TOP 50 USE CASES OF ARTIFICIAL INTELLIGENCE IN DIVERSE SECTORS


liu, tempo Date: 2021-06-22 17:18:43
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Analytics Insight has listed the top 50 business use cases of artificial intelligence.


The digital sphere is raining technologies. The influence of artificial intelligence is taking center stage with every possible improvement. Technology is changing almost all industries including banking and finance, healthcare, automobile, telecommunication, manufacturing, defense and military, entertainment and media, education, etc. The sub-domains of Artificial Intelligence such as machine learning, natural language processing, data analytics, and image analytics are also rolling out profitable use cases in diverse sectors. Besides, artificial intelligence is serving the business purpose by leveraging end-to-end automation processes. Therefore, Analytics Insight has listed the top 50 business use cases of artificial intelligence in diverse sectors.

Artificial Intelligence in Healthcare

Artificial Intelligence (AI)


Predictive analytics to validate the need for surgery

Predictive analytics is a gift to healthcare. Sometimes, we come across patients who say they underwent an unnecessary surgery due to a lack of predictions on what was coming. Fortunately, artificial intelligence is changing the fate of such burdensome risks and avoidable surgeries. By using artificial intelligence and predictive analytics, healthcare professionals can identify if the patient needs surgery or not. The technology will assist doctors to evaluate whether the operation is actually necessary or if there is an alternative with far less risk involved.

Machine learning to diagnose infectious disease

Over the past one and a half years, medical experts have been whining that if the government knew the impact and influence of coronavirus, then they should’ve taken immediate action to control it. The repeated statement we hear is ‘no one was aware of Covid-19’s seriousness. Therefore, artificial intelligence and other disruptive technologies could be used to detect future pandemics. Machine learning and big data can help change the way we diagnose infectious diseases. Using a proprietary database and ML algorithms, doctors can run genetic testing to see if the disease is infectious or not.

Healthcare apps as medical assistants

Besides the actual medical services at hospitals and healthcare centers, artificial intelligence is helping patients in their daily care, be it at home or workspace. The tremendous amount of healthcare apps blooming on the App Store and Play Store, which could keep track of the patient’s health conditions. Powered by voice assistant technology, the healthcare applications indicate patients to take medications and check their health performance. They also send alerts and education materials to keep the patients on their heels all the time when it comes to taking care of their health.

AI-powered wearables track health conditions

Most of the time, follow-ups post a health condition are very mandatory. Unfortunately, we, humans, are very careless about keeping track of our health conditions. Some healthcare facilities offer such follow-ups or life coaching services, which are extremely expensive. However, AI-powered wearables can help patients in keeping track of their health issues. For example, when a patient wears an AI-powered watch, the device captures their real-time healthcare data and gives suggestions on required medication, exercise, activities, and even habits that could help them maintain their body.

Early detection of dementia

Dementia is seen as an expensive disease. Serious conditions of dementia cost up to US$500 billion worldwide for patients. However, with early predictions, the patients can escape the haunting expenses and save up to US$118,000. Fortunately, the early detection of dementia is turning out to be possible with artificial intelligence. A sensitive diagnostic tool can compare the way patients answer questions and validate their accuracy, speed, and image properties. The tool can further say if they are likely to get dementia or not.

Intelligent robots in surgery

Owing to the increasing global population and demand for doctors, robot surgeons are a must for the 21st century. Besides filling in for human surgeons, robot surgeons can actually do better in most cases. Surgery procedures require utmost patience and precision, and the skill of medical surgeons does not falter even when they operate without pause for hours and hours. Therefore, robotic assistants in surgeries can further help the surgeon achieve a new level of precision even for the most minute movement.

AI in drug discovery and production

Drug and vaccine discovery is a very lengthy process. Generally, it takes up to 10-12 years for a pharmaceutical company to discover a vaccine or a drug that is fully effective on people. However, the Covid-19 pandemic has accelerated the need for the rapid discovery of a vaccine. Pharmaceutical companies across the globe used artificial intelligence, especially, machine learning technology to detect the right base components that could work well in creating immunity against the virus. They also used data analytics to fast-track the trial process.

Converting doctors’ unstructured notes with NLP

Whether you agree or not, doctors’ notes are beyond recognition in most cases. However, they are very important for diagnostic and tracking purposes. They define a patient’s health condition, improvement or deteriorating situations, etc. Fortunately, natural language processing can unlock unstructured data directly from doctor’s notes, and convert it to structure data. This helps reduce errors and speed up the transfer of information.

Image analysis for medical diagnostics

However well trained and experience a physicist is, they are likely to end up missing something or the other in medical diagnostics. Fortunately, with the help of image analysis, doctors can get help from technology to analyze many of the medical images such as MRIs, X-rays, and CT scans. Besides, the technology can also provide feedback on what the human eyes miss out on.

