While “AI” continues to dominate industry conversation, its real impact is emerging in quieter, more practical ways. In 2026, automotive organisations are applying tailored, data-driven systems to improve safety, reduce risk and support decision-making – with accuracy, explainability and regulatory compliance now as important as innovation itself.

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With each new year comes new technological developments, and 2026 is no different. But in taking stock of the technologies that will have the biggest impact on motorists and the automotive industry in the coming year, there is one recurring theme that cannot be avoided.

“We can’t ignore the impact of AI,” says Martijn Versteegen, CEO of automotive imagery company Imagin.studio.

Versteegen argues that the impact of the set of generative technologies known as “AI” can now be felt from the very start of the customer’s journey.

“In the past, when people were searching on the internet websites were optimised for many years for search engines, with companies finessing their SEO until they were on page one of Google,” Versteegen says. “Today if someone is searching for a new car they just type in ‘What’s the best EV under 50 grand for a family of four with a dog’ and you get an answer from Google that starts with an AI overview. This is already happening and people might not even scroll down to the actual search results or even the sponsored links.”

Rather than focusing on SEO, as businesses have been doing for the last 15 to 20 years, Versteegen believes businesses should now be investing in “GEO” or “Generative Engine Optimisation”. He says this is not just a long-term trend, but drastic change in customer behaviour over the last couple of months.

“Some firms are seeing organic web traffic decline by as much as 50%,” Versteegen says.

AI-powered car sales

Jeremy Evans, Director of Marketing Services for TekCor4 company, Marketing Delivery, has also pointed to the increasing role of AI in the customer journey.

“[Last year] there were significant advancements in the deployment of automation and AI, and manufacturers and retailers are likely to integrate these more deeply into their operations this year,” Evans says. “The customer journey is evolving – from initial enquiry, through the buying process and into aftersales. To drive conversions and loyalty, retailers need new processes and tools for capturing and maintaining accurate data to underpin personalised and timely interactions, at scale.”

Last summer, Marketing Delivery ran a survey of its customers. They asked, “How would you feel about a car dealer using artificial intelligence (AI) tools to facilitate their communications with you, if it meant those communications were more personalised and relevant, and as long as your data was still protected?” Evans reports that 52% of respondents “were now either neutral about or would prefer a retailer to use AI”, a result which Evans claims “demonstrates a growing consumer acceptance of AI communication”. However, that still leaves a sizeable 48% of customers who are neither in favour of nor even neutral on the use of “AI”.

But despite mixed consumer feelings on the technology, applications are being found for GenAI products throughout the customer journey, not just in the early stages of the retail process.

AI-driven road safety

Motive is a firm providing an integrated platform that aims to improve the safety, productivity, and profitability of fleet operations. Nyanya Joof, head of Motive’s UK branch, tells us, “In 2026, the biggest shift in the customer journey is the move from reactive fleet management to real-time, AI-driven prevention. Road risk is rising, collision costs are climbing, and too many organisations are still managing vehicles and drivers across disconnected systems — creating blind spots and forcing reactive decisions.”

Joof says that where and how AI tools are being applied is changing.

“Advances in edge AI, where intelligence lives inside the vehicle and decisions are made in milliseconds, can give customers insights they can rely on in real time — not days or weeks later,” Joof says. “With AI Dashcam Plus, for example, the device can run more than 30 high-precision AI models simultaneously, enabling broader detection with fewer false alerts. That means the device can detect more unsafe behaviours like Forward Collision Warning, Lane Swerving, and Close Following in real-time with higher accuracy to detect risk faster and prevent more collisions. That’s a fundamental change in how safety technology supports drivers.”

Motive believes that by applications like this will drive greater consumer trust in the technology. Joof tells us that the AI is not just generating data, but enabling insights that are “accurate, contextual, reliable, and actionable in the moments that matter”. She believes it will set a new standard for road safety.

Meanwhile, Fleet Assist has been trialling its voice AI driven booking service with a small number of customers for several months as it aims to automate areas of its service booking for its customers’ drivers.

“The core objective is not to drive costs down but to ensure that the Fleet Assist team of specialists can focus on the more complex requirements. Effectively using AI for those low-risk high value tasks!” says Fleet Assist’s Technology Director, James Elliot. “Safety and trust are the key words that form the cornerstone of our AI development, starting with informing customers when AI is being used, offering customers and easy to use escalation path to a human at any time and ensuring the data handling is GDPR compliant.”

Fleet Assist currently plans currently a full role out of these tools by mid-2026.

Some are seeing AI as a way of mitigating driver error. Motive’s 2026 AI Road Safety Report, based on 1.2 billion hours of dashcam footage from commercial drivers, shows that collision risk rises as daylight shortens and driving conditions worsen.

“More importantly, it highlights that driver behaviour is a leading indicator of risk, outweighing factors like mileage or road type,” says Joof. “As a result, a big shift inside commercial vehicles is towards AI systems that detect risky behaviour early and support drivers in real time. Instead of relying on after-the-fact analysis, in-vehicle technology is increasingly identifying distraction and drowsiness, enabling hands-free, voice-activated support, and intervening before incidents occur.”

AI managed risk – and managing AI risk

This is not just about applying “AI” or automated systems on an individual basis, but about working towards an all-in-one, intelligent, connected system based on sensor technologies intended to give vehicles the perception they need to operate more safely in real-world conditions.

“Stereo-vision camera systems are emerging as an important upgrade, enabling true depth perception and earlier, more accurate hazard detection on increasingly congested roads,” says Joof. “Taken together, these trends point to a clear evolution: vehicles are equipped to become active safety environments that can help drivers anticipate risk and stay focused in challenging conditions.”

