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The Role of AI in Electric Vehicle Adoption

Artificial intelligence (AI) is rapidly evolving and becoming ubiquitous across virtually every industry. AI solutions allow organizations to achieve operational efficiencies, gain insights into customer behavior, measure key performance indicators (KPIs), and leverage the power of big data, among other things.


Similarly, the electric vehicles (EV) market has gained traction in recent years. It’s more common to see drivers cruising in EVs, whether a Tesla, Chevy Bolt, or Nissan Leaf. EVs are becoming popular among eco-conscious consumers because they offer more eco-friendly benefits than traditional gas-powered vehicles.


EVs have shown growth throughout the decade and great promise, but adoption rates have lagged in the U.S. compared to other countries.

Is it possible for AI to play a role in helping EV adoption in the U.S. and other countries? Here’s how the EV market could leverage AI to increase sales and create a more sustainable transportation system.





Looking at Current EV Adoption

The U.S. has noted increases in EV adoption rates, but rates are still on the low side compared to other regions of the world. According to data from the World Economic Forum, Norway, Iceland and Sweden lead the world in EV adoption.


One main reason other countries have adopted EVs on a larger scale is that it’s common for their governments to offer incentives to consumers. Various policies have incentivized EV purchases in Norway, but the World Economic Forum suggests this may not fly in other countries.


According to the Argonne National Laboratory, a U.S. Department of Energy (DOE) research center, nearly 2.4 million battery EVs have been sold since 2010. A critical aspect of the EV market is implementing the infrastructure to support charging. Many consumers may be hesitant to purchase or lease EVs because they worry about finding charging stations in their area.

The U.S. currently has almost 113,600 EV charging stations, with most of them located in California. The Biden administration announced a plan to allocate $5 billion in the next five years to build up the EV charging network, which will certainly aid in adoption rates.


How AI Can Speed up EV Adoption

Aside from government funding for infrastructure improvements, other factors will play a role in aiding EV adoption. An article from Forbes cites five major factors driving adoption, including:

  • Emissions regulations

  • Technology

  • Cost

  • Overcoming myths about the environmental impact of EVs

  • A fast-changing EV market with various players (Volkswagen, Tesla, Hyundai, Kia, etc.)

AI can be used for various applications, so it’s worth exploring how it can be leveraged in the EV market to drive adoption.

Improving EV Batteries

One piece of technology necessary for EV development is electric batteries. Developing a suitable battery for an EV requires testing various material combinations, and that’s a time-consuming process.


EV battery manufacturers can leverage AI solutions to sift through vast amounts of data much quicker than a human researcher. For example, a recent IBM project involved developing a battery capable of faster charging without nickel or cobalt. Researchers had to evaluate a set of 20,000 compounds to determine the battery’s electrolytes. Normally, it would take five years to process this data, but it only took nine days with the help of AI.


Additionally, AI can aid in testing batteries for EVs. Algorithms can be trained to predict how they will perform using only a small amount of data. Speeding up battery research and development will improve EVs, thus speeding up adoption.

Smoothing Out EV Charging Demand

A new project in Canada may help manage EV charging when demand is high. It was recently announced that the Independent Electricity System Operator (IESO) and the Ontario Energy Board (OEB) would support an AI project to improve EV charging management. BluWave-ai and Hydro Ottawa are leading the project, and it’s expected to enhance charging operations when energy is in peak demand.


The pilot project is called EV Everywhere. It uses AI to create an online service for drivers and pools batteries’ storage and charging capabilities. The system will automatically gauge customer interests and impacts, smooth out demand peaks, and allow people to capitalize on lower-cost charging during off-peak times.

Enhancing HMIs for Safety

Another factor driving the adoption of EVs is to ensure safety for drivers and passengers. One essential feature in an EV and most modern vehicles is the human-machine interface (HMI), which is needed for controlling and providing signals to various types of automated equipment, including the LED screens found in many EVs.


HMI systems that leverage AI solutions allow drivers to access a voice-enabled smart assistant, additional controls, better EV monitoring, and infotainment. AI-powered HMI systems will become more widely used, helping drive adoption.

AI has many use cases, especially in the EV market. It’ll be interesting to see how manufacturers and other companies leverage AI to encourage adoption.

Expect More AI Use Cases to Drive EV Adoption

It is becoming more popular for drivers to consider purchasing EVs, but adoption rates need to increase to create a more sustainable transportation system. AI will play a significant role in driving sales if more companies find innovative ways to use these solutions. It’s only a matter of time until EVs become the dominant mode of transportation, but leveraging AI will be critical in reaching that point.

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