How Artificial Intelligence Will Impact These 10 Industries

Artificial Intelligence isn't slowing down

Every pundit and analyst has had artificial intelligence, or AI, on the tip of their tongue lately, and it’s not hard to see why.

No longer in the realm of science fiction, AI is set to revolutionize practically every industry it touches — and it’s already happening.

From virtual assistants and consumer chatbots to news aggregation applications, AI improvements are changing everything from the way individuals live to the way companies function.

Here are ten major examples of industries that will drastically change with the advancement of artificial intelligence.


Many people think that Insurance has long lagged behind the cutting-edge of tech innovation, but the industry’s embrace of artificial intelligence could soon change that perception.

AI will allow insurance companies to streamline the claims process by having technologies sift through the claims and automate personalized responses to simpler ones.

In addition, systems will soon be able to compile and analyze information about individuals available online and relate that information to broader trends in order to make customized premium recommendations based on that person’s habits.

For example, if someone has a healthy lifestyle and has held the same job for a long time, AI may be able to deduct that they are also a safe driver.

One of the biggest problems in the insurance industry is correctly analyzing the swaths of consumer data they have already collected. AI can take this data and break it down by individual to help insurers offer more accurate and affordable coverage.


In the healthcare industry, the benefits of AI mostly come from personalization and automation.

Regarding automation, AI will make physicians’ lives easier by completing their more menial tasks and making drug or treatment suggestions based on patient analysis.

AI for healthcare personalization will learn systems that know each patient’s unique medical situation, and provide information accordingly.

This type of individualized experience could help cut down on fatal drug interactions and other human-related errors that result in patient illness or death. It could also help improve a patient’s overall experience by making personalized tests and information more easily accessible.

According to the American Hospital Association, AI could also help track community health changes that might affect new admissions. For example, a spike in pollen in a certain neighborhood would allow hospitals to prepare for a potential increase in asthma patients.


Several large banking institutions have already enacted some sort of analytical AI.

JPMorgan Chase chopped a data mining process that would have taken 360,000 employee hours down to mere seconds with a system called Contract Intelligence — COIN.

COIN reads through legal documents and extracts the most important information. The system has helped the bank decrease the number of loan-servicing mistakes, which the COIN designers say were from the human error that eventually comes along with reading and interpreting 12,000 new wholesale contracts every year.

Outside of analytics, AI can also be used for customer service chatbots, such as Bank of America’s Erica.

Other uses for AI include completing basic tasks like external data requests, review and correction of fund transfers and fraud prevention measures.


AI has also started to seep into both the online and brick-and-mortar retail sectors.

Retail giants like Amazon and Walmart have long used recommendation systems and algorithms aimed at guessing consumers’ individual spending habits.

Ideally, if a consumer receives more targeted recommendations, retailers can expedite sales and improve the quality of the consumer’s experience.

Advanced AI systems are bringing dramatic changes to both online and in-person shopping experiences with technologies like gesture recognition that analyzes shoppers’ reaction to merchandise and virtual mirrors that allow customers to see themselves in multiple looks without actually trying on one piece of clothing.


Much like the retail industry, the entertainment industry is driven by customer engagement.

As such, many of its AI applications involve improving a customer’s experience through complex predictive software.

After moving away from a crowd-sourced system based on information gleaned from millions of Internet Movie Database ( users, Netflix now uses AI learning systems to track viewer habits and make content recommendations.

In addition, movie studios use AI to improve the quality of their computer animation by having it seek out and correct any visual aberrations that made it past animators.


Driverless cars have long been a distant dream in the auto and tech industry, and now it finally seems to be on the cusp of a mainstream breakout.

Companies like Tesla, Toyota, Google, Mercedes-Benz, BMW and Ford have all bet big on autonomous and semi-autonomous vehicles, and some have already rolled out or announced their consumer models.

AI allows for smarter automated systems aimed at improving the safety and efficiency of the driving experience.

AI in transportation goes past cars, though. Volkswagen and Aurora Innovation are working toward a goal of making mobility safe, easy and accessible for populations that may otherwise encounter obstacles such as children, elderly people, sick people, visually impaired people, and more.


The labor shortages currently affecting the farming industry make it an ideal candidate for AI intervention.

By streamlining control of agricultural robotics and automating many of these processes, AI could go a long way toward easing the pain of a reduced labor force.

Farmers could also take advantage of soil analysis and crop health analysis tools to improve their harvest. Using nothing but photos of crop fields from various sources like tractor cameras, satellites and drones, and ground-sensor data, Resson was able to help farmers understand how to identify and stop the spread of harmful crop diseases and pests.


While the construction and engineering industry have already started to utilize some AI-driven technologies, there is still a ton of unrealized potential.

Currently, project schedule optimizers, safety programs and maintenance solutions use machine learning systems to improve efficiency and catch problems early.

However, the future of construction AI means deeper predictive insights in the planning stages that can help reduce unforeseen issues that could increase production time and costs, and intelligent autonomous equipment that can speed up construction and reduce injury.


AI can help simplify the way factories work and enhance already robust automation systems.

Manufacturing plants are often finely-tuned machines, with humans and robots working hand-in-hand to complete the same task. If one facet of the process suddenly stops working or is having issues, then the whole system can grind to a halt.

With new learning software like the WIP Manager software or GE’s Brilliant Manufacturing software, problems in the production line can reach a manager or supervisor more quickly who, with detailed AI-assisted analyses available within seconds, can solve the issue and efficiently get the process back on track.


The key term driving the AI revolution in the marketing industry is personalization.

People respond more to ads that line up directly with their interests. As people spend more time on their devices, companies are generating tons of data about their habits and behaviors.

Google uses their Pixel smartphone as one way to gather more comprehensive user data. That information is then analyzed through a machine learning tool called Custom Algorithm, which ultimately allows for their ads to reach a more relevant audience.

This method is not unique to Google, though. Facebook and many other social media companies have long used AI to help understand the immense amount of data that is generated on their platform, and how to use it.

Corporate use of consumers’ personal data is what led to the General Data Protection Regulation (GDPR) being passed by the European Union. Enterprises have had to take many measures, but that does not need to stop the innovation process, in marketing or any other vertical.

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How to Bring AI into Your Enterprise

The end game of AI are shorter processes and easier experiences for the end users, but the software testing, evaluation and implementation required on the part of the enterprise can seem daunting.

However, it does not have to be that way.

Corporate innovation is becoming an industry in and of itself, and the complex process of managing, running and evaluating proof-of-concepts is now less complicated.

Learn how to optimize the way you incorporate AI into your company’s offering by downloading our free guide: How to Run a Proof-of-Concept in the 21st Century.

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