Automating the administrative tasks

Healthcare institutions are a big hub for data. On a daily basis, many patients come in and go out. Even though many don’t need follow-ups, it is the responsibility of the healthcare workers to keep a record of patients’ medical data. Therefore, they use AI to automate administrative tasks. It is expected that by implying AI in automating administrative tasks, healthcare institutions can save up to US$18 billion. Machines can also help doctors and nurses save time on labor-dense works

Artificial Intelligence in Banking and Finance


NLP to detect the risk of insurance

Insurance companies rely highly on data. They check for the applicants’ background before processing the insurance procedures. Insurance companies sort through vast sets of data to identify high-risk cases and lower the risk. Using Natural language processing, insurance companies can analyze large volumes of text and identify key considerations affecting specific claims and actions.

AI in fraud detection

Banking and financial institutions are highly prone to fraudulent transactions. Unfortunately, human employees can’t keep track of all the transactions and mind malicious content or suspicious payments. But machine learning algorithms can analyze thousands of data points in real-time and flag suspicious or plain-right fraudulent transactions, stopping many fraudulent claims in the process.

Machine learning helps in investment

As technology evolves, banking and financial institutions are employing artificial intelligence and other disruptive technologies in their working system to do predictive tasks. One such predictive work is identifying the best investment plan or place. Machine learning-enabled technologies give advanced market insights allowing the fund managers to identify specific market changes much earlier as compared to the traditional investment models.

AI-powered apps provide financial advice

Budget management apps are mushrooming like never before in the digital world. These apps powered by artificial intelligence and machine learning technology offer customers the benefit of highly specialized and targeted financial advice and guidance. They allow customers to track their spending daily using these apps and also help them analyze the data to identify their spending patterns

Customization of services

In the digital era, financial institutions are using AI-powered mobile applications to track user behavior and provide valuable personalized suggestions to them. Besides, banks are leveraging the facility for consumers to do unlimited transactions from their smartphones. Banks are also tying up with financial transaction platforms and are rolling out services, offers, and insights based on users’ search patterns.

Artificial Intelligence in Automobile


AI Application in Enhancing Design

Artificial intelligence (AI), programmable shading, and real-time ray-tracing are heavily used in transforming the traditional design process of the product. The advanced AI has disrupted to form an advanced ecosystem that accelerates new design workflows and improves team collaborations. It is said that the future of designing cars lies in AI algorithms that can generate uncountable potential designs by defining product ideas and the problem.

AI Application in Manufacturing

Companies use AI-based robotics combined with a human workforce to execute manufacturing and supply chain tasks. AI-powered robotics in manufacturing has generated proven results in the proper handling of materials, test performances, and packing finished products. The use of artificial intelligence in the manufacturing of cars makes the manufacturing process swift as robots are given the responsibility to use their deep learning programs to determine which parts to pick and how to pick.

AI Application in Quality Control

AI is used for quality control which includes inspecting painted car bodies. Such sensitive detections often get prone to errors if done by humans. AI-powered machines can detect defects more acutely and accurately than humans. It is anticipated that quality inspection using machine learning (ML) will be a substitute for current optical crack detection.

AI in Car Dealership

AI is also employed by car dealers to enhance efficiency and effectiveness in delivering customer experience. All the advanced data techniques are impacting how consumers gather information about cars and make decisions about car purchases. This also allows dealers to understand and assess their customers better and customize their services accordingly.

AI Application in Automotive Insurance

The automotive industry is gradually resorting to a tech-driven culture by adopting and implementing AI. AI applications in insurance are rigorously advancing the processes of filing claims in cases of accidents or unfortunate circumstances. The unfortunate circumstances also entail cyber theft. The more connected are the car, driver, and passenger with each other, the greater the risk of cyber breaches and threats.

Artificial Intelligence in Manufacturing and Factories


Advanced-Data Analytics

The manufacturing sector has been successful in using AI for its advanced data analytics. Digital transformation has led to a supply of multiple sets of large-scale real-time data that are used for in-depth insights to predict current market trends. The combination of data with advanced analytics has provided tremendous help in risk management, data visualization, supply chain management also rapid decision-making process efficiently and effectively.

Predictive Maintenance

Predictive Maintenance or PdM leverages real-time data to identify core issues in the manufacturing process for taking necessary corrective actions promptly. It helps to analyze data by studying the difference in nature and frequency and alerts the system to reduce the potential risks of failure. Predictive Maintenance acts as a guide to the manufacturing industries in process optimization of top-notch quality products at a lower cost.

