Navigating the Future of AI

September 20, 2024

Matt Wolfe

Every fall, SAE International’s COMVEC symposium brings leaders from the on-highway, off-highway and defense sectors together to collaborate on solutions for the macro and micro challenges within the commercial vehicle industry. One of the executive panels at this year’s conference tackled the intricacies of AI’s effects both present and future on the industry and how various OEMs are approaching its implementation.

“There’s a lot of things going on in the industry that really aren’t getting a lot of airtime but are actually really important,” said Alan Berger, managing partner at abcg and moderator for the panel. “One of those things is the hype around generative AI. Is this topic relevant in our industry? What about all the data that we’re generating? How do we use that? Do these technologies have an impact on business models and how we go to market? And how do we get the right talent into the organization? We need to untangle all this.”

A panel of perspectives

Dr. Ray Gallant, VP of sustainability and productivity services for Volvo Construction Equipment, gave his general view on AI in the industry. “There’s a lot of talk in the industry about generative AI and classical AI. How do we use the new AI to take those mountains of millions of data points and make sense of them? We can’t possibly build a spreadsheet the way we used to and try to spot trends. There’s just too much data coming in and it overwhelms us. So, we can use AI to help us spot the trends and take direction from that data.”

Gallant continued, “What’s really exciting and what’s different than most of the innovations that I’ve seen in my career is now we have three completely different technology sets converging with each other. So no longer is it a technical innovation in one area that may disrupt that part of the industry, it could be a technical innovation for an [entire] industry.”

“I believe over the next 10 years, we’re going to see more change to this industry than we’ve seen in the last 100, which can induce anxiety,” said Steve Greenfield, general partner at Automotive Ventures. “But if you’re positioned correctly to leverage some of these trends it should really energize anybody in the audience, especially younger folks in the industry, which has been somewhat of a challenge.”

Phil McEwen, VP and general manager of commercial and special vehicles for Continental, provided his perspective on the business case for utilization of AI in the industry. “One of the big questions about AI on the business side is how do you enable this technology faster than we’ve done it before,” he said.

“My best example is telematics,” McEwen continued. “If you buy your car today it is available with telematics. The car talks back to the cloud and gives all diagnostics. Think about how long it took to come full circle to get that, what the barriers of entry were for a lot of these Tier 1s. And I love the startup topic here. That’s also a great way of forcing the industry forward.”

Driving development

abcg’s Berger asked the panel specifically if there were actual applications being employed in their respective businesses. “I think that the way to look at AI is practical,” Continental’s McEwen said. “Say you’re a venture capitalist and you’re raising a 10-year fund. So, whatever technologies you’re investing in and effectively betting on have to manifest within 10 years’ time. The adage is that being too early is worse than being wrong. This is very true in venture capital, and then how I look at it is really this framework, whether this is right or wrong.”

McEwen continued, “Compared to even three years ago, it’s crazy how much AI has improved. The quality, the throughput, the effectiveness of a software developer because they’ve effectively got this little co-pilot on the righthand side of the screen where it can be writing code for them or correcting their code in real time. So, the methodology of writing the code is very different.”

An example of the “end state” for AI is Tesla’s Optimus robot, which eventually will replace humans, McEwen said. “That may seem farfetched, but within two years Amazon will have more robots in their warehouses than humans. So, that inflection point is coming very quickly,” he said. “What I would like to see AI used as is a co-pilot, which is simply an augmentation. Think of it as increasing your intelligence by 10 IQ points and increasing your productivity by 25%. You’re going to see many more of those applications in the short term across every industry.”

Gary Johansen, VP of engineering for power systems at Cummins, discussed his view on AI’s capability to improve product development. “I think if you look across the entire value chain of what we do in product development, one of the best uses for this tool is alleviating the engineer tedium. Relieving the engineer of tedious tasks of report generation or documentation is very helpful.

“At the same time, we’ve got to be careful so we don’t remove [engineers’] opportunity to do their own thinking,” Johansen continued. “If you move all the way up the value chain to the product creation, product conception and exploring the design space in hardware in addition to software, and maybe finding solutions that we perhaps wouldn’t have thought of. So, one of the things we’re trying to do right now is make sure we’re not just focusing in one part of the value chain.”

Cummins is “walking before running” when it comes to AI implementation, Johansen added. “We’re trying to sample and pilot in areas that give us a strategic view about how these things might help us all the way through value creation. We’re not to that point yet, but I think in terms of saving money, saving time and creating value, we’re certainly trending in that direction.”

Predicting trends

Volvo CE’s Gallant provided observations on AI’s capacity to analyze large swaths of data and spot future trends. “AI is very important not only for analyzing huge amounts of data and spotting trends, but also for determining how can we use those to predict future trends. That’s how we get ahead of what’s probably going to happen, and AI is very good at building those kinds of models in real time by using the latest data that we couldn’t possibly do on our own.”

AI also has the potential to remove some of the biases engineers may have, Gallant said. “We’re all trained practically as engineers in our problem-solving routine to find the root problem. Then you come up with possible solutions, implement the solution, test it, then go back and follow up and tweak it where necessary.”

“We all have inherent biases,” Gallant continued. “Whether that’s things that have worked well for us before or things that we’re familiar with. And we ignore technologies that may be right beside us, but we’re not familiar with. AI has got a great promise of being able to look at all those technologies and propose solutions that may never have entered our sphere of influence if you will, when we’re coming up with those solutions.”

Gallant also provided a caveat to the SAE COMVEC audience. “The one caution I want to point out with AI is that it is only as good as the data going into it,” he stressed. “We’re seeing examples of misinformation where AI is providing flat out wrong information because the data in was bad. And of course, if you let AI scroll the internet for all the data on a particular subject, you’re going to get a lot of bad data coming in and your result is going to be similarly questionable.”

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