A new wave of enriched and responsible customer experience in Automotive industry empowered by Gen AI

Gen AI powered by Large Language Models have taken many industries by storm. This includes Automotive industry as well. Chatbots have become more efficient and personalized. Knowledge retrieval has become easier, and automation of various documentation processing has become a child’s play. AI Use cases what could take many months of both human and computational resources are made cost effective and expedited due to advent of Gen AI. A few of the use cases in automotive industry where Gen AI can pivotal role are:

• Supply chain optimization for spare parts
• Visual inspection of automobiles in production
• Optimization of production assembly
• Technician assistance for fixing automobiles
• Prediction maintenance
• Hyper personalization

In this article, we will deep dive into enriching customer experience using hyper personalization in a responsible way with guard rails to ensure and respect the privacy of customers.

Personalization of customer experience in automotive industry after sales is challenging compared to other sectors like retail or banking. Usually, the extent of personalization in automotive industry for customers is related to cross-sell or up-sell, early warning of parts break down, and predictive maintenance.  Gen-AI has unlocked the door from personalization to hyper personalization for prolonged loyalty to the automotive brand and an opportunity for customer to become an ambassador of brand. Here are a few use cases that can be built to drive increase in customer experience using Gen AI.

1. Customized car controls:  Using historic settings used in the car – like the temperature of air conditioning/heater, fan speed, vent direction along with external temperature, temperature control can be customized on daily basis when the car is started for the day.  This can also be extended to loading music in Spotify or setting to specific radio station or loading audio book in amazon music depending on the type of media used by customer. The AI solution can also show recommendations based on the previous experience.
2. Preloading of maps: Based on the route taken on a day from historical data, the maps for the specific time of the day can be pre-loaded along with traffic conditions. The AI solution can also provide an alternate route to the destination based on the traffic or road conditions. When this recommendation is provided without request from customers, this sets the tone for positive experience for through out the day and customer will attribute this experience towards the brand.
3. Early warning of road conditions: Based on route taken, driving behaviour of customer, and current day road conditions of the route, early warning can be provided to the driver at least 2 minutes ahead of the impact like potholes, bumpy roads etc. In case of connected cars, this can be extended to warning rash drivers near by based on the driving behaviour of other customers that take the similar route and who are near by at that point in time.
4. Real time assistant for faults: Not every fault in a car requires roadside assistance or visit to the mechanic. Minor faults can be rectified by the customer themselves. The challenge lies in the lack of knowledge. For example, in the event of puncture, the challenge for many customers is lack of knowledge in changing tire. If there is a live help available with step-by-step instructions, this will be a game changer in the customer experience. The automotive brand can introduce a mobile app which is powered by Gen AI. When the incident occurs, by simply taking a picture, the AI assistant will be able to identify the issue occurred.

• If it can be remedied by customer themselves, it will provide step by step instruction to follow
• If it needs attention from experts, it will place the call to roadside assistance, create log for tow truck assistance and service center.  
• If it needs attention from insurance, it will direct customer for additional pictures to be captured and reconstruct scenario for First Notice Of Loss (FNOL).

While the above are a few of the use cases that can be built to drive increase in customer experience empowered by Gen AI, equal attention must be paid to respect privacy of customers and innovate using AI responsibly. Many time organizations put privacy in back burners in the name of innovation and profitability. As the times are changing with introduction of EU AI act and many other similar acts and regulations across the globe, nonchalance when it comes to privacy and other traits of Responsible AI can lead to heft fine and loss of reputation. The million-dollar question is to how do we balance between responsibility and profitability of innovation. Here are a few best practices to build guard rails for a responsible AI that rebrands customer experience through hyper personalization in the era of Gen AI.

1. Ensure to get permission from customers on using their data for training AI solutions for hyper personalization. In case of rejection and no answer, ensure to drop that data from training. Document the permissions in secured place and keep updating as the customer base increases.
2. Document the purpose of the use case, along with data used, algorithms used for building model, testing conducted, test results, deployment methodology and updates done after methodology
3. Conduct Data Privacy Impact Assessment on the customer data used
4. Test and validate the results of AI solution thoroughly.
5. Ensure the results from AI solution used for driving customer experience are monitored constantly and any drift is captured and communicated to stakeholders immediately.
6. Conduct red teaming of the AI solution and publish results with customers and stakeholders
7. Publish protocol in case of privacy breach
8. Inform the customer that they are interacting with AI solution in their automobile and provide an option to opt-out.
9. Provide an option to share feedback and contest for redress in the AI solution.
10. Conduct conformity assessment of AI solution with respect to transparency, privacy, security, accountability, fairness before deploying the solution.
11. Conduct periodic audits of AI solution to assure it is up to date with responsible AI principles.

By following the above best practices combined with power of Gen AI, organizations can rebrand customer experience in automotive sector through hyper personalization paving way to a better engagement with their customer base.

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