Gen AI & Adjacent Technologies Will Enable Faster Electrification Of The Transport Sector
Shikhar Gupta is a seasoned Automotive, Energy, Electric mobility, and Industrial manufacturing sector professional with over 14+ years of experience in Strategy consulting, Sales enablement, new Solution go-to market strategy, and business development. He works closely with several global energy and automotive clients in developing their market entry, new business models, and diversification strategies.
In conversation with Charulatha, Correspondent, Siliconindia Magazine. Shikhar shares his views about how the emerging technologies such as GenAI reshaping the E mobility industry and the Impacts of GenAI and tech innovations on E mobility future.
How do AI advancements influence E mobility trends and drive transformation through emerging tech?
Electric mobility is one of the most transformative trends for the global economy, with the energy and automotive sectors most influenced. We can already see several large economies announced ban on the sale of ICE vehicles and promote EVs. While OEMs, and energy players are navigating through this journey, technology is emerging as a key enabler accelerating this shift. One of the important things to note here, with EVs growing in market share, we are not just talking about clean fuel, but also more digital and connected cars. As per a latest report , the overall automotive software and electronics market is projected to grow to nearly $660 billion by 2030, more than doubling today’s size of $320 billion.
AI, thus, is finding multiple applications in the EVs, and has far reaching effect so far. Over the last 3-4 years, AI applications have risen across the value chain. In the upstream part of the value chain, AI is finding use cases in the manufacturing of vehicles by streamlining assembly line operations, supply chain management, and other manufacturing processes. Further, real-time data analysis by AI-powered systems are enabling OEMs to reduce errors, identify bottlenecks, thereby improving production schedules. Similarly, AI algorithms play a key role in battery management systems. The performance of EV batteries is influenced by several factors such as temperature, driving behaviour, load, and charging patters. AI enables users to analyse all this data and optimize range and performance.
Fleet management companies are the most aggressive adopters of electric vehicles due to better economics. As per my conversations with fleet managers, they find AI driven real-time assessments most critical to optimize costs. Right from managing charging needs of the vehicles to predictive maintenance of EV parts, to optimizing route patterns and vehicle idle time, fleet managers are finding EVs highly efficient. With several states, including Delhi announcing to convert all aggregator fleets to EVs by 2030, I foresee AI and data analytics playing a key role in deciding the profitability and efficiency of fleet operations.
How Are Emerging Technologies Such As GenAI Reshaping The E Mobility Industry?
GenAI is currently the most discussed theme across the boardrooms of all major companies, including automotive. All major OEMs and EV players are currently looking to develop a GenAI roadmap, with focus on identifying short-term, and medium-term use cases.
What excites me most about GenAI is the potential of this technology to revolutionize the entire design, manufacturing, and customer experience part of the value chain. For instance, Toyota Research Institute, announced a new GenAI Technique for the vehicle design process, that enables designers to cut down the iterations needed to reconcile design and engineering considerations. It also allows to incorporate engineering constraints directly into the design process, thus helping the firm design electric vehicles quickly and efficiently.
Safety, is another dimension that can be significantly enhanced by the use of GenAI technology. By analysing real time data from sensors and cameras, it enhances Advanced Driver Assistant Systems (ADAS) and enabling users to improve collision detection, lane keeping, and parking assistance. It also analyses users driving patters and history to generate the most optimal driving pattern.
One that I feel will make the biggest difference from the end users’ perspective is personalized car experience. GenAI will enhance the existing linear and rule-based voice assistants to more intelligent, which can assess customer sentiment and respond accordingly. These chatbots will be able to engage and revolutionize the entire experience for driver and passengers by offering tailored and relevant features such as suggesting nearby charging stations, route planning, shopping, music. Mercedes-Benz is another major player which integrated ChatGPT into its in car voice control to amplify in-car customer experience.
Can you detail the integration of AI and emerging tech in e mobility and the challenges it presents?
Beyond AI, several other technology innovations are already well integrated into the vehicles. Telematics and connected car features are already creating several new revenue opportunities for the companies. Almost terabytes of data will be analysed by a single car per hour. To ensure companies can unlock value from this data, AI and data analytics are critical. Hence, companies ensure they leverage cloud-based platforms to get real time intelligence.
However, as vehicles become more software driven and electronic, challenges such as cyber attacks, data privacy, and other security related incidents are on a rise. This will increase further as fully autonomous vehicles take higher market share. With GenAI, data privacy has been one of the key issues, hence, a number of companies are currently ensuring they are creating private and secured GenAI environment, completely isolated. Similarly, several companies are now working with Data Loss Prevention vendors. I expect data privacy to take centre stage as GenAI applications gain prominence across the vehicle value chain.
Cyberattacks are another major concern. Electric vehicles are onboarded with chips and software that drives batteries and motors to cruise control and other connected features. Further, while connected to the charging infrastructure, there is two-way data and information flow, making this entire process prone to hacks.
Impacts of GenAI and tech innovations on E mobility future? How are organization adapting?
Gen AI and other advanced technologies will have a very positive impact on the appeal of electric vehicles for both private and commercial users (such as fleet management companies). It not only enhances market appeal, but also safety and dependability of electric vehicles thus accelerating the transition. I believe tipping point for electric vehicles has arrived for several use categories such as fleets. With the advent of GenAI, this pace of adoption will accelerate further.
