A study conducted in 2020 revealed that over 48% of businesses use machine learning, deep learning, natural language processing, and more to improve their businesses. Another report by Cisco says that 83% of businesses believe using AI in their operations is a top priority.
Besides these, numerous other stats, facts, and trivia testify to how AI and ML will play a significant role across all industries. The technologies are considered one of the critical pillars of Web3, after blockchain and AR/VR.
But how exactly are these technologies being applied today? Here’s a list of the top 5 applications of AI and ML in 2022.
As the involvement of e-commerce in our daily lives increases, the platforms are trying to up their game on multiple fronts to make our experience as simple and hassle-free as possible. One of the focuses of such companies is product recommendation systems.
These systems require AI and ML to suggest products for people to buy. Their purpose can gauge the effectiveness of these systems. For product recommendations, the aim is for people to spend more on the platform. So ML will be leveraged to build recommendation systems with a higher conversion rate.
This is another aspect e-commerce platforms focus on. However, this feature is not available with just them but with any company that interacts with their customers. In an age where personalization and customization are being promoted, chatbots are the perfect place to use AI and ML.
People want answers and responses which are quick but also valuable for them. Some even expect the systems to respond as humans and in the tone they prefer. While the last part is on the extreme side of the spectrum, it will surely be pursued by companies in the future.
Malware, viruses, and other forms of cyberattacks are evolving at a rapid speed. As a result, cybercriminals are devising innovative strategies to which the most prominent companies and organizations do not have an answer.
This is because the systems are much less enhanced than the ones the hackers possess, and our skills and expertise need constant upgrades too. As a result, ML and AI can help us. Here’s how.
AI and ML can identify patterns, look at historical data to predict future patterns, and understand the overall system. It can do all this and more, and it can do it fast. Thus if we need to keep our IT infrastructures secure, AI and ML will need to work with them.
Companies have understood this and in a survey conducted, 25% of IT professionals said that leveraging AI and ML in cyber security is of the utmost importance.
Medical and Pharma companies are turning towards AI and ML to improve the efficiency and accuracy of their processes. For instance, today, if you go to a hospital with a problem, it would take time first to narrate your symptoms, get a bunch of tests done, and finally have the doctor diagnose your problem.
However, these tests tend to consume time depending upon the rarity and complexity of the disease and might not be affordable to people. But what if hospitals used AI and ML systems to study data sets to understand symptoms and accurately pinpoint the exact problem? These include predicting heart failure, identifying the exact stage of the disease, and more.
This is what is being worked upon by numerous pharma companies and healthcare professionals across the globe. The idea is to make the process simpler and cheaper for patients, giving them a better chance of getting better.
This is one of the most exciting applications of AI. While it is currently being leveraged mainly in the entertainment industry to understand audience responses, its applications are far-reaching.
Currently, the systems can be used for getting a sense of the overall sentiment of the audience towards a book that has just been released or a movie, game, etc. But if you realize what this system achieves, it can also be used in decision-making processes, especially in decentralized organizations where the platforms are community-driven.
Overall, these are the top 5 applications of AI and ML. However, there are others, such as facial recognition, image recognition, employee access control, etc.