The right use cases for the right customer type can make or break the adoption curve for AI. Staying close to customer adoption trends has never been more important.
CES 2024 was dominated by generative AI, with many companies showcasing services that helped demonstrate innovative, best-fit, use cases while driving consumer acceptance for the technology. For automotive specifically, this year’s event focused on the potential of AI in lower-stakes, consumer-facing applications such as vehicle personalization and in-vehicle services.
While generative AI tools and large language models (LLMs) are democratizing access to artificial intelligence, their success in automotive relies on the industry's ability to position the right AI integration use cases for the right customer demographics.
In late 2023, SBD Automotive partnered with a leading user experience research and analytics firm, Pulse Labs, for an innovative, hands-on experiential consumer study. Using the latest tools to analyze videos of participants using AI, apps, and websites, alongside their survey response data, the objective was to understand whether consumers use AI to solve everyday needs around automotive experiences. Participants compared using AI to an app or website experience for four key automotive tasks. Then we analyzed their interactions and perspectives on the ease of use and trustworthiness of AI in automotive applications when attempting the following tasks: buying a car, troubleshooting a dashboard light, bluetooth pairing, and planning a long trip.
So, what did we learn from this research?
The results revealed five key insights on the perception automotive consumers have of AI today.
Below is a top-level overview. Full details, including user videos and rich data, can be found in the downloadable report, The AI Future of Automotive: Consumers and the Conversational Car.
1. The barrier to acceptance is low for generative AI.
While our survey revealed that only 28% of the respondents had previously used AI for auto use cases, 72% said that, following their user experience on the tasks, they would prefer to use it. The AI’s clarity, conciseness, and relevance were the key influencing factors behind this shift, indicating there are several cases that are ripe for AI integration.
2. Users favored AI for its speed, specificity, and personalized responses.
Our respondents cited contextual/in-the-moment use case scenarios, such as a dashboard warning light, or simple tech support, such as Bluetooth pairing, as the top use cases for which they would prefer to leverage AI in automotive contexts. The technology’s quick response time aligned with the urgency to provide a better user experience in these cases.
Watch a Bard user get fast information with easy-to-understand visuals for dashboard light troubleshooting:
3. Users are developing a sense for when they trust AI.
While ease of use was higher on all use cases, trustworthiness on high stakes use cases was rated lower for AI than websites and apps.
4. Unique customer demographic of ‘Situational Believers’ shows that you can win users over with the right AI use cases.
While we expected the Preacher and Nay Sayer clusters to appear, for AI in automotive use cases, the emergence of the Skeptic, Believer, and Situational Believer clusters highlight nuances within customer clusters.
Situational Believers were participants who gave high ratings for their user experience with AI in some auto use cases, but not others. They were frequent users of generative AI like ChatGPT, Bard, Bing, etc., using it daily or multiple times a week. 33% of entry level vehicle buyers were Situational Believers and 40% were new vehicle owners (2023-2024 model years), with near equal gender distribution.
5. Executions leveraging bidirectional conversations implementing suggestive AI tools and contextually embedding audiovisual materials can lead to high engagement.
Here, Bard provided better embedding of contextual metainformation – supporting its responses and aiding the customer experience.
Ultimately, the right execution of best-fit use cases will play a pivotal role in the success of generative AI in automotive.
Overall, the study’s findings illustrate the need to stay close to customer adoption trends and ensure that hype around AI is suitably converted into a strong, thorough, implementation roadmap. This will bring true value to customers, while remaining scalable and monetizable for OEMs.
Engage with SBD Automotive & Pulse Labs by downloading the complimentary report and scheduling an expert briefing.
Furthermore, SBD Automotive and Pulse Labs can collaboratively help you on this journey by:
Enabling you to place the consumer experience at the heart of your AI strategy.
Support your work in identifying the right use cases and experience delivery of AI for your customers.
Download The AI Future of Automotive: Consumers and the Conversational Car