Will AI and SDV Transform the Future of EVs?

The panel discussion explored Software-Defined Vehicles, Artificial Intelligence and connected mobility as the new key drivers of EV growth. The session was moderated by Ajesh Saklecha, Co-Founder, Ozone Motors. The discussion featured Mahesh Medida Venkata, Leads SDV Program, Jaguar Land Rover; Brahmanand Patil, MD & President, Vector Informatik India; Sai Sridhar, Managing Director, Elektrobit India Pvt. Ltd.; Rajat Srivastava, Founder and CEO, Df-OS; and Jagrit Gandotra, CBO, Aion-Tech Solutions Limited.

Experts highlighted that EVs have ushered the automotive industry into a new digital era, where vehicles are no longer just hardware products but smart platforms powered by software, data, AI and connectivity. Through Software-Defined Vehicles, vehicles can continuously evolve throughout their lifecycle with over-the-air updates, new features and improved performance.

The discussion also covered important issues such as cybersecurity, functional safety, data privacy and AI-based predictive maintenance. The panel emphasized that a strong ecosystem of data and connectivity between vehicles, OEMs, service centres, insurance companies and fleet operators will play a crucial role in the future of mobility.

According to the experts, EVs have created a new platform for Software-Defined Vehicles. Going forward, the effective use of AI, data analytics and cybersecurity will make vehicles safer, smarter, more connected and more predictive, giving a new direction to the next generation of electric mobility.

How important is software in a Software-Defined Vehicle (SDV), and what should be its limits?

Jagrit Gandotra: EVs can now be described as “computers on wheels” because they generate large amounts of data. This data can be used for analytics and insights, but it also increases cybersecurity risks.

Threats can include battery manipulation, charging fraud, vehicle theft and the theft of customer behavioural data. Therefore, cybersecurity should not be treated as a feature added later, but should be built into the vehicle architecture from the beginning.

Should we move beyond Software-Defined Vehicles towards Software-Defined Mobility?

Rajat Srivastava: I see Software-Defined Mobility as a much broader concept. With the arrival of EVs, mobility has reached a point where a vehicle is no longer just a product but part of a larger digital ecosystem.

In the future, vehicles, insurance providers, fleet managers and other parts of the mobility value chain can be connected with one another. Bringing all these elements together can create better services and greater value for the customer.

Why are EVs considered the most suitable platform for Software-Defined Vehicles?

Sai Sridhar: EVs are digitally native systems. In traditional ICE vehicles, the software and hardware were largely defined at the time of manufacturing, after which the vehicle operated in more or less the same form throughout its lifecycle.

EVs have changed this model. Electronic systems in vehicles can now be updated and improved through software throughout the vehicle lifecycle. This means that a vehicle can continue to become better over time.

A Software-Defined Vehicle will not remain limited to the software inside the vehicle. It will have deep interaction with the entire digital ecosystem around the vehicle. As a result, cybersecurity, data and digital assets will become increasingly important.

What is the biggest difference between ICE and EVs in the context of Software-Defined Vehicles?

Brahmanand Patil: ICE vehicles also contain a significant amount of software, but most of it is developed and installed during the manufacturing stage. Changing the torque or other critical parameters of an ICE vehicle over the air is not easy, as it may require the vehicle to undergo homologation again.

The EV powertrain, however, is still evolving rapidly. Battery technology and electric powertrains are continuously improving. Therefore, vehicles need to be continuously enhanced through software updates.

With over-the-air updates, new applications and connected vehicle features, EVs can be upgraded throughout their lifecycle. This is why EVs are considered a major and important platform for Software-Defined Vehicles.

How is the Software-Defined Vehicle changing the customer experience from an OEM perspective?

Mahesh Medida Venkata: Earlier, the customer’s vehicle experience largely began and ended with the delivery of the vehicle. However, Software-Defined Vehicles are changing this entire experience.

Instead of simply becoming outdated over time, vehicles can improve through software updates. Over-the-air updates can add new features, improve safety and enhance the customer’s driving experience.

Therefore, SDV is not just a way to add new features. It is a way to continuously improve the customer experience throughout the entire lifecycle of the vehicle.

What happens if a software update fails while the vehicle is being driven?

Sai Sridhar: If an app encounters a problem on a mobile phone, the phone can simply be restarted. However, this is not possible in a vehicle. If a system restarts while the vehicle is being driven, it can create a serious safety risk.

Therefore, automotive software requires a strong safety layer. This safety cannot exist only at the application level; it must extend across the entire hardware, middleware and application layers.

Vehicle software must be designed in such a way that a problem in one application does not affect critical safety and driving systems.

How can cybersecurity and AI improve vehicle safety in EVs?

