The role that Artificial Intelligence (AI) plays in various industries including manufacturing, finance, and healthcare is on the rise. Companies are utilizing significant components of AI such as machine and deep learning to improve their efficiency and workflow, to better construct and maintain their equipment, and to boost overall sales.
Over the past few years, AI has noticeably disrupted the automotive industry. The adaptation of AI is changing the way we get around and will continue to have a more substantial impact on transportation. Below are three AI trends in the auto industry that are expected to fuel the growth within this explosive market.
While the ultimate goal for companies is to create a fully-autonomous model, many manufacturers are easing themselves into the conversation by adding smaller-scale features. People are intrigued by the thought of a self-driving car, but they are more interested in the AI-based systems that are currently being installed. In 2015, the installation rate of AI-based systems in new vehicles was 8%, but that number is set to rise dramatically to 109% by 2025 as AI systems in vehicles become standardized.
With advancements in features like automatic braking, collision avoidance systems, pedestrian and cyclists alerts, cross-traffic alerts, and intelligent cruise controls, it’s clear that innovation is focused on driver assistance and safety. Intel Corporation believes that between 2035 and 2045, more than half a million lives could be saved because of autonomous and semi-autonomous vehicles.
However, as much as safety is a goal in the innovation of self-driving cars, it’s also a major concern. Companies like Uber have tested their robotic vehicles, but there have been many problems including one severe instance that resulted in the death of a pedestrian in March.
As fully autonomous vehicles become more of a reality, extensive regulation, approval, and software validation remain necessary components of the process.
The market for autonomous vehicles is there. NVIDIA claims driverless cars will balloon into an $8 billion opportunity for the company by 2025, and while it will likely be decades until autonomous vehicles are part of our everyday lives, companies and manufacturers are doing what they can to shorten the timeline.
Just as AI has evolved the automotive industry, cloud computing has taken AI to the next level.
Massive tech companies like Oracle are seeing the relationship between AI and cloud computing as an opportunity, and are adapting to serve a growing customer need. CEO Mark Hurd has recognized this need for cloud-based platforms and has catered to the shifting market.
“We became a service company in delivering real software and real-time services, and then we opened up a whole new mid-market of customers we never had before,” said Hurd in a recent podcast with Forbes. “When you take something to the cloud, everybody can be our customer,” he continued. “The market opens up to us now because of the cloud.”
We have already seen auto manufacturers make the shift to cloud platforms. Subaru USA, for example, recently adopted Oracle Cloud Platform’s integration and computing services to deliver a seamless end-user experience to their customers.
How can these cloud-based platforms and applications make life easier for drivers? Big data access and analytics, centralized connectivity, and fast processing speeds give drivers information in real time to enhance the overall driving experience. Some of these applications are already available, while others are coming soon. We’ve seen features such as:
- Locating gas stations and enabling the driver to pay for fuel from inside the vehicle.
- Providing reminders to purchase needed household items as the driver approaches relevant stores.
- Automatically pre-ordering food as the driver approaches a certain restaurant.
Through the continuous collection and analysis of big data, cloud applications will continue to adapt and serve drivers in ways they never thought possible.
Not only does AI have a growing impact on the ways that vehicles are used, but it’s also beginning to affect the way they are manufactured.
One example is quality control. According to a research report from McKinsey Digital, AI-based machines can detect defects up to 90 percent more accurately than humans. Insights from AI-based quality testing can also be used to analyze the root causes of defects and improve overall production processes. Not only will this save money, but it will improve the overall safety of the vehicles and their drivers.
Supply chain management is another example. Accurate forecasting is crucial to achieving a close-match between supply and demand, and AI systems are proving to be a viable solution. AI-based approaches could reduce forecasting errors by 30 to 50 percent. Through machine learning and real-time status views, AI-powered supply chains can adapt and respond to eliminate unnecessary issues and costs.
While some companies are developing these tools internally, others are turning to more established firms like NetSuite to optimize their processes. Their real-time transparency into company performance across all business functions and single version of the truth (SVOT) data warehousing creates an immediate impact on overall business intelligence.
From innovations in manufacturing to driver interaction, artificial intelligence has already started to transform the automotive industry and will continue to have a growing impact for years to come. To stay competitive, auto companies will need to continue to push the envelope and strive for the next best thing.