Consumers continue to embrace generative artificial intelligence (AI) not just to inform but to improve their buying experience. Consider this: 62% of consumers said they used AI to find and purchase new products, according to a new report by the Oliver Wyman Forum, which includes survey data from nearly 300,000 people globally over the past five years. The trend cuts across generations, with 56% of boomers saying they’ve used AI for shopping compared to 65% of Gen Z respondents.
The leading use cases — price comparison, faster product search, and personalized recommendations — sit at the exact moments where brand preference is formed. More than half of respondents to the Oliver Wyman Forum survey said they are comfortable with AI producing a curated list of personalized products based on preferences they provide, a 16% jump from 2023.
The automotive industry has watched these shifts unfold in consumer electronics and fast-moving consumer goods, often with the assumption that high-consideration, emotionally driven purchases like cars are fundamentally different. That assumption is no longer valid. The same AI tools people use to decide which headphones to buy are beginning to reshape how they choose their next vehicle. Automakers need to adapt their strategies to keep pace, or risk falling behind competitors. We highlight three important actions below.
Consumers use AI to deliver a single, definitive answer for product research
The most visible disruption is in search. Google’s AI Overviews, which launched in 2024, provides synthesized answers directly on the results page, eliminating the need for consumers to click through to individual websites. The shift from a list of blue links to a single, authoritative AI-generated answer has had dramatic consequences: more than 80% of searches now end without a click in categories where AI Overviews have rolled out, according to data from Similarweb.
This structural change impacts the consumer journey in three ways:
- AI as gatekeeper. AI decides what surfaces and what does not, making it the new gatekeeper for brand visibility.
- Algorithmic comparison. Product comparison shifts from an emotionally influenced, brand-curated experience to being driven by key performance indicators and algorithmically ranked assessments. Consumers no longer browse product pages and absorb brand narratives; instead, they receive a ranked shortlist based on specifications, ratings, price, and reviews.
- Validation first experience. The physical experience — whether visiting a showroom or, in the case of automotive, taking a test drive — shifts from exploration to validation. The customer arrives with a decision already substantially formed.
Price transparency is also greatly impacted, especially as affordability increasingly influences decision-making during uncertain economic times. In Germany, for instance, average vehicle prices surged by 40% between 2019 and 2024 while sales volumes dropped by 22%, according to our 2025 pricing study with JATO. AI tools that make cross-market, cross-dealer price differences instantly visible will compound the pressure. Total cost of ownership calculators are already embedded in AI responses for automotive queries. As these capabilities mature, the opacity that has historically enabled regional and dealer-level pricing variation will further diminish.
Automotive industry feels protected, but AI is reshaping decisions
The instinct in many automotive boardrooms will be to argue that car buying is different. They are complex, configured products often with long purchase cycles. They involve emotional decision-making, physical test drives, and personal relationships with sales representatives. All of this is true, and online sales serve as a reminder: while over 25% of online sales were forecasted for 2025, the reality remains just 3%–5%, underscoring that automotive is still fundamentally hybrid, not fully digital.
The AI impact will land first and hardest in the discovery phase, where consumers form their initial consideration set. By some estimates, more than 80% of consumers use digital touchpoints during their journey. It will progressively expand into comparison, total cost of ownership, feature-by-feature ranking, and financing scenarios, which are precisely the kinds of tasks AI handles well. The Oliver Wyman Forum survey showed a 33% increase in respondents using AI for overall financial planning between 2023 and 2025. The purchase execution phase — dealer interaction, test drive, handover — remains a human experience. But even that is changing: from persuasion to confirmation, from information delivery to emotional connection.
Three imperatives for automotive OEMs to win in AI commerce
The window for action is now. Based on current adoption trajectories, roughly one in two car purchasing decisions was influenced by generative AI in some form in 2025, whether through model research, price comparison, feature evaluation, or financing advice. That figure was near zero two years ago. Original equipment manufacturers (OEMs) that move decisively can establish positions in this new landscape before it consolidates.
First, position brands to be recommended in every AI shortlist. This requires understanding how AI algorithms evaluate and surface brands through structured data, broad internet presence, consumer-generated content, ratings, and diverse media formats. OEMs must actively manage their AI discoverability with the same rigor they apply to search engine optimization today, treating generative engine optimization as a core marketing discipline.
Second, win the decision layer before the sale. The moment a consumer’s AI assistant compiles a shortlist is the moment that determines whether a brand has a chance to compete. OEMs must ensure their product data, pricing structures, and value propositions are AI-readable, accurate, and competitively positioned. Configuration complexity, which has historically been a barrier to direct comparison, must be reframed as a structured advantage rather than an obstacle to algorithmic evaluation.
Third, elevate the role of the sales representative through AI, combining efficiency with deeper emotional engagement. In premium automotive, only a smaller part of the purchase decision is rational. AI will support this by handling inquiries, qualifying leads, and generating personalized offers. However, a large part of the decision remains emotional, driven by trust and personal connection. AI Sales Copilots will enhance this by providing tailored insights and real-time guidance.
The lesson from consumer goods is clear: AI commerce does not wait for industries to be ready. It restructures the path to purchase regardless of product complexity, price point, or purchase cycle. Automotive sales are more nuanced than many consumer products: complex, emotional, personal. But the mechanism that controls which brands make the shortlist is the same. And once a brand is excluded from the AI’s recommendation, no amount of brand heritage, dealer network strength, or marketing spend can compensate for the lost demand upstream.