Robotic Process Automation

Robotic Process Automation or RPA software has the functionalities to manage the backend duties of the organization effectively without any human intervention. It helps the employees to focus on other duties to enhance productivity. RPA manages high-volume repetitious tasks with multiple complex calculations and records maintenance accurately. Implementing RPA software in several systems of the manufacturing industries can help to reduce time and improve workflow against competitors.

Robotics

The collaboration of smart robots with human employees in these manufacturing units and factories has successfully reduced the potential risks of human lives. Factories have started using robots in dangerous fields like mining where there is a high risk of losing the lives of employees with one mistake. Robots are known for their accuracy and better performance in risky areas with machine vision to precise mobility. In some fields, industrial robots require the necessary help from human employees to complete risky tasks efficiently.

Inventory Management

Integration of AI into the existing systems of factories has successfully achieved appropriate inventory management in this fast-paced world. Human employees are required to run a lot of issues simultaneously that can create mistakes. AI helps to maintain all kinds of inventory records to alert the employees at the right time to replenish the necessary supplies. AI algorithm generates timely alerts by predicting the delivery timings, delayed timings, and forecasting crises in the environment.

Artificial Intelligence in Education


Personalized Learning

AI can tailor lessons and learning strategies according to specific students. It serves students with different capabilities, considers the knowledge gaps, and provides personalized learning recommendations, increasing the efficiency of each student. The traditional approach is a one-size-fits-all method and it can cause serious knowledge and learning gaps. AI-based personalized education can cater to specific needs and identify the most efficient learning patterns to which different students respond.

Unburdening Administrative Staff

AI can simplify and automate repetitive and mundane administrative tasks otherwise done manually. Grading, continuous assessment, checking assignments, responding to queries are some tasks that AI can take up to unburden the teachers. This will enable teachers to get a 360-degree view of the students and their performance and also focus on other tasks that need high skills.

Increased Accessibility

Remote learning creates a lot of benefits compared to physical classroom training. With AI students can access the learning platform and lessons round the clock according to their needs. AI eliminates geographical boundaries in education and enables students to access it from wherever they want at any time. AI also opens up ways of interaction and accessibility for students with learning disabilities and those requiring special needs.

Smart Learning Content

A digitized curriculum powered by AI delivers smart learning content, which is more interactive, engaging, and simplified. Visualizations and simulations are other significant benefits of AI-driven digital learning. With AI, there are new learning materials generated like audios, videos, e-books, visualized charts, etc. AI also keeps the learning content updated and customized according to the needs of the different learning curves.

Virtual Assistants

AI-based learning systems will have digital AI tutors and virtual assistants like chatbots. Chatbots can provide accurate real-time communication to many students simultaneously. Personalized outreach and insightful feedbacks on curriculums are also enabled by virtual assistants.

Artificial Intelligence in Retail


Smart Assistant

Chatbots have provided you with automated responses for a long time. Now that Chatbots have been established, they can provide professional advice and continue to learn as you converse with them. It learns from the information and advances. Here as well, an AI’s ability to self-learn is considered the most useful.

Purchase Prognosis

Sites like Amazon are attempting to develop an algorithm that can anticipate precisely what you require and deliver the goods before you even place an order. The algorithm will be based on machine learning that has been created throughout the course of your visits.

Method for Pricing

It is one of the most effective AI applications in the retail industry. One of the most difficult challenges for retailers is product pricing. They should know the market price of the product before pricing it. Artificial intelligence applications for retail can help retailers determine the ideal price for a product that will entice customers. AI models in retail stores ensure profitability in terms of acceptable pricing without causing you to lose customers.

Improved Advertisement

After a few days of interacting with customers, AI can be used to determine where a business should place an ad. The advertisement is then placed in the exact location where it will capture the most customers. It prevents businesses from wasting money on marketing that will be ineffective.

Personalization

Retailers may use AI and machine learning to identify and evaluate their consumers’ purchasing habits. As a result, it enables merchants to provide customers with a more tailored in-store experience.

Artificial Intelligence in Defense and Military


Surveillance

US Pentagon has come up with project Maven that would incorporate AI algorithms along with computer vision to analyze the footage recorded from unknown serial vehicles and identify chances of hostile activity. It would save a lot of time for the human analysis to spend hours in the analysis of drone footage.

Logistics

F-35’s Autonomic Logistics Information System is used by Air Force to extract real-time sensor data that is embedded in the engines of the aircraft and all other onboard systems. It feeds the data into a predictive algorithm to determine when the technicians would require to inspect the aircraft or replace its parts. IBM’s Watson is an AI software that develops tailored maintenance schedules for the Stryker fleet by taking information from the 17 sensors installed on each vehicle.

