Source: Getty image/ Andrey Suslov

Q&A with Ansys

The automotive industry is increasingly using artificial intelligence to enhance various aspects of vehicle design, production and user experience. AI technologies are proving essential in streamlining processes, improving safety and enabling new business models, ultimately shaping the future of mobility.

One of the most significant applications of AI in automotive design is in simulation processes. Traditionally, simulations can take days to complete, but AI-driven tools are reducing this time to mere minutes. This acceleration allows automakers to evaluate new designs much more efficiently, leading to faster iterations and a shortened time-to-market for new vehicles. For instance, companies are now able to explore a wider range of design possibilities, which can result in more innovative and competitive vehicle offerings.

The shift from distributed electronic control units (ECUs) to centralized high-performance computing systems is another trend being driven by AI. This transition is crucial for managing the increasing complexity of software functions, including advanced driver-assistance systems (ADAS) and over-the-air updates. Centralized computing enables better integration of these functions, which is essential for enhancing vehicle performance and safety. Moreover, it supports the development of new business models, such as subscription services for software features and updates.

Safety remains a primary focus in the automotive sector, and AI is playing a key role in this area. AI technologies facilitate the development of safety systems in ADAS by providing fast and accurate simulations of real-world scenarios. These simulations are vital for ensuring that vehicles meet stringent safety regulations and for validating cybersecurity measures in connected vehicles. By enhancing safety features, AI contributes to building consumer trust and compliance with regulatory standards.

Despite the benefits, the implementation of AI in the automotive sector faces challenges, particularly in data management. Automakers must handle vast amounts of data for simulations and predictive analytics. AI tools are being designed to require fewer simulations while still delivering accurate results, thus reducing computational overhead and enabling quicker deployment.

As the automotive industry continues to evolve, AI is paving the way for innovative design concepts, such as autonomous vehicle interiors that prioritize user comfort and infotainment. This transformative potential of AI in mobility is underscored in our conversation with Mazen El Hout, senior product marketing manager at Ansys, where we explore how the company integrates AI technologies into automotive solutions and the implications for the future of mobility.

Key takeaways:

The following is an edited transcript of the conversation.

S&P Global Mobility: How is Ansys currently integrating AI technologies into automotive solutions, and what specific areas are showing significant measurable improvements in efficiency, performance and customer interactions?

Mazen El Hout: Ansys integrates AI through its SimAI software, enabling rapid simulation for automotive design. This reduces the time for simulations from days to minutes, streamlining resource-intensive processes. SimAI's ability to create surrogate models from historic simulation data allows automakers to evaluate new designs 10 to 100 times faster, facilitating broader design exploration. For example, Renault has utilized SimAI to significantly reduce the time to market while improving design possibilities. This AI-driven approach enhances efficiency and performance in all design phases, making it a game changer in the automotive simulation domain.

What emerging AI technologies or trends do you foresee shaping the future of the automotive industry, and how is your company preparing to address these changes while enhancing user experience?

Vehicles, which today are controlled by distributed electronic control units, are increasingly moving to centralised high-performance computing. This architecture is the key to integrating the growing number of software functions — from ADAS to over-the-air updates — efficiently and securely.

But the key question for the next few years will be: How do we manage this complexity? I expect simulation and test platforms to play a crucial role, especially in verifying software updates for older vehicle models. Companies that use digital twins and accurate simulation will be able to deliver reliable updates even years after production. This shift will not only create new business models, such as subscription-based features, but also pave the way for increasingly autonomous vehicles. The move to software-defined architectures is no longer a futuristic topic - it is a reality and will transform the entire industry in the coming years.

What role does Ansys play in integrating AI for safety systems, particularly in ADAS and cybersecurity measures for connected vehicles, and how do these innovations contribute to regulatory compliance?

Ansys supports safety system development in ADAS by enabling fast and accurate simulations of real-world scenarios. SimAI accelerates the testing of autonomous systems, ensuring vehicles meet stringent safety regulations. Its ability to model diverse vehicle behaviours also aids in validating cybersecurity measures for connected vehicles. These innovations help manufacturers achieve compliance with regulatory standards while enhancing safety and reliability in increasingly connected and autonomous automotive environments.

What primary challenges do you face in implementing AI solutions within the automotive sector, especially regarding data management and analysis, and how are you addressing these?

One challenge is managing the extensive data required for simulation models. Ansys addresses this by designing SimAI to require fewer simulations — starting from 30 closely related datasets for specific applications — while still delivering accurate predictions. This reduces computational overhead and enables quicker deployment. By offering a SaaS model, Ansys simplifies integration and reduces infrastructure demands, overcoming barriers to entry for AI adoption in the automotive sector.

