The Automotive Industry in a Search-Driven, Software-Defined World

Car buying is no longer linear, loyal, or dealer-first. Winning new customers will be critical as loyalty weakens and more brands and models enter the market. In 2025, 17 more automotive brands and 81 new models entered the industry, compared with figures from 2019. Competition is intensifying, so brands and retailers need a mindset to dominate market share, with a focus on standout products, customer experience across all touchpoints, and performance.

We’ve already seen this play out within AI search using our AI Visibility Tool, LLMLens. When we tracked used car prompts for one national dealer group across four major AI models, a newly launched SUV from a brand that only launched in the UK in 2025 was the topic where the group picked up the most mentions. They received 190 in total, ahead of generic used car queries and established models. New entrants aren’t just competing in physical dealerships, but creating conversations that retailers can take ownership of. 

This is where user-centred search comes into play. You need to be accessible throughout the customer journey, answering queries, showing expertise, and building authority and trust, so that when the time comes for a purchasing decision, your brand is front and centre. 

But first, the big picture. 

The global automotive market continues to be shaped by dominant players. In revenue terms, Toyota and Volkswagen remain out in front globally, while closer to home in the UK, Volkswagen and Ford continue to lead on brand popularity (2024).

Sales channels tell a similar story of transition, with online platforms influencing discovery, comparison, and decision-making, underscoring the need for automotive brands to show up across multiple touchpoints, both physical and digital.

Most innovations in automation are being driven by software-defined vehicles (SDVs), rather than advances in physical components. Bespoke software will be the ultimate driver in differentiating your vehicles from others and enabling continuous improvement of your product after it leaves the production line. 

Investors are increasingly backing startups pursuing original equipment manufacturer (OEM) strategies, battery technologies, autonomous driving, and software-defined vehicles (SDVs), with investment reaching approximately $170.8 billion, with a CAGR of 23% from 2009 to 2025. 

With the rise in investment, partnerships between established brands and startups are an important driver for innovation. With most start-ups being in an early phase, car brands and suppliers have an opportunity to shape new tech.

Consumer-electronics giants such as Xiaomi, Sony, Huawei, and Oppo are going to use their expertise in hardware, manufacturing flexibility, and large, loyal audiences to gain a stake in the automotive industry, leading legacy carmakers who are already behind in innovating.

Purchasing a car is a large financial commitment, and today’s buyers are taking no chances. To feel confident in their purchasing decision, modern car buyers are research-first and risk-averse, investing more time online before stepping into a dealership.

This is reflected in the questions people now ask AI assistants. In the prompts we ran for a regional dealer group in our tool, LLMLens, the ones where the brand surfaced the most included language within the prompt where the user was looking to build reassurance.

Examples included:

• Proper warranties
• Trustworthy
• Proper history checks
• Not just back street traders
• How do I avoid getting ripped off

Buyers aren’t just asking what to buy, but who they should be buying with.

Car search websites shape the early stages of discovery and research, helping buyers compare options, validate pricing, and build trust. Dealerships play a role much later in the journey, when confidence has already been established. In fact, consumers are more likely to enquire or visit a dealership when a vehicle appears consistently across multiple platforms, using this to confirm accurate pricing and reliable vehicle details before moving forward.

Search is no longer ‘just Google.’ Today’s search experience is far more fractured, with discovery happening across platforms like Instagram, Reddit, YouTube, and AI-driven models. Each of these channels captures demand at different moments in the user journey, which means brands need to be visible wherever and whenever consumers are looking for answers (BloomReach/Survata: 2015-2016 product search starts)(NBER Working Paper 34255 (ChatGPT scale)).

Let’s use ’best electric cars’ as an example. A strategy focused solely on traditional search would reach only around 20.6% of total demand, leaving vast visibility across social platforms, video content, communities, and AI-led experiences. Relying on a single channel means leaving a significant consideration up to chance.

Each AI model has it’s brand favourites. For one national dealer group we tracked in LLMLens, Perplexity accounted for almost half (46%) or all it’s mentioned across four models.

For a regional group, it was the reverse. Perplexity mentioned the brand just once in 100 responses, while ChatGPT, Claide and Gemini mentioned them 14-16 times. Optimising for AI as one channel means missing how differently each model sources its answers.

User-generated content (UGC) is a great way to demonstrate your brand’s reputation, fostering loyalty and providing social proof. Because the content is created by real owners, drivers, and enthusiasts rather than the brand itself, it increases trust and confidence in the product. With high-value products, this validation matters just as much as the pricing and spec of the vehicle.  

Creators and community voices are used in completely different ways across the buyer’s journey. Some content focuses on education, with how-to videos on maintenance, repairs, and styling, while others offer trusted opinions, industry news on release,s and hands-on experience with vehicles. Car detailing is a popular trend at the moment, with creators in this niche showing how cars are experienced in everyday life and promoting car cleaning brands. 

Creators like ChrisFix have built large audiences by producing practical, instructional content that’s suitable for enthusiasts and everyday drivers. This type of content supports buyers both before and after purchasing.

Then there’s AutoSocialUK, which brings industry experience to her content. She provides test drives, walkthroughs, and honest reviews across a wide range of brands. 

The value of UGC isn’t just to reach more people (although that’s a bonus). When it’s part of an all-encompassing digital strategy, this content can build authority and trust, validating decisions at the right time in a user journey. Often, these voices can carry more weight than brand messaging alone.

