Five Industries That Will Benefit from AI in 2022

Neural network

Artificial intelligence is changing the world as we know it. Estimates show that AI will contribute trillions to the global economy by 2030. This number will continue to grow as deep learning and computer vision become more sophisticated.

There are already several industries benefiting from AI, and in this article, we will discuss five specific sectors that will see the most significant gains in productivity and efficiency. But first, let us cover some basics:

What is AI & Deep Learning?

In short, AI is a process of machines learning how to do things that ordinarily require human intelligence. One of the most recent types of AI is deep learning, a type of machine learning that involves training artificial neural networks on large datasets. Deep learning has been shown to be more effective than traditional methods for tasks such as image recognition and natural language processing.

For industrial companies, AI can be highly beneficial for quality control. Indeed, quality control and automatic defect identification are the focus points of this article. Deep learning and computer vision can help identify quality concerns such as scratches, dents, and incorrect assembly. Let us dig in further.

Automotive

The automotive industry has been a significant adopter of AI in years past. For example, many automakers have used AI technology to build safety systems with collision avoidance. In advanced AI applications, automakers use deep learning techniques to power autonomous vehicles.

But automakers are increasingly turning towards AI to help save money on the bottom line: by applying AI to production.

In 2022, the automotive industry will see even more benefits from AI. For example, companies can use deep learning for automatic defect identification in manufacturing. The adoption of AI means that issues with the car body, such as scratches or dents, will be automatically identified for a human to repair.

In addition, automakers can use deep learning for quality control in the assembly line. With AI and deep learning, issues with the car, such as incorrect assembly, will be automatically identified and corrected.

Construction

The construction industry is another sector that is rapidly adopting AI technology. For example, construction workers can now use drones for surveying and mapping. In addition, deep learning is being used to develop construction management software. This software can help construction managers plan and execute projects more efficiently.

In 2022, the construction industry will see an increased impact from AI. For example, OEMs can use deep learning to develop autonomous construction equipment. This means that construction tasks, such as grading and paving, can be done without human intervention.

In addition, deep learning will be used for quality control in construction. Therefore, issues with the construction project, such as incorrect measurements, will be automatically identified and corrected.

Infrastructure

The infrastructure industry is one of the most critical sectors in the economy, but it is also one of the most underdeveloped sectors in terms of AI adoption. However, this is starting to change. Utilities are applying deep learning and computer vision to tasks such as condition monitoring and defect identification.

In 2022, the infrastructure industry will see a significant increase in productivity from AI. For example, deep learning will be used for automatic defect identification in transportation infrastructure.

This means that issues with the road, such as potholes or cracks, will be automatically identified and repaired. In addition, deep learning will also be used for traffic management. The adoption of AI to traffic management means that software will optimize traffic flow on a regional level.

Insurance

The insurance industry is another sector that is rapidly adopting AI technology. For example, deep learning is being used to develop predictive models for insurance. By analyzing defect imagery, insurers will anticipate risks and plan for them better.

Manufacturing

The manufacturing industry is one of the largest sectors. Recently, deep learning and computer vision have been applied to quality control and defect identification tasks.

In 2022, the manufacturing industry will see a significant increase in productivity from AI. For example, manufacturers will use deep learning for automatic defect identification in production lines. This means that issues with the product, such as incorrect assembly, will be automatically identified and corrected.

In addition, deep learning will also be used for quality control in the production process. For example, low-quality materials will be automatically detected and then flagged for human correction with AI.

These are just a few examples of how AI will benefit different industries in 2022. In general, deep learning and computer vision will be used for applications specific to each industry. This means that the productivity of every sector will increase as a result of AI adoption. So, what are you waiting for? Let’s learn how to get started!

How to work with Simerse for AI and Deep Learning?

Simerse is deep learning and computer vision company that helps businesses harness the power of AI. We have experience in a wide range of industries, including automotive, construction, infrastructure, insurance, and manufacturing. We can help you develop AI applications specific to your industry so that you can increase productivity and stay ahead of the competition.

The best part is that Simerse provides all the training data and AI models, so you don’t have to worry about technical details. We take care of everything for you so that you can focus on your business applications.

If you’re interested in learning more, please contact us today. We would be happy to discuss your specific needs and see how we can help you.