Optimizing next-gen in-vehicle infotainment system with AI and ML
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We had a water cooler chat with a product engineer of a leading luxury auto original equipment manufacturer (OEM)On our common interests in music.
As we chatted, we drifted to the death of Bill Withers and his iconic song ‘Ain’t no sunshine’. He showed a Spotify playlist of Withers on his mobile and rued about the additional six-month Spotify subscription that had come with the infotainment system of his 2020 number plate as a free package, something that he hardly used. This led us to discuss how OEMs have been adding more electronics to keep pace with growing consumer demand and how the increase in automated self-driving vehicles has turned the spotlight on next-gen in-vehicle infotainment (IVI) systems in cars.
Trends in in-vehicle infotainment
Our conversation with the engineer led us to the following insights and possible interventions to help OEMs navigate this trend:
Blurring the lines of infotainment: As the centerpiece of the ‘cockpit’ of the future car, next-gen IVI integrates multiple systems with the current standard infotainment system in cars (of entertainment and navigation), which includes the instrument cluster (for vehicle operations) and the advanced driver assistance system (ADAS). This integration is blurring the boundaries and definition of IVI, and as the product engineer in our conversation said, it depends on who you ask.
Managing multiple teams with multiple focus areas: Auto OEMs have separate engineering teams working on different components of the IVI system. Often, these teams work in silos and lack an integrated view of the product.
Cellphone on wheels: From smart speakers to smartphones, consumer expectations for the quality of interactions they have with devices and the features these devices provide, continue to rise. These expectations extend to IVI systems as well. However, mobile technologies are evolving at a much faster rate than car technologies. So, OEMs are left with a quandary – what features should they build and which ones should be integrated through smartphone projection solutions?
Bridging the electronics skills divide: According to the Boston Consulting Group, electronic components account for approximately 35% of a car’s material costs, and by 2030, this will rise to over 50%. Most engineering personnel, however, lack the digital skills required while reorienting their operations to put customers first. With almost 50% of the engineering budget dedicated to electronics and software development, auto OEMs must work to bridge this gap.
The above points, if not managed well, can become a recipe for disaster with higher costs of development and support as well as poor quality.
Moving towards an optimized next-gen IVI experience
Auto OEMs must work towards a deeper understanding of the customer’s behavior through his/her interaction with the IVI system.
This will help OEMs to (a) optimize existing IVI features by providing it in the way the customer intends to use it while being cost effective, and (b) define IVI features for future models. To achieve this, a cross pollination of customer relationship management (CRM) data along with IVI data becomes critical.
Here are a few low-hanging use cases (see Figure 1), where a data-driven approach using artificial intelligence (AI) and machine learning (ML) can help OEMs resolve these questions:
Figure 1: IVI use cases for OEMs
The water cooler chat was just the tip of the iceberg.
Next-gen IVI systems offers a powerful touchpoint for automobile manufacturers, enabling brands to successfully engage with customers to share and retrieve information, collate data, and provide a plethora of value-added services. Analytics forms the base of these transformations.