Jagrit Gandotra: AI can be used to identify potential problems in advance. For example, if battery performance is deteriorating or there is a possibility of a future issue, the system can inform the customer beforehand. In this way, AI and data analytics can be used to improve vehicle reliability and safety.

Should vehicles always remain connected, or should software updates happen only when required?

Jagrit Gandotra: This depends entirely on the use case. If customer behaviour and driving patterns need to be continuously analysed, the vehicle may need to remain connected at all times.

However, constant connectivity is not necessary for every use case. Connectivity and data sharing can be customised according to the needs of the vehicle and the customer.

Rajat Srivastava: The manufacturing sector offers an important lesson. Data streaming can primarily take place from the machine to the cloud, while significant changes to the machine or system can follow a Human-in-the-Loop model. Multi-factor authentication, secure locations and other safety conditions can be made mandatory for software updates.

How is safety ensured during software updates?

Brahmanand Patil: In the automotive sector, safety and cybersecurity are deeply interconnected. Several safety conditions are checked before any software update is carried out.

Before updating any critical controller, it must be ensured that the vehicle is in the correct condition. Additional safety protocols are applied when updating critical systems such as the engine, powertrain and braking systems.

Vehicles have several potential entry points, including connected systems, telematics, Bluetooth, Apple CarPlay, Android Auto, USB, CAN, LIN and Ethernet. Therefore, cybersecurity must be implemented at multiple levels.

Automotive cybersecurity follows an “onion-peel” model, with multiple layers of protection. Even in the event of a cyberattack, it is essential to ensure that the vehicle’s critical safety functions remain unaffected.

What role do SDVs and AI play in preventive, predictive and prescriptive maintenance?

Mahesh Medida Venkata: Clear and uniform standards for SDVs are still being developed across the industry. Just as autonomous driving has different levels, SDVs may also have different levels of safety and maturity in the future.

Functional safety and cybersecurity standards will play an important role in SDV development. As the technology evolves, software updates and connected features in vehicles can be made increasingly secure.

Rajat Srivastava: Preventive maintenance has existed in vehicles for a long time. Regular servicing and scheduled maintenance are part of this approach.

Predictive maintenance requires a significant amount of operational data. RPM, vibration, temperature and other sensor data, along with actual failure data, are all important.

In the case of batteries, a Battery Passport is also extremely important. Information about the materials used in the battery, the amount of recycled material and the battery’s complete history can help provide a more accurate assessment of its condition and potential future problems.

Prescriptive maintenance goes one step further. It is not enough to simply predict that a vehicle may face a problem in the future; the system should also suggest what action should be taken to address that problem.

For this, the vehicle, service centre, insurance provider and the wider mobility ecosystem must be connected. The industry is currently progressing towards predictive maintenance, but reaching the prescriptive level will require better data integration and connectivity.

How important is driver and vehicle usage data for predictive maintenance?

Sai Sridhar: Predictive maintenance does not depend only on vehicle sensor data. Driver behaviour and how the vehicle is being used are also extremely important.

For example, it is important to know whether a vehicle is continuously carrying heavy loads in hilly areas, how the driver is operating the vehicle and how much stress is being placed on the vehicle. All these factors can help estimate when maintenance may be required.

This data is particularly important for fleet vehicles. By combining vehicle sensor data, driver behaviour, routes and operational usage, it is possible to estimate when a particular vehicle may require maintenance.

However, data privacy is also an important consideration. Proper permissions and clear regulations are essential for the use of personal data, OEM data and other types of data.

How are AI and data analytics being used in EVs and commercial vehicles?

Jagrit Gandotra: Several EV and motor companies are already making extensive use of data analytics tools. These tools help companies understand customer behaviour and vehicle performance.

Based on this data, companies can make decisions much faster than they could through traditional processes. This is particularly important in commercial vehicles and fleet operations, where even a small improvement in efficiency or cost savings can have a significant impact at scale.

In the future, AI and analytics will make it possible to better understand vehicle performance, battery health, driver behaviour and operational efficiency.

Conclusion

The panel discussion made it clear that EVs have ushered the automotive industry into a new era of Software-Defined Vehicles and Software-Defined Mobility. Vehicles are no longer simply hardware products; they are becoming continuously evolving digital platforms connected through software, data, AI, connectivity and cybersecurity.

Experts emphasized that over-the-air updates, AI-based predictive analytics, cybersecurity, data integration and connectivity across the wider mobility ecosystem will play a crucial role in future vehicles.

However, this development also brings greater responsibility for safety and data privacy. Therefore, SDV development cannot focus only on adding new features. Hardware, software, AI, cybersecurity and functional safety must all be developed together.

Overall, EVs have created a new digital platform for the automotive industry. In the coming years, vehicles that can continuously learn, update themselves, predict potential problems and remain connected to the wider mobility ecosystem will shape the future of smart and sustainable mobility.