If there’s one thing I’ve learned from hundreds of conversations with automotive leaders over the past year, it’s that innovation is having a maturity moment, writes Jacqui Barker, Keyloop’s vice president of global engagement
Next month sees Innovation Week at AM so it’s a timely topic.
For much of the last decade, our industry has been fascinated by what might be possible. We’ve debated electrification, imagined autonomous vehicles and talked extensively about connected ecosystems, not to mention artificial intelligence. Innovation often felt exciting, ambitious, and let’s be honest a little ‘Tomorrow World’.
That’s changing.
This year, as I travelled between industry events, recorded episodes of the Drivetime podcast, and spoke with experts from across the globe in automotive, mobility and technology, I noticed a subtle but important shift in the conversation. The most interesting discussions were no longer centred on futuristic concepts or technology demonstrations. Instead, they are focused on execution.
The questions have evolved from ‘Can we build this?’, to ‘Can we scale it?’ It’s no longer, ‘Will customers use it?’, but ‘How do we operationalise it?’ And it’s not, ‘Could this technology change the industry?’, it’s ‘How do we create measurable value from it?’
Innovation is growing up. And three themes have emerged repeatedly throughout the conversations I’ve had this year, that I believe will shape automotive’s next chapter.
AI is moving from experimentation to practical application
Few technologies have attracted as much attention as artificial intelligence. Depending on who you speak to, AI is either the solution to every problem in automotive or the latest technology buzzword that will eventually settle into the background.
The reality, as always, is probably somewhere in the middle.
What strikes me most is how quickly the conversation has moved beyond fascination with the technology itself. Two years ago, most discussions revolved around what generative AI could do. Today, the most progressive organisations are focused on where it creates value.
At MOVE 2026, Juho Hyytiäinen, CEO of fleet intelligence platform Way, described AI as less about algorithms and more about context. Data alone, he argued, has limited value. The real opportunity comes when organisations can apply context to data and use it to improve decisions.
This has been a recurring theme throughout the year.
Peter Wilson of Volteras spoke about the industry’s shift from simply collecting vehicle data to helping businesses understand what that data actually means. Rather than presenting thousands of data points, the next generation of AI platforms will increasingly provide actionable recommendations and personalised insights.
At AM Live, Paul Hilton of JATO described a future where AI agents interact with structured automotive datasets autonomously, allowing machines to analyse information and surface insights far faster than human teams could manage manually.
Most importantly, not one person I spoke to viewed AI as a replacement for people. Instead, they viewed it as a way to remove friction.
Predictive maintenance that prevents downtime before it occurs, vehicle health monitoring that identifies issues before they become expensive repairs, smarter inventory management, better marketing attribution, more intelligent fleet operations.
These use cases are not futuristic; they exist today.
What separates successful AI deployments from unsuccessful ones is often surprisingly simple: data quality.
Time and time again, conversations returned to the same foundational challenge: Data.
Not glamorous or attention-grabbing, not worthy of a keynote headline, but absolutely essential. Without connected, accurate and accessible data, AI becomes little more than an expensive experiment.
The organisations creating the most value from AI today are not necessarily those with the most advanced models. They are the ones that have invested time in creating trusted sources of information and connecting their data ecosystems effectively.
The age of AI experimentation is ending and the age of AI operationalisation is beginning.
The software-defined vehicle is changing the rules
The phrase “software-defined vehicle” is everywhere right now. Unfortunately, many definitions make it sound far more complicated than it needs to be.
One of the most insightful explanations I heard came from Christiane Soppa of Bosch. She compared the future vehicle to a smartphone. Two people may own identical devices, but they have entirely different user experiences depending on the software, services and applications they choose to use. This same principle increasingly applies to vehicles.
That shift represents something bigger than a technology upgrade; it represents a fundamental change in how value is created.
Historically, vehicle value was largely fixed at the point of sale. A customer bought a car with a defined specification and that specification largely remained unchanged throughout ownership.
