Ashley Little | Do Supply, Inc.

While artificial intelligence may seem like a science fiction dream of the future for highly technical industries, it has proven to be relevant in today’s era and is reshaping a broad range of industries. From finance to healthcare and transportation to supply chain, AI is increasingly playing a critical role.

The advancements in machine learning and AI over the last 10-15 years have helped move technologies from doing mundane rudimentary tasks to performing tasks that require a significant amount of creativity and intelligence. AI technology has faced up to difficult challenges, beating humans in reading comprehension tests and even sophisticated games like chess, proving that AI has a great potential to disrupt many industries.  In the same way that electricity transformed industries, products, and societies many decades ago, so too will artificial intelligence impact and improve every aspect of human life.

The future of AI is bright, and as more companies and institutions begin to invest in the technology we will see an exponential surge in adoption and application of AI. Here are some key areas and industries that AI is already transforming:

Health Care

The United States health care system is indubitably inefficient for more than one reason. Millions of dollars are lost every year due to misdiagnoses and incorrect treatments. Additionally, the health care industry generates an immense amount of data every year, contributing to as much as 30% of all the world’s stored data. This data could provide physicians and researchers with critical information to improve patients’ health, but most of it exists in silos, making it difficult and nearly impossible to analyze and utilize.

Machine learning and artificial intelligence are changing the ways in which this data can be processed. AI algorithms have the capabilities to sort through a large amount of data very quickly and accurately, processing far more than any human would be capable of going through. AI technologies can collect, store, organize, and mine through medical records instantaneously, revolutionizing the data management system. The results generated can help medical professionals improve treatments and diagnoses by utilizing the information rather than wasting it.

The application of AI in healthcare will not stop here – it will continue to grow. In the future, AI will be able to predict ailments before they occur and design treatment plans, further improving quality of care for patients.

Insurance

The insurance industry is another that processes masses of data each day as hundreds of claims are filed. To process the colossal amount of information sent by consumers, insurers are turning to AI to enhance the claim process and to make it easier for recipients to receive the benefits they deserve. Some minor claims are processed by AI without even requiring human intervention, which helps improve customer experience and reduce overhead costs.

Implementing AI processes in the industry can help to prevent some of the most costly elements in operations. Insurance companies in the United States and around the world lose billions of dollars every year to fraudulent claims. AI can detect anomalies in the claim process and flag them for human inspection. This reduces the likelihood of fraud and allows insurers to take swift actions to stop fraudulent claims before they occur.

The future implementations of AI in the insurance industry have many possibilities. One of the most beneficial uses for the industry is the use of chatbots, automated messaging services that can process concerns and provide personalized customer service immediately. Customers will be highly satisfied to be able to have quick, personalized communication with their insurance provider.

Automotive

In the distant past, autonomous cars were considered unviable. Regulation, technological impediments, and ethics slowed down the pace of growth and adoption in the early years of its discussion. The applications of AI and machine learning to driverless cars in the last few years have brought about a much-needed change to considering the viability of autonomous cars, drastically accelerating the pace of growth in the automotive industry.

With the implementation of AI algorithms, self-driving cars can react to events and driving conditions similarly to, or even better than, the way humans do. Autonomous cars by Waymo (a subsidiary of Google’s parent company, Alphabet Inc.) utilize high-powered lasers, which allow the cars to generate 3D maps of their surroundings. The generated maps are then combined with the maps of the world to create systems that allow the cars to drive themselves. Even ride-sharing platforms like Uber are considering adding self-driving vehicles to their fleet to help move their business to the next level. The future of seeing autonomous cars in every driveway may not be as far away as we once thought it was.

Supply Chain

Crucial time and resources are lost in supply chain every day. Labor and time-intensive tasks such as packing, shipping, and inventory management require a lot of coordination and manpower, which affects prices and overhead costs. That’s why marketers and retailers are increasingly utilizing AI, machine learning, and analytics for inventory and merchandise monitoring. The data and information collected help determine the areas that need improvement.

Machine learning could be vital in optimizing the supply chain decision-making process. Incorporating machine learning in the supply chain planning can help to manage inventory more efficiently. Business owners could use intelligent algorithms to assist in monitoring supply and demand according to the delivery of goods. An even further advancement we may see in the future is the use of autonomous vehicles for shipping. These vehicles not only have the ability to drive themselves, but also can monitor logistics for deliveries to enhance productivity and profits.

Author Profile
Ashley Little is from Do Supply, Inc., an industrial electronics supplier based in Cary, NC. She writes about robotics, machine learning, and the future of automation for industries.