Have any unexpected use cases for AI emerged recently?

AI has unlocked potential in reshaping simulation workflows. For instance, automakers are now using SimAI not only to refine existing designs but also to explore radically new concepts, such as autonomous vehicle interiors prioritizing comfort and infotainment over traditional driving aesthetics. Additionally, surplus computing and simulation capacity from AI efficiencies is enabling exploration of niche topics like enhanced aerodynamics for electric vehicles, driving further innovation across the industry.

Contacts

Copyright © 2024 S&P Global Inc. All rights reserved.

These materials, including any software, data, processing technology, index data, ratings, credit-related analysis, research, model, software or other application or output described herein, or any part thereof (collectively the “Property”) constitute the proprietary and confidential information of S&P Global Inc its affiliates (each and together “S&P Global”) and/or its third party provider licensors. S&P Global on behalf of itself and its third-party licensors reserves all rights in and to the Property. These materials have been prepared solely for information purposes based upon information generally available to the public and from sources believed to be reliable.
Any copying, reproduction, reverse-engineering, modification, distribution, transmission or disclosure of the Property, in any form or by any means, is strictly prohibited without the prior written consent of S&P Global. The Property shall not be used for any unauthorized or unlawful purposes. S&P Global’s opinions, statements, estimates, projections, quotes and credit-related and other analyses are statements of opinion as of the date they are expressed and not statements of fact or recommendations to purchase, hold, or sell any securities or to make any investment decisions, and do not address the suitability of any security, and there is no obligation on S&P Global to update the foregoing or any other element of the Property. S&P Global may provide index data. Direct investment in an index is not possible. Exposure to an asset class represented by an index is available through investable instruments based on that index. The Property and its composition and content are subject to change without notice.

THE PROPERTY IS PROVIDED ON AN “AS IS” BASIS. NEITHER S&P GLOBAL NOR ANY THIRD PARTY PROVIDERS (TOGETHER, “S&P GLOBAL PARTIES”) MAKE ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, FREEDOM FROM BUGS, SOFTWARE ERRORS OR DEFECTS, THAT THE PROPERTY’S FUNCTIONING WILL BE UNINTERRUPTED OR THAT THE PROPERTY WILL OPERATE IN ANY SOFTWARE OR HARDWARE CONFIGURATION, NOR ANY WARRANTIES, EXPRESS OR IMPLIED, AS TO ITS ACCURACY, AVAILABILITY, COMPLETENESS OR TIMELINESS, OR TO THE RESULTS TO BE OBTAINED FROM THE USE OF THE PROPERTY. S&P GLOBAL PARTIES SHALL NOT IN ANY WAY BE LIABLE TO ANY RECIPIENT FOR ANY INACCURACIES, ERRORS OR OMISSIONS REGARDLESS OF THE CAUSE. Without limiting the foregoing, S&P Global Parties shall have no liability whatsoever to any recipient, whether in contract, in tort (including negligence), under warranty, under statute or otherwise, in respect of any loss or damage suffered by any recipient as a result of or in connection with the Property, or any course of action determined, by it or any third party, whether or not based on or relating to the Property. In no event shall S&P Global be liable to any party for any direct, indirect, incidental, exemplary, compensatory, punitive, special or consequential damages, costs, expenses, legal fees or losses (including without limitation lost income or lost profits and opportunity costs or losses caused by negligence) in connection with any use of the Property even if advised of the possibility of such damages. The Property should not be relied on and is not a substitute for the skill, judgment and experience of the user, its management, employees, advisors and/or clients when making investment and other business decisions.

The S&P Global logo is a registered trademark of S&P Global, and the trademarks of S&P Global used within this document or materials are protected by international laws. Any other names may be trademarks of their respective owners.

The inclusion of a link to an external website by S&P Global should not be understood to be an endorsement of that website or the website's owners (or their products/services). S&P Global is not responsible for either the content or output of external websites. S&P Global keeps certain activities of its divisions separate from each other in order to preserve the independence and objectivity of their respective activities. As a result, certain divisions of S&P Global may have information that is not available to other S&P Global divisions. S&P Global has established policies and procedures to maintain the confidentiality of certain nonpublic information received in connection with each analytical process. S&P Global may receive compensation for its ratings and certain analyses, normally from issuers or underwriters of securities or from obligors. S&P Global reserves the right to disseminate its opinions and analyses. S&P Global Ratings’ public ratings and analyses are made available on its sites, www.spglobal.com/ratings (free of charge) and www.capitaliq.com (subscription), and may be distributed through other means, including via S&P Global publications and third party redistributors.