Cybersecurity

The Defense Advanced Research Projects Agency (DARPA) organized a competition in 2016 called as Cyber Grand Challenge to find automatic defense systems that would automatically identify the flaws of defense-related software. The results of the competition demonstrated that the AI-based cyber tools have the ability to play offense and defense in a simultaneous manner.

Autonomous vehicle

DARPA completed the testing of the Anti-Submarine Warfare Continuous Trail Unmanned Vessel Prototype named as “Sea Hunter,” in 2018. It has been integrated into Surface Development Squadron 1. Sea Hunter is expected to help the Navy autonomously navigate the open seas. It would swap out the modular payloads and also coordinate missions with other unmanned vessels.

Lethal Autonomous Weapon Systems (LAWS)

It is a weapon system that uses sensor suits along with computer algorithms to automatically identify a target and then employ an onboard weapon system that would engage with and destroy the target without having any manual human control of the system. These systems still await a lot of development to be able to operate in a communication-denied environment.

Artificial Intelligence in Telecommunication


Virtual Assistance

One of the biggest contributions of artificial intelligence is conversational AI. It helps the telecom companies to control the massive customer support traffic, reducing call time wait for customers, maintaining and troubleshooting problems, and also helping in installation and set up of other projects. According to reports, virtual assistants can automate calls so efficiently that by 2022, telecom sectors are estimated to cut costs by US$ 8 billion, annually.

Fraud Detection

The telecommunications industry is a hotbed for fraudulent activities. Illegal access, cloning, theft, and fake profiles are some of the most common causes of fraud in telecom. Therefore, companies have started implementing AI fraud detectors, applications, and techniques that use machine learning algorithms to detect abnormal traffic and prevent fraudulent practices. The efficiency of such AI applications is high; providing a real-time response to illegal activities.

Predictive Analytics

AI-driven predictive analytics provides services by using data, algorithms, and machine learning techniques to predict upcoming results based on historical data. AI-driven applications enable companies to take preventive measures against impending losses by analyzing market patterns and trends. These tools strengthen strategic goals and create enhanced customer experiences. Network automation enables analysis of underlying problems and helps secure fast solutions.

Client Sentiment Analysis

Customer sentiment analysis is crucial for information processing. It helps the company understand the negative and the positive impact of a service or product. Since there has been a drastic change in the market due to digitalization, these tools help in analyzing the changed customer behavior, preferences, and patterns. These tools collect information from media platforms and enhance customer experience and the company’s performance.

Robotic process automation in Telecoms

Robotic process automation (RPA) is a business process automation tool based on AI. This automation technology helps telecom companies to manage back-office activities and long repetitive rules-based actions more efficiently. The labor-intensive and time-consuming activities like workforce management, data entry, and billing are processed without further complications and more swiftly.

Artificial Intelligence in Entertainment and Media


Content Personalization

Don’t you like it when popular OTT platforms like Netflix, Hulu, and Prime show you the kind of shows and movies that interest you? That’s the work of artificial intelligence. Content streaming sites have perfected their streaming recommendations according to different tastes and preferences for people of all locations. These companies use machine learning and AI algorithms to analyze user behavior, in terms of what genre of content users are mostly streaming. AI uses these data insights to create a highly personalized experience for every user.

Meta Data Tagging

In the media and entertainment industry, content is created on a daily basis, almost every minute. Making that content easily findable for viewers can be a daunting task for the employees. To carry out this task on a large scale, entertainment and media companies are using artificial intelligence-based video intelligence tools to analyze the content and identify the objects in the frame, and tag accordingly.

Decision Automation

Not just menial tasks, AI also has the capabilities to automate business decision-making. Leading organizations in the media and entertainment industry are using Natural Language Processing (NLP) and machine learning to generate performance reports from the raw analytics information shared by the authorized source. Without AI, large excel sheets filled with data can take up to weeks for analysis by the teams to generate meaningful insights.

Subtitle Creation

With vernacular media becoming mainstream, production firms are making sure that their content is suitable for audiences from various regions. To make foreign content comprehensible, providing accurate multilingual subtitles is crucial, especially for video streaming platforms. Manually writing subtitles for each movie and show is stressful and time-consuming. In addition, the cost of hiring employees who can understand and translate different languages is cost-invasive. As a solution to these challenges, the media and entertainment industry is using AI-powered technologies like NLP and natural language production.

Search Optimization

Having a vast amount of information online is good, but sometimes, searching for what you want can become tough. With AI, search results and recommendations are becoming easier and accurate. For example, rather than typing the name of a movie, you can simply upload an image on Google and get results based on the image. If you want to know the name of a song, instead of typing random lyrics, you can play the tune and the streaming app will identify the song for you.

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