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The role of Artificial Intelligence in the automotive industry

The role of Artificial Intelligence in the automotive industry

With technology developing at a faster pace than ever, the automotive industry needs to keep apace. Professor Prashant Pillai, Director of the Wolverhampton Cyber Research Institute, has co-authored an Industry White Paper along with Munish Sharma from TCS, one of India's largest IT companies. The Role of Artificial Intelligence in the Automotive Customer Journey, addresses some of the challenges of the future. Here, Professor Pillai outlines his views and ‘the art of possible’:

AI is the future for automotive industry success

The automotive industry is currently undergoing phenomenal changes under the influence of digital technology.

Demand for interactive digital features in the vehicle, urgency to engage with the customers on digital channels and transitioning from reactive to pro-active customer service are among priorities car makers.

Interestingly as the automotive sector is embracing the first wave of digital technology i.e. cloud, mobile apps, social media and analytics to meet the expectations of today’s digital natives, there is already anxiety building up in the ecosystem to gear up for the next wave of digital technology.

These will include Artificial Intelligence (AI), Blockchain, IoT, Big Data and Augmented Reality. As part of a contribution to a new White Paper, we are outlining the ‘art of possible’ in automotive customer journey by leveraging AI technology.

AI, where systems perform visual perception, speech recognition and synthesis and decision-making capabilities like human beings, is addressing the challenges faced by the car makers in the automotive customer journey.

Pre-sales, 70 per cent of customers consider their decision to purchase the car on digital channels and use product comparisons, peer consultations, car configuration, online deals, stock visibility, etc. While car manufacturers can analyse this information and generate business insights, they still lack the capabilities to contextualise these insights for each individual customer to offer promotions/deals tailored for each individual needs.

New technology analyses the similar web patterns and predicts the possible outcomes through algorithms, creating a customised sales process for the prospective customer.

To help consumers understand the main features of a modern car, which in today’s context offers a combination of 100 plus options, chatbots can engage with customers on quick Q&A mode to assess individual lifestyle, using pattern matching to classify the text and produce a suitable response for customers.

Almost 80 per cent of new car sales are either financed or leased, with the average time taken at the dealership to complete the finance formalities four-five hours. Most of the online EMI calculators do not consider customer credit history /credit profiling and customers frequently change their mind to switch to other models due to differences in monthly instalments, increasing waiting times and dissatisfaction.

A possible solution for this situation is to use an AI based intuitive mobile app where customers can input the new car details, trade-in vehicle registration number (if applicable) and loan amount. The app should be capable of pulling customer background information, repayment history and estimated value for trade-in vehicles from the equivalent of Kelly Blue book.

The quality of the vehicle service/repair at the dealerships is critical to retain customer loyalty. AI technology can play an important role by enabling an intelligent platform for the front desk staff at dealerships and contact centres. The AI powered solution can assist the users (front desk staff) to ask the right questions based on customer verbatim to define and capture correct symptoms. The system can provide the recommendations to fix the problem either in DIY mode or pinpoint the guided repair process for the technicians to work upon.

The automotive industry at present is primarily operating on a reactive customer service model. This essentially means that customer reaches out to manufacturers/dealers to address their repair needs/parts failures. This situation leads to the disruption in customer transportation, warranty expenses, additional expenses of courtesy cars and roadside assistance. The role of AI can transform this traditional practice, allowing managers to reach out to customers before the actual failure occurs.

Artificial Intelligence is seen as a key disruptive technology that will fuel growth for the automotive industry. While its uses in autonomous driving, traffic management, and improving production has already been well appreciated, this White Paper presents its role in improving the customer journey.

It is important that the industry starts preparing for the AI adoption by facilitating the collecting and harmonizing of data from the different sources, setting up a data sharing ecosystem across the various stakeholders and establishing a team to drive the required transformation.

About the Authors:

Prof Prashant Pillai has nearly 16 years of research experience and specialises in the areas of communication networks, cyber security and intelligent algorithms. His current research interest lies in the application of AI and developing novel security solutions for safety critical systems (like smart grid, autonomous cars, aeronautical systems and robotics). He is a Senior Member of IEEE, a Fellow of the HEA and a Fellow of the BCS. He was recently appointed a founding member of the IEEE special interest group on Big Data for Cyber Security and Privacy and the Co-Chair of IEEE Future Networks Technology Roadmap 5G Satellite Working Group.

His co-author is Munish Sharma, who heads the Customer Experience Management (CEM) value engine of the Innovation and Transformation Group at TCS UK & Ireland. He has over 17 years of automotive industry experience focusing on digital transformation of manufacturing industry. Most recently, he has been working in the Information Technology sector (IBM and TCS) as a digital consultant for the manufacturing sector. 



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