You’ve got to consider the introduction of the AI Overview and the rise in zero-click searches. As of Q1 2025, 26.6% of all internet users have been served an AIO, and SERP coverage for AIOs reached over 50% by November 2025. For automotive brands, this changes what visibility looks like and where it’s earned.

When researching AIO visibility, informational search intent is where they appear most often. It’s not just about the hard sell, but about providing the user with useful information when they need it. Practical guidance and information-seeking intent are also high indexers on ChatGPT, so make sure your content isn’t just talking about the latest deals and USPs, but on helpful content about your products, which in this case could be: 

For this search query, we used Carwow, Motorway, and Autotrader as examples, using generic (not brand-specific) prompts, by first feeding the seed keywords, ‘sell car online,’ ‘buy car online,’ and ‘buy used car online,’ into the tool. This provided an AI-generated list of 36 prompts, which are labelled with user intent stages and persona (beginner, expert, intermediate). From this, we picked six to focus on, as seen in the right-hand side of the image. This provides a heatmap of which brands are showing up across five major LLMs, and shares key opportunities to improve visibility. For the primary brand, we can calculate the share of voice across competitors and share other brands that appear in these searches. 

You could also use keyword data and user-behaviour to inform your strategy. From analysing current keyword data, results show that trends are up for the following informational queries:

An insurance company could produce an infographic comparing policies for electric versus gas vehicles, an explainer video for TikTok or Instagram, or on-site FAQs to ensure the brand remains visible and helpful across multiple touchpoints. 

Used-car marketplaces could curate a video series on YouTube and other video platforms that compares different electric car models to guide users towards their decision. This content could be extended into an interactive online questionnaire on their website and amplified through PR placements in authoritative publications, with new angles emerging as data is collected. 

Automotive brands themselves could publish blogs exploring electric car features and real-world benefits, connecting with potential buyers by putting them at the centre of the conversation. 

These results show how brands across the automotive industry, such as car manufacturers, local dealerships, and insurance providers, can use user behaviour to inform strategies tailored to each platform.

To show what this looks like in real life, we used LLMLens to ask four popular AI assistants (ChatGPT, Claude, Gemini and Perplexity) the kinds of questions car buyers actually type in, such as ‘where’s the best place to buy a used car with good warranty?’ The tool then recorded which dealer brands each AI recommended in its answers.

Think of the tool as the AI version of checking where you rank on Google, but instead of page links, the buyer gets a shortlist of brand names. If you’re not on that list, it’s likely that you aren’t being considered.

We looked at one regional dealer group, whose locations are well-known locally, but they’re overlooked in other areas. Across 400 AI answers, this group was recommended roughly 1 in 10 times. Its biggest competitor was a national franchised dealer group that was recommended more than twice as often and mentioned more than four times as much.

AI knows the brand, but mostly when their buyers name their home region within their question. AI isn’t yet treating it as a go-to name for general car buying questions.

The clearest gap for this brand was finance. When buyers asked about their car finance options, the group barely features, and these type of questions are more prevalent right before someone is looking to commit to a purchase.

To help improve on their visibility here, LLMLens compiles salient points and our team can work on opportunities to create a strategy for increasing brand visibility.

In this case, the regional group could publish helpful content surrounding finance options, and what they mean, including guides for buyers with poor credits, explainers on dealer versus broker finance. This could help them start to appear in those conversations they’re currently missing out on.

The national dealer group we looked at is a strong contender, but not the first name AI reaches for. This group was recommended in about 1 in 4 answers, making it one of the most visible brands tracked. But a national used car supermarket was recommended slightly more often, and in those responses, AI tended to go into more detail about their competitor.

This shows how being visible isn’t the same as being the top pick. The group performed best when buyers compared dealers head-to-head or asked about buying in a specific city, which suggests that AI does see this brand as a credible option. However, it was the weakest when buyers asked about popular car models. These are buyers who already seem to know what they want, which is exactly the point where being missing could cost you sales.

To help tackle this, the national group could work on building what’s already working – comparison content, while filling the gaps with buying guides for popular models and optimised specifications on popular models within their business, with structured data that is easy for AI models to read and understand.

A note on the data: the regional group’s prompts were run in September 2026 and the national group’s in October 2026. LLM visibility is a moving target. Models are updated regularly, answers shift as new content is published and indexed, and the same prompt can return a different shortlist from one week to the next. These figures are a snapshot of a moment in time, which is exactly why visibility needs tracking continuously rather than checking once.

Whether you make the cut comes down to how well AI understands what you’re offering, if you have content that answers specific questions that buyers want the answer to, and how consistently your brand is talked about across the internet. You can influence all three, but in order to prioritise and see where the greatest commercial opportunities lie, it’s best to know where you stand.

Winning visibility in today’s environment requires a multi-platform approach: authoritative, trustworthy content built around real user needs; a website underpinned by strong SEO and intuitive UI and UX; PR activity that supports brand awareness and reputation; and Paid Media that boosts presence in high-demand spaces. User-search is no longer linear – it’s messy and unpredictable. Users will enter different platforms in different orders and be at completely different stages of purchase. Being present across every stage of the journey through the listed elements will help automotive brands build a connected ecosystem and increase customer confidence. 

This is what we call ‘Orbit.’ You need to align search visibility, messaging, and content to real intent at each stage, using platform-specific content. 

You never know, it might even end up in a dealership visit.