Software-defined vehicles challenge that assumption. For the first time, vehicle capabilities can evolve continuously with each owner. Functions can be updated remotely, features can be added after purchase and performance can improve through software. Battery management can become smarter over time and new services can be deployed throughout the vehicle lifecycle.
The result is a vehicle that behaves less like a traditional automotive product and more like a digital platform. And that creates new challenges and enormous opportunities. Because software-defined vehicles generate unprecedented amounts of data, organisations must develop the ability to transform that data into useful insights.
Bosch, Way and Volteras all described variations of the same challenge: creating meaningful intelligence from connected vehicle information. Whether predicting battery health, improving fleet efficiency or monitoring asset utilisation, the winners will be those capable of turning data into decisions.
The shift to software-defined vehicles also requires a different approach to partnerships. No single organisation can build every element of the software-defined ecosystem. The future belongs to organisations that can collaborate effectively across these ecosystems rather than attempting to control every component themselves.
That is why I increasingly believe the software-defined vehicle is less about software and more about collaboration. The software simply makes the collaboration possible.
Autonomous mobility is becoming an operational challenge, not a technology challenge
Autonomous vehicles have been part of the automotive conversation for years and yet many discussions still feel trapped in the same place.
We continue to debate technological capability while overlooking a more important question: What happens once the technology works?
One of the most fascinating conversations I had this year was with Carlo Lacovini, author of The Human Side of Autonomous Mobility. Unlike many discussions around autonomy, his perspective was grounded in practical deployment experience. His story wasn’t about perfect technology. It was about what happens when innovative technology collides with the real world.
Every new innovation should start with a pilot. Successful deployment requires consideration of customer expectations, operations, regulation, infrastructure, public acceptance, scaling challenges and all the messy realities that emerge when innovation leaves the laboratory.
Carlo described the industry’s evolution beautifully: First came technology, then ecosystems. Soon, he argued, success will be determined by operational excellence.
Carlo’s astute observation and lived experience aligns with what I’m seeing elsewhere. The most compelling discussions around autonomy no longer focus exclusively on perception systems, sensors or vehicle intelligence. Instead, they focus on the realities required to run autonomous services at scale.
Sam Clarke from Gridserve highlighted a similar challenge while discussing the UK’s growing electric freight infrastructure.
Technology alone does not create transformation, supporting ecosystems do.
Vehicles require charging. Charging requires infrastructure. Infrastructure requires investment. Operations require optimisation. Customers require confidence.
Every innovation journey eventually arrives at the same destination: execution, and execution demands ecosystems.
This may explain why so many mobility discussions now revolve around partnerships. No organisation can build autonomous mobility alone. Success will depend on software providers, infrastructure partners, vehicle manufacturers, mobility operators and regulators working together effectively.
The technology is becoming increasingly capable, but the operational challenge is only beginning.
The common thread: from innovation to implementation
At first glance, AI, software-defined vehicles and autonomous mobility might appear to be entirely separate trends, but I don’t think they are.
In fact, I believe they are all manifestations of the same underlying shift: The automotive industry is moving from invention to implementation.
For years, innovation success was measured by technical possibility, now it’s measured by operational reality.
The organisations that succeed over the next decade won’t necessarily be the ones with the most exciting technology. They will be the ones that understand how to deploy technology effectively.
They will connect data instead of creating silos. They will build ecosystems instead of isolated solutions. They will focus on outcomes instead of features. And perhaps most importantly, they will remember that innovation is ultimately about solving human problems, not creating impressive technology demonstrations.
The conversations I’ve had this year leave me optimistic. Not because automotive innovation is accelerating (although it is). But because the industry’s mindset is changing.
We’re asking better questions, focusing on outcomes, and beginning to understand that the most transformative innovations are rarely the technologies themselves. They’re the operational capabilities, partnerships and ecosystems that allow those technologies to create meaningful value.
Innovation isn’t slowing down, It’s growing up. And that may be the most important innovation of all!
Author: Jacqui Barker, vice-president of global engagement, Keyloop
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