The Top Applications of AI

Artificial Intelligence or AI has taken the world over by storm. Though the concept has existed hypothetically since many years, it has been brought to life in recent times. This is because of the advancements taking place in other areas like big data analytics and cloud computing. Traditional CPUs weren’t designed to handle the requirements of AI and its subset, machine learning. Today, however, we have Graphics Processing Units or GPUs, access to historical data sets through the cloud, and high computation power to handle big data. All these factors have accelerated the growth of AI, and we are able to see its initial potential in the form of autonomous driving, drones, chatbots, and voice assistants among others.

Artificial Intelligence is one of the trending careers these days, and there is high demand for skilled professionals. Compared to the software developer role, companies are paying higher salaries to AI/machine learning engineers. According to LinkedIn’s 2020 Emerging Jobs Report US, the hiring growth for AI and machine learning specialists grew 74% annually in the past four years (2016 to 2019). Machine learning, deep learning, natural language processing (NLP), TensorFlow, and Python programming are the top skills asked for such roles. The demand for AI specialists is higher in industries like computer software, consumer electronics, information technology and services, the internet, and higher education.

You will be witnessing a rewarding career if you are an AI specialist wannabe. You can explore online AI courses to build a strong foundation in this domain and become job-ready. But, if you aren’t familiar with the technology much, you should check out some of the fascinating applications of AI. Knowing about them may inspire you to dive into AI concepts and start a career in this promising field.

Here are some of the major applications of AI in various fields.

AI in customer service and experience

Ensuring customer satisfaction is the primary goal of all businesses. When customer service is supported by AI, you can imagine how efficient the process would be. Today, many firms are using chatbots, powered by machine learning algorithms and NLP capabilities, that can answer many of the queries and requests customers have. They do it faster than humans and at a comparatively low cost.

Recommendation engines used in eCommerce sites, OTT platforms, and more are also powered by machine learning. Based on user history and predictive analytics, they recommend the products that the customer would be most likely to purchase.

Financial Investing

Today, everyone seems to be looking for quick money-making ideas, and stock investing is one of their top options. There are expert advisors and relationship managers to help you buy the right sticks; they are not always reliable. Customers often feel dissatisfied and don’t get personalized investing suggestions. Today, there are some AI platforms that understand the investors and give them personalized suggestions based on their financial goals and risk appetite. Such platforms do not have a biased opinion and offer better suggestions than humans who have emotions and may be biased with a particular option.

Recruitment process

Gone are the days when a company had to dive through hundreds of resumes and conduct interviews for several individuals to hire the right candidate. Today, AI is even helping with the hiring process. AI-powered tools add a layer of talent intelligence to the recruiting process through which thousands of resumes can be screened automatically, thus reducing tedious manual effort.

In such applications, machine learning can learn how to shortlist the ideal candidate, conduct sentiment analysis on job descriptions to identify potentially biased language, and give better insights into the talent pool.

Efficient supply chains

Many studies have shown that AI and ML can deliver great value to supply chain and logistic operations. Supply chain managers can implement AI to make better decisions as it will allow for predicting unforeseen abnormalities, building up bottlenecks, and quantification of expected outcomes across different stages of scheduling. Machine learning algorithms can forecast what will be required when and the optimal time to move supplies.

AI can also help manufacturers with possible implications across various scenarios with regards to time, revenue, and cost. A cognitive AI-driven automated platform can also offer a single virtualized data layer to offer complete visibility of the entire supply value chain.

Brain-computer interfaces in healthcare

Healthcare is one of the sectors where AI can do wonders. Creating a direct interface between machine and human mind without the need for keyboards or monitors is a new area of research that has considerable potential for some patients. Brain-computer interfaces (BCIs) supported by AI can help in restoring a patient’s ability to speak, move, or communicate meaningfully when they have been affected by neurological diseases and trauma. It could also significantly improve the quality of life for patients who have suffered strokes, ALS, locked-in syndrome, and spinal cord injuries.

Apart from the ones mentioned above, AI is penetrating areas like game development, agriculture, banking, manufacturing, social media, marketing, aviation, and so on. In the coming years, you will undoubtedly witness some of the awe-striking applications of AI.