Returning to the beginning of the customer journey, one factor in “GEO” of Generative Engine Optimisation, is that it will tend to skim over duplicate images. Online retailers using stock imagery will find it hard to be picked up. This is the challenge Imagin.studio aims to address, having created a solution that creates unique imagery on the fly.

But this is an area where Generative AI tools find their limits.

“If you just ask ChatGPT to generate an image of BMW IX3 you’ll get an image that looks good, but people forget that AI models have been trained with source material without license, so it is infringing copyright, and can hallucinate,” says Versteegen. “It’s not consistent, it’s not accurate. There are a lot of input problems with AI generated imagery and a lot of issues with the output.”

Rather than relying on generated imagery, Imagin.studio creates accurate 3D models of every single car in its studio, allowing for the rendering of 100% accurate but unique images.

“By this process we cannot only guarantee the highest quality but also that we own all the copyrights on the content and provide a legally compliant product,” says Vertsteegen.

Joof also agrees that “AI” technologies should not be applied without due consideration.

“One of the biggest challenges isn’t the technology itself, it’s assuming a one-size-fits-all AI approach can solve every safety problem on the road,” says Joof. “We serve a diverse set of customers across a broad range of industries and verticals, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, waste services, and the public sector. Fleets are diverse across each of those industries and have different needs: different vehicles, different routes, different risk patterns, and different operational priorities.”

She tells us, “Generic AI models that aren’t tailored to real fleet behaviour often generate noise — too many false positives, irrelevant alerts, or insights that don’t align with how a particular fleet actually operates. At Motive, we believe AI should be customised to the realities of each fleet.”

Joof argues that the issues with AI applications don’t originate from the technology, but from how users apply that technology.

“The challenge isn’t AI itself. It’s adopting AI that understands the unique patterns and priorities of each fleet. When the technology is tailored and continuously improved, it becomes a partner in safety and performance, not a source of distraction,” Joof says.

While the use of programs that fall under the “AI” banner grab the headlines, a key part of this process is not generative or machine learning, but a more straight forward combination of sensors and data analysis.

Ashley Crookes, Sales and Marketing Director at independent leasing and fleet mobility company, Ogilvie, tells us about the new applications of built-in telematics.

“We now have data uploads from vehicles, with live management information and a live feed of our vehicles’ performance and maintenance needs. They can analyse that information and make better predictions based on the characteristics of a vehicle, booking it in for maintenance long before faults occur.”

It also has regulatory and tax implications. As the transition to electric vehicles continues apace, one of the biggest continuing dilemmas is measuring, funding and taking payment for electric vehicle charging.

“One of our partners, All Star has probably the largest charging network in the UK, with a charge pass that allows drivers to access the vast majority of the public charging highway,” says Crookes. “There is now a technological enhancement for drivers with a home charging unit where All Star can precisely calculate the driver’s home electric costs. It generates a HMRC-compliant invoice to allow the customer to calculate private use, business use and enroute charging.”

As Crookes points out, “One of the key principals many of our clients are adopting with van usage is bringing in external telematic suppliers, using tools like dash cams and driver scoring to create better arrangements with drivers, identifying drivers who are misusing vehicles and rewarding the ones who drive carefully.”

But this is not just about safety on an individual level, it is also about managing risk on a larger scale, in a way that has implications for the financing and insurance side of the industry.

“By sharing verified telematics and driver-behaviour insights, insurers can gain a more accurate and real-time view of organisational risk — enabling fairer pricing and faster claims resolution for both fleets and primary insurers,” says Joof.

Predicting and predictive AI

We are going to see the impacts of these technologies throughout 2026, but the technologies and their applications will continue to develop far beyond that, with the industry promising still more possibilities for the future.

“One of the biggest shifts ahead in tech is the rise of accurate, predictive AI becoming essential across the physical economy,” Joof predicts. “As the industry moves beyond the hype, accuracy becomes non-negotiable – especially in physical operations, where there’s no margin for error. In 2026, organisations won’t invest in AI on promise alone. They’ll expect measurable outcomes, clear ROI, and real bottom-line impact – and they’ll expect it fast.”

Motive’s goal is to embed accurate, explainable AI and automation across more workflows in its Integrated Operations Platform, so safety, operations, and finance teams can act earlier and work from a single source of truth.

“As safety AI moves from reactive alerts to proactive risk prevention, organisations can see real improvements — fewer collisions, faster investigations, and less manual review,” Joof promises.

Evans agrees that as fast as the technology is developing, customer expectations are incredibly high.

“We’re in the middle of a massive growth period for technology within the automotive space, and we don’t see this slowing down anytime soon,” says Evans. “Customers expect more from retailers than ever before, in particular with regard to the speed, relevance and timeliness of communications. Automation and AI are absolutely essential for meeting these expectations.”

Of course, the next big development that the industry is holding its breathe for is another form at AI. The long-promised self-driving car.

“Autonomous driving will be with us at some point, whether we like it or not. I believe the Government are doing an internal trial on that,” says Crookes. “I wouldn’t be surprised if we have that by the end of this decade, especially in some routes and industry types.”

Whether these technologies will be able to deliver on the promise and expectations, and whether consumer scepticism can be won round, remains to be seen. But perhaps one thing that needs to change is our use of the phrase “AI”. This article describes a variety of applications described as AI, but the programs and processes behind each of them are very different. One thing the technology sector will hopefully develop soon as a more specific and illuminating terminology.