Generative AI for Quality and Safety in Automotive
AI applications in the automotive industry
The future of automotive quality and safety isn't just about airbags and seat belts. It's about intelligent systems that can foresee and mitigate risks before they happen, thanks to Generative AI (GenAI).
Artificial intelligence (AI) is revolutionizing the automotive industry, transforming every aspect of the value chain from design and manufacturing to sales and after-sales services. In this article, we explore how we have harnessed GenAI to drive efficiency and change in the quality and safety domain, along with specific AI use cases and applications that are driving significant value.
Automotive quality issue life cycle
The reality for automotive companies is that the quality and safety issue life cycle is fraught with complexity at every stage. The stakes are incredibly high: a single missed defect can result in massive recalls, regulatory penalties, reputational damage, and—most important—potential safety risks for drivers and passengers. Yet, the process of identifying, investigating and resolving quality issues is anything but straightforward. To identify and solve these problems, companies have to sort through mountains of data, with the majority of it being “noise.” Finding the real quality and safety issues can feel like finding the needle in a haystack. Even after the issue is identified, coordinating between engineering, manufacturing, warranty and field teams can be an operational challenge for investigators.
To bring these challenges to life, let’s walk through the quality and safety issue life cycle.
Initially, an event occurs that may be attributed to a quality or safety issue. Imagine a wheel bearing coming loose on your car. This could be through normal wear and tear with use, or it could be an early indication of a poor-quality part, potentially leading to a safety issue. When a quality and safety team hears of enough of these alerts to warrant an investigation, the team opens a case to further understand the issue. Here, the goal is to determine the root cause of what is going wrong. Is the bearing faulty? Was the assembly not installed correctly? Is there a part failing? Are these unrelated, coincidental incidents with no relation to each other? After the investigative team has reached a conclusion, a remedy decision is made for any issues that constitute a quality or safety campaign. From there, various administrative and regulatory actions are taken to ensure the issue is remediated.
Throughout this process, vast amounts of data are utilized. Hundreds of thousands of vehicle identification numbers (VINs) could be impacted by a single issue, which makes having the correct data critical. Given these challenges, traditional approaches may no longer be sufficient. Next-gen solutions—especially those powered by AI and GenAI—can help surface actionable insights and drive timely, effective responses. By automating data integration, accelerating root cause analysis and streamlining compliance, these technologies empower automotive companies to not just react to quality and safety issues but to anticipate and prevent them. The importance of drawing accurate insights from the available data cannot be understated.
Next-gen quality and safety GenAI use cases
Recently, GenAI has emerged as a game changer for solving quality and safety issues. The use cases below have the potential to deliver real results to enhance and expedite the quality and safety life cycle.
GenAI report generation: Throughout the quality and safety life cycle, dozens of reports are required. Reports to inform others of the investigation, presentations to executive leadership with the findings, potential regulatory reports, customer communications, etc. If an organization’s quality cases are stored on or within a process workflow application that lets employees compile information in one centralized location, this is a prime opportunity for GenAI report generation. Imagine being able to click a button and have a preliminary findings report, a SteerCo presentation, and an email to the customer service group all drafted. GenAI can streamline those repetitive processes, leaving your safety teams with more time to do the higher-level and strategic work.
AI root cause analysis: GenAI can be used to accelerate one of the most important but time-consuming elements of the quality issue life cycle—determining the root cause. Creating an issue investigator AI assistant results in a chat bot interface where investigators could rapidly obtain tailored insights, automate complex calculations, and enhance their ability to analyze data through simple, intuitive text querying and responses. Additionally, this interface could be used to retrieve key safety information from relevant documents, analyze historical investigation decisions or publicly available information to craft a recommendation, allowing for digitized institutional knowledge.
GenAI report generation: Throughout the quality and safety life cycle, dozens of reports are required. Reports to inform others of the investigation, presentations to executive leadership with the findings, potential regulatory reports, customer communications, etc. If an organization’s quality cases are stored on or within a process workflow application that lets employees compile information in one centralized location, this is a prime opportunity for GenAI report generation. Imagine being able to click a button and have a preliminary findings report, a SteerCo presentation, and an email to the customer service group all drafted. GenAI can streamline those repetitive processes, leaving your safety teams with more time to do the higher-level and strategic work.
Art of the Possible Lab
The quickest way to get started exploring quality and safety GenAI solutions is to inquire about an Art of the Possible Lab. During this workshop, the goal would be to learn more about potential problems you may be facing and hear more about any specific areas of interest. The objective of this lab would be to determine if a holistic AI roadmap strategy should be pursued, or if there is enough interest in diving into building a pilot for a specific challenge.
Current state assessment and AI roadmap strategy
If more than one of these use cases stood out to you, or if you are unsure of where to start on your quality and safety journey, Deloitte offers a fast-paced eight-to-12-week current state assessment, paired with a customized transformation roadmap. During this time, we will conduct an analysis of your end-to-end quality and safety practices, compare them against industry leading practices and cutting-edge solutions, and identify targeted areas of improvement. Finally, a roadmap will be developed to help incrementally achieve those goals over time.
GenAI solution pilot
Another potential option is to jump into solving a specific problem. With this approach, Deloitte can build a custom solution leveraging one of the GenAI use cases previously discussed. This would result in a solution pilot that applies to one part of the process, rather than a holistic GenAI transformation.
Opens in new window
Getting ahead of quality and safety issues may be achievable sooner than anticipated. GenAI is a critical component in helping solve quality and safety issues faster, which can ultimately result in safer vehicles on the road. Contact us today to learn more and get started on your GenAI quality and safety journey.
Contributors: Zack Nowland and Zach Herd
