Artificial intelligence (AI) is a branch of computer science focused on making computers behave in human ways, such as rational thinking, perception and action. AI already exists in many different forms, from robots that perform repetitive tasks in factories, to computers that play chess, to the digital assistant on your smartphone. AI initiatives allow machines and software programs to use pre-determined algorithms to solve problems, learn, plan, identify patterns and react accordingly.

Many of us carry advanced AI technology in our pockets. Digital assistants, like Siri and Alexa, use natural language programming (NLP) to listen to our requests and follow instructions without our needing to know any type of computer language.

We also interact with AI in less obvious ways. The car you drive was built by robots that used AI to perform precise operations. That same car may have AI that optimizes your gas mileage or hits the brakes to prevent collisions. Chances are, you’re reading this webpage because AI directed you here when you used a search engine.

Machine Learning (ML) is a branch of artificial intelligence and one of the ways AI can be achieved. Where AI initiatives make it possible for a machine to mimic human behavior based on what it has been taught, ML models help machines to teach themselves. Instead of being pre-programmed with specific algorithms, computer scientists use ML to give machines the models necessary to absorb and process vast quantities of data, then use that data to create its own algorithms and draw its own conclusions.

• Entry-level (0-2 years of experience): Rs. 4-8 lakhs per annum
• Mid-level (2-5 years of experience): Rs. 8-15 lakhs per annum
• Experienced (5-10 years of experience): Rs. 15-30 lakhs per annum
• Senior-level (10+ years of experience): Rs. 30+ lakhs per annum

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Career Pros Details

1. Error-free Processing

The execution of tasks by humans is more prone to make errors. We often make mistakes while doing a specific task. This might be due to the variation of the intellectual ability of an individual. But, it is not the same case with AI-based machines. We program the machines for accomplishing a specific task. Thus, the accuracy depends on how well we design and program the machines to carry out the task.

If we compare AI-based machines to humans for executing a particular task, then Artificial Intelligence has proved itself to be more efficient than humans. The use of Artificial Intelligence in various fields helps reduce unnecessary errors and losses. Algorithms used for building AI-based models implement complicated mathematical constructs that help perform actions with greater efficiency and fewer errors. Thus, it helps solve complex real-world problems.

2. 24/7 Availability

An average worker can only invest in service for 7 to 8 hours per day. Humans need time to refresh themselves, and they need to maintain a work-life balance. They cannot work 24 hours a day.

Here, Artificial Intelligence helps provide 24/7 services to an organization. In another scenario, AI-based chatbots used by customer service applications can handle multiple queries at a time, round-the-clock. AI can provide services without any delay or lack of efficiency. Nowadays, every eCommerce application, e-learning website, healthcare sector, educational institute, etc. uses Artificial Intelligence for support chat. This helps in enhancing customer services.

3. Right Decision Making

One of the advantages of Artificial Intelligence is its ability to make the right decision. There are no emotions attached to the AI-based machines that help prevent hampering efficiency. The machines that are built using Artificial Intelligence are capable of making logical decisions as well. A human would examine a situation by considering many factors. These factors may influence the decision emotionally or practically. However, the machines give accurate results as they are programmed to make logical decisions. AI-powered machines use cognitive computing that helps them make practical decisions in real-time.

4. Digital Assistance

Another advantage of AI is digital assistance. AI-powered applications also provide digital assistance. Today, most organizations make use of digital assistants to perform automated tasks. This helps save human resources. Some digital assistants can program to make a website for us. The use of digital assistants has revolutionized the healthcare industry as well. Now, doctors can look after their patients from remote locations with the help of digital assistants that provide real-time data on patients.

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Career Cons Details

1. High Costs of Creation

The creation of machines empowered with Artificial Intelligence is very costly. For a large-scale project, the price might reach up to millions of dollars. Thus, for a small-scale business, it is not possible to implement AI. For companies with large revenues too, the cost of the development of an AI project may be felt high due to the features, functionalities, or scope with which it is designed. The cost of development also depends on the hardware and software the companies use. Moreover, to meet the demand of a highly changing world, the hardware and software should be regularly updated. AI-powered devices are built, employing complex codes, algorithms, software, and hardware. The maintenance of these components requires great effort and costs very high. However, in the future, the cost of developing machines using AI may reduce due to the invention of advanced tools that will help create them easily.

2. Increased Unemployment

In the not-so-distant future, the rapid advancement of artificial intelligence has brought about unprecedented levels of automation, leading to a profound impact on the global workforce. While AI has undoubtedly revolutionized various industries, there is an unmistakable human toll associated with its progress.

3. Lacking Creativity

Machines cannot become as creative as humans. Artificial Intelligence can provide functionalities to learn from data but cannot make the machines mimic the exact human brain and skills. The accuracy of the results from an AI-powered machine depends on the level of analytics used by the creator. Artificial Intelligence cannot invent anything. It can just perform the task it is programmed for and improve itself by experience.

4. Lacking Improvement

AI algorithms are designed in such a way that they allow machines to learn by themselves by exploring data. Then, the machines try to improve by learning. But, any redundancy in the data may cause failures in learning, and the machines may show unpredictable results. Then, the algorithms need to be readjusted for the new set of data or learned to adapt to exceptional conditions. There may be inconsistency in the results due to the inability to process bits of information. Also, due to the lack of improvement, AI-generated results may have inaccuracy and cause great losses.

• Programming language
Computers have developed a language called programming language, which helps them easily communicate with different systems and processes. Moreover, computer language also provides computer systems with a standardized medium of instruction to perform functions and activities.
AI professionals should be well-versed in different computer languages to carry out various roles efficiently. Some of the common programming languages used in AI applications are Python, R, and Java.

• Linear algebra and statistics
Data science and artificial intelligence systems are made of mathematical equations. Similarly, it requires basic statistical knowledge to decipher the data collected through these processes. So, aspirants planning to make a career in AI should know mathematical and statistical concepts like calculus, differential equations, linear algebra, matrix, complex numbers, linear regression, and numerical analysis.

• Signal processing techniques
Understanding signal processing techniques is imperative while operating different AI and data science applications. Moreover, it helps in improving the reliability and accuracy of digital communication. Therefore, AI professionals well-versed in signal processing techniques can achieve efficiency and productivity in digital communication.

• Neural network
Neural networks are built to replicate the biological neural network architecture of the human brain. Since AI professionals design neural networks, a basic understanding of the system is necessary. Moreover, it helps them instigate innovation and creativity in the existing neural network framework.