plans (DVPs) for robust technical accuracy. This helps OEMs and Tier-1 suppliers uncover opportunities from the planning phase onwards.

Concept Design and Development

AI-powered design tools, like CAD systems, significantly streamline workflows and reduce timelines. Designers can generate solutions meeting performance goals by inputting structural and functional prompts. This approach minimizes manual iterations, aligning innovations with consumer needs faster and with greater accuracy.

Computer-Aided Engineering (CAE) and Computational Fluid Dynamics (CFD) Integration

CAE and CFD simulation programs are crucial for performance predictions across key parameters, including, NVH (Noise, Vibration, Harshness) and durability. Using Gen AI can help enhance these processes by reducing meshing and analysis times by more than 70%. Engineers can save on computational resources while achieving improved accuracy in identifying potential failures.

Manufacturing and Assembly

The use of Gen AI extends beyond the design stage, transforming manufacturing processes as well. It ensures error-proofing in assembly lines and optimizes production strategies leveraging real-time data. These advancements reduce assembly delays and enhance overall efficiency.

Realizing Business Impact with Gen AI in PDLC

Generative AI offers revolutionary advantages. However, its effective usage requires careful application, oversight, and collaboration to ensure maximum business value. A notable concern in this regard is the "hallucination" effect, where AI models are found to generate incorrect or misleading information.

Without expertise to validate outputs, such issues could result in flawed designs or strategies. Hence, addressing key concerns include:

  • Ensuring Human Validation: Skilled professionals ensure that the product designs meet performance and market demands while validating AI outputs,
  • Integration with Consumer Insights: Combining AI results with real-world research delivers a deeper understanding of user needs, and
  • Adaptation to Trends: AI relies on historical data, but teams must remain agile to align AI insights with evolving market dynamics.

By addressing these challenges, businesses can unlock Gen AI’s full potential while avoiding pitfalls.

Generative AI as a Driver of Automotive Innovation

LTTS views AI as an enabler of human creativity. Our AI solutions enhance every PDLC stage, setting new standards in performance, safety, and efficiency.

LTTS Applications of AI

AI Assistants: Structured design assistance reduces errors and improves workflow accuracy during the concept phase.

AI in Design: CAD-AI integration generates innovative, optimized solutions with fewer iterations.

AI for CAE/CFD: Faster simulations lower analysis times by 70%, improving predictive reliability.

AI in Manufacturing: Real-time insights streamline assembly and improve project timelines.

This cohesive approach allows LTTS to partner with OEMs and Tier-1 suppliers, helping them shift from one-time sales models to continuous customer engagement. Our Fleet Data Analytics ensures manufacturers can build consumer loyalty while driving operational success.

Take the Next Step

Generative AI has come to represent the future of product design and lifecycle management. For automotive professionals ready to unlock business value and incredible innovation, the time is now.

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Ravindra Singh
Ravindra Singh

Practice Head – Vehicle Engineering

Ravindra Singh is an accomplished vehicle engineering expert with over two decades of experience in the automotive domain, ranging from conceptualization to production. Experienced in developing solutions for global OEM & Tier-1’s across geographies in the Mobility segment, he is currently the Head of Vehicle Engineering practice at L&T Technology Services.  Responsible for developing new areas of technical solutions like AI in PDLC, and working with Global OEM’s and Tier-1’s in designing products with efficient solutions that drive growth and help expand our market share, Ravindra continues to deliver multiple vehicle programs, from concept to production, across the design and development of full vehicles, including, body, chassis, interiors, and exteriors for EVs, Hybrid, and ICE vehicles.

Annapureddy Veera Reddy
Annapureddy Veera Reddy

Practice Head, Data & AI, Mobility

Annapureddy Veera Reddy is a Data and AI leader with over two decades of experience in developing, managing, and consulting on Data and AI strategy, architectural blueprints, and in building solutions for global enterprise clients across multiple industries, including Mobility and Hi-Tech. Currently as the Head of Data & AI practice for Mobility segment at L&T Technology Services, he is responsible for developing and executing a successful Data & GenAI architecture, frameworks, and strategies to build scalable, secure, and efficient solutions that drive growth and help expand the company’s global market share.

He has played a key role in setting up COEs for multiple global clients and hyperscalers to showcase LTTS solutions, besides helping enable academia collaborations with the Coventry University (UK) and IIT Hyderabad for the design and development of cutting-edge AI/ML models for AD/ADAS, including Level 2, 3 and 4 features. He has also led the development of LTTS’ data annotation platform AnnotAI, serving global automotive OEMs and Tier1 in their AD/ADAS journeys, and leads the development of the GenIQ platform for generating secure and scalable GenAI use cases across automotive, aerospace, and rail domains.

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