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Published May 30, 2024

Driving Forward: How Data and AI are Revolutionizing the Automotive Industry

Ocient's VP of Product shares insights from 2024 ICA Summit in Frankfurt, Germany

Director of Product Management Dylan MurphyBy Dylan Murphy, VP of Product

The automotive industry is going through radical changes filled with challenges, opportunities, and mind-blowing innovations. No one knows exactly what the future holds or how quickly we’ll progress, but a few things are very clear. Their business models and offerings are changing, there is a thirst for rapid innovation, and the data that will drive these changes is growing rapidly. Oh, and all of this is happening as the industry prepares to use, or increasingly use, AI.

A few weeks ago, I had the opportunity to discuss these trends at the Innovation, Connectivity and Autonomous (ICA) Summit in Frankfurt, Germany. It’s a fantastic conference to have one-on-one discussions with leaders in the industry and listen to their stories. Having tracked the automotive industry for years, we’re approaching a time when there will, undoubtedly, be some big winners and, unfortunately, some big losers.  

From the business-side, automotive companies are quickly shifting their business models to rely more on paid software services, consolidated manufacturing processes, and getting consumers more embedded in their brands. While these companies have limitless possibilities to innovate, they’re concurrently adjusting how they make money after a century focusing on selling cars, services, and financing.  One example of innovation is around predictive maintenance and issue detection. Using vehicle telematics datasets, iterative analytics, and solutions like OcientGeo, companies can save costs and provide a better user experience by predicting failures and maintenance requirements before they happen. 

As the business models change, the requirement to innovate and act quickly is critical. There’s an acknowledgment that partnering, sharing data, and sharing services will all be required to get to an autonomous future. While it’s an easy acknowledgment to make, it’s very complex to pull off from a people and organization perspective. From a technical perspective, these integrations, partnerships, etc. are equally challenging. Companies are urgently partnering while looking at ways to expedite their own development and innovation processes. 

One interesting thread of a conversation that I had with several leaders was around AutoSAR, an emerging standard for the auto industry. Bringing together a consortium of 500 companies, AutoSAR aims to establish uniformity in data flows and APIs, streamlining the integration process for OEMs, integrators and manufacturers alike. This standardization effort not only fosters interoperability among various autonomous systems but also facilitates the development of safer, more efficient vehicles. By pooling resources and expertise, the industry endeavors to accelerate innovation while ensuring compatibility across a diverse landscape of autonomous technologies. 

The industry is flooded with structure, unstructured, image, sensor, vector data that needs to be correlated around particular events. Improved understanding of this data as it fits together will drive innovations from autonomous progression, EV adoption, commercial fleet management, driver personalization, and safety improvements. Handling this data in an efficient way (cost, power, people’s time, etc.) is not an easy task.  

Data privacy is another heavy consideration for the industy, especially in Europe. Regulations like the General Data Protection Regulation (GDPR) impose stringent requirements on the collection, processing, and sharing of personal data. Automakers must comply with these regulations to earn the trust of consumers and demonstrate a commitment to data privacy and security. 

As the VP of Product Management for Ocient, my discussions at the ICA Summit were focused around moving, transforming, and analyzing these growing, already massive, datasets. It was clear that companies are preparing to leverage more AI to solve their problems from manufacturing to providing a better user experience. Concerns over how to handle the scale of their current data, position themselves for undefined AI use cases, and handle their data growth were recurring themes. Security, for obvious reasons, was another common topic for discussion.  

My presentation focused on why these large, critical datasets can be difficult to manage and strategies for building these future analytics solutions. We touched on issues that only arise at real, production scale. We discussed the growing complexity of data governance and security – interesting, complexity-ridden challenges in this industry. I helped the audience understand how to talk to their vendors about existing infrastructure and cost management.  

These are all topics that can last for days on their own. The main takeaway is that Ocient’s focus on complex, compute-intensive, always-on workloads, aligns extremely well with the journey of the automotive industry. We work with our customers as partners, and partnership will be required to tackle these challenges. It’s going to be very challenging for these companies to either spin up open source solutions or get a link from a hyperscaler to their new analytics environment and work well out of the box.  

As a father, I’m extremely excited by a safer, more sustainable, and convenient future. I also wouldn’t mind for an autonomous fleet to drive my children to their 30 activities this week. I’m probably missing my window for that, but in all seriousness, the future is exciting and bright. Together, we can accelerate progress, enhance safety, and create a more connected and sustainable automotive ecosystem for generations to come. 

You can see all my slides here and don’t hesitate to reach out to see a demo of Ocient today.