Sarwant Singh,

Managing Partner, Frost & Sullivan

Q. How do you think AI will affect the auto industry?

A. Artificial Intelligence (AI) will influence several aspects of the auto industry. Layered across various levels, AI will lead to the operation of vehicles autonomously. At Level-five, they could do so in any condition and at any speed. Such a possibility may look remote at this moment in time, it could eventually be the case. In India, automation is at Level-Two, and comprises of features like lane-keeping among others. Implemented effectively, it could help to save lives. For Levelthree or Level-four, platooning in CVs and a connected supply chain in a restricted environment could be a reality. This is linked with the way the supply chain network or warehousing is designed and developed. In the way that it includes certain elements. At Level-Three and Level-Four, it would be worth expecting different business models. Looking at examples where Daimler showcased an LCV with drone delivery integrates, it is clear that the driver no longer is a mere driver. He is on the way to become a fleet manager, and his profile is about taking the vehicle from A to B and reloading the parcel into a drone by an automated process and its making the delivery to the destination. Such models will work in India. In some regions if not all.

Q. What kind of stakeholders will AI attract in India?

A. Considering vehicle usage management and driver behaviour, stress would be on reducing the downtime and improving productivity. This will attract players like Mahindra & Mahindra and Tata. It is these majors that are leveraging AI to monitor vehicles. Companies like KPIT technologies, which are offering solutions. They are partnering with state run transport corporation and bus operators to monitor the vehicles in the fleet analysing them and the behaviour of the driver in terms of speed, efficiency, reliability, safety and route. Many fleet operators are using AI to analyse drivers productivity. AI is helping fleet operators to monitor invariable parameters and improve productivity and efficiency. The use of AI is set to grow in India.

Q. Isn’t infrastructure a challenge?

A. Infrastructure needs to be developed. Efforts are being made in this direction. An interesting example is of Porsche partnering with Bangalore Traffic Police to understand traffic conditions in the city and develop an intelligent transportation software. At intercity levels, such initiatives can be taken by CV makers. It will amount to much learning. They could partner with an established firm or a startup offering telematic solutions. They could partner with a large fleet operator. Clearly the progress from 4G to 5G will be crucial. It will come with infrastructure and AI. For example, it would not be possible to reach Level-Four of automation without 4G or 5G. There’s the issue of regulation too. So, it is not just the infrastructure, but various other factors that are posing a challenge.

Q. In terms of the total cost of ownership, how would AI help?

A. For the total cost of ownership, there is a need to differentiate between connected vehicles and autonomous vehicles. Autonomous vehicles, say, are still five to seven years. Connected vehicles are already here. Look at developments like Bridgestone acquiring TomTom Telematics, and the introduction of connected trucks like Rio by Volkswagen. The Rio leverages IoT to aid the fleet operator to increase efficiency. It makes a business case.

Q. How will it look like in India?

A. In the near-term, India will have very limited access to AI. It will mostly likely to be used for outside truck operations than the inside. Supply chain optimization looks like the first application area. The other area where would be the offering of value added service like TmaaS or Traffic Management by a tyre company for example. Unlike before, tyres are now equipped with a chip. The chip enables the monitoring of vital parameters in CVs, including load and route optimisation. In the short-term, in India, an ecosystem which optimises value added services like TmaaS to truck and bus fleet operators, will draw attention. It will add to the operation of BSVI vehicles as operators look for higher productivity. In the long-term, it is hard to predict.

If significant automation will come to India, it is difficult to anticipate. Its use in SCVs and urban CVs is expected to be lead longhaul CVs. Drivers will play a key role in its proliferation. It is new, innovative and disruptive opportunities that will drive AI in vehicles – CVs especially. In fact, the flexibility of application will drive automation and AI.

Q. What would be the economic implications?

A. At Level-Two, the implications will not be high in terms of a job threat. Vehicles with automation ranging from Level-Two to Level-Four will operate with driver assistance. Efficiency improvements will come from driver navigation pattern and driver optimization route flow pattern. Looking at the scale of the progress of automation, one need not worry about job losses for at least ten to twenty years from now. There’s also the need to look at nonautomotive or non-mobility stakeholders will play a role. Stakeholders like insurance companies or health care service providers for example. Much also depends on how they connect to the ecosystem for factors like accessing driver behaviour or vehicle parameter. There’s also the prospect of new services or business offerings. Energy and utility services for example in terms of electrification. New business models and revenue systems are in the making.

Q. How do you anticipate the regulations to affect?

A. I’m not very sure if the government is specifically looking at AI as such. It is just one form of application that is the result of an improvement in sensors and other related technologies. Look at how AI is shaping up, and it is looking at regulations. Regulations that are there, and regulations that are going to come.

Efforts are being made to adapt as well as localise AI everywhere. The department of IT and electronics is keen to localise electronics manufacturing. AI regulation per say may not happen but its implications would. With companies like Tata, Mahindra & Mahindra and Ashok leyland entering the fray, AI is bound to open up new avenues. It is bound to attract new players; players from fields like energy and infrastructure. With the generation of vast amount of data, AI is bound to create new value added business models. In the wake of the advancements and improvements, localisation will progress. This will involve sensor data, data analytics and a lot of external parameters. From the mobility perspective, improvement or evolution will revolve around how OEMs will bring technologies together and combine them. It will also depend on how it influences the TCO.