For organizations, it will be critical to focus not just on strategy but also enablers like workforce transformation. OEMs and suppliers not only need to hire the right skills but also upskill legacy workforce. It won’t be an easy task as it involves significant change management and needs a strong push from the top leadership.
In conversation with Charulatha, Correspondent, Siliconindia Magazine. Shikhar shares his views about how the emerging technologies such as GenAI reshaping the E mobility industry and the Impacts of GenAI and tech innovations on E mobility future.
How do AI advancements influence E mobility trends and drive transformation through emerging tech?
Electric mobility is one of the most transformative trends for the global economy, with the energy and automotive sectors most influenced. We can already see several large economies announced ban on the sale of ICE vehicles and promote EVs. While OEMs, and energy players are navigating through this journey, technology is emerging as a key enabler accelerating this shift. One of the important things to note here, with EVs growing in market share, we are not just talking about clean fuel, but also more digital and connected cars. As per a latest report , the overall automotive software and electronics market is projected to grow to nearly $660 billion by 2030, more than doubling today’s size of $320 billion.
AI, thus, is finding multiple applications in the EVs, and has far reaching effect so far. Over the last 3-4 years, AI applications have risen across the value chain. In the upstream part of the value chain, AI is finding use cases in the manufacturing of vehicles by streamlining assembly line operations, supply chain management, and other manufacturing processes. Further, real-time data analysis by AI-powered systems are enabling OEMs to reduce errors, identify bottlenecks, thereby improving production schedules. Similarly, AI algorithms play a key role in battery management systems. The performance of EV batteries is influenced by several factors such as temperature, driving behaviour, load, and charging patters. AI enables users to analyse all this data and optimize range and performance.
Electric vehicles are onboarded with chips and software that drives batteries and motors to cruise control and other connected features
Fleet management companies are the most aggressive adopters of electric vehicles due to better economics. As per my conversations with fleet managers, they find AI driven real-time assessments most critical to optimize costs. Right from managing charging needs of the vehicles to predictive maintenance of EV parts, to optimizing route patterns and vehicle idle time, fleet managers are finding EVs highly efficient. With several states, including Delhi announcing to convert all aggregator fleets to EVs by 2030, I foresee AI and data analytics playing a key role in deciding the profitability and efficiency of fleet operations.
How Are Emerging Technologies Such As GenAI Reshaping The E Mobility Industry?
GenAI is currently the most discussed theme across the boardrooms of all major companies, including automotive. All major OEMs and EV players are currently looking to develop a GenAI roadmap, with focus on identifying short-term, and medium-term use cases.
What excites me most about GenAI is the potential of this technology to revolutionize the entire design, manufacturing, and customer experience part of the value chain. For instance, Toyota Research Institute, announced a new GenAI Technique for the vehicle design process, that enables designers to cut down the iterations needed to reconcile design and engineering considerations. It also allows to incorporate engineering constraints directly into the design process, thus helping the firm design electric vehicles quickly and efficiently.
Safety, is another dimension that can be significantly enhanced by the use of GenAI technology. By analysing real time data from sensors and cameras, it enhances Advanced Driver Assistant Systems (ADAS) and enabling users to improve collision detection, lane keeping, and parking assistance. It also analyses users driving patters and history to generate the most optimal driving pattern.
One that I feel will make the biggest difference from the end users’ perspective is personalized car experience. GenAI will enhance the existing linear and rule-based voice assistants to more intelligent, which can assess customer sentiment and respond accordingly. These chatbots will be able to engage and revolutionize the entire experience for driver and passengers by offering tailored and relevant features such as suggesting nearby charging stations, route planning, shopping, music. Mercedes-Benz is another major player which integrated ChatGPT into its in car voice control to amplify in-car customer experience.
Can you detail the integration of AI and emerging tech in e mobility and the challenges it presents?
Beyond AI, several other technology innovations are already well integrated into the vehicles. Telematics and connected car features are already creating several new revenue opportunities for the companies. Almost terabytes of data will be analysed by a single car per hour. To ensure companies can unlock value from this data, AI and data analytics are critical. Hence, companies ensure they leverage cloud-based platforms to get real time intelligence.
However, as vehicles become more software driven and electronic, challenges such as cyber attacks, data privacy, and other security related incidents are on a rise. This will increase further as fully autonomous vehicles take higher market share. With GenAI, data privacy has been one of the key issues, hence, a number of companies are currently ensuring they are creating private and secured GenAI environment, completely isolated. Similarly, several companies are now working with Data Loss Prevention vendors. I expect data privacy to take centre stage as GenAI applications gain prominence across the vehicle value chain.
Cyberattacks are another major concern. Electric vehicles are onboarded with chips and software that drives batteries and motors to cruise control and other connected features. Further, while connected to the charging infrastructure, there is two-way data and information flow, making this entire process prone to hacks.
Impacts of GenAI and tech innovations on E mobility future? How are organization adapting?
Gen AI and other advanced technologies will have a very positive impact on the appeal of electric vehicles for both private and commercial users (such as fleet management companies). It not only enhances market appeal, but also safety and dependability of electric vehicles thus accelerating the transition. I believe tipping point for electric vehicles has arrived for several use categories such as fleets. With the advent of GenAI, this pace of adoption will accelerate further.
For organizations, it will be critical to focus not just on strategy but also enablers like workforce transformation. OEMs and suppliers not only need to hire the right skills but also upskill legacy workforce. It won’t be an easy task as it involves significant change management and needs a strong push from the top leadership.
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