AI technology has been advancing with a considerable pace, and it has resulted in the growth of
career opportunities in various domains. During recent years, there has been a huge
exponential growth for careers in artificial intelligence (AI) to meet the demands of digitally
transformed industries.
There are plenty of job opportunities in artificial intelligence, and on the other hand, there
is a lot of shortage of essential skills and talent for making a career in AI.
If we look at the statistics of demand for AI skills, then we will be able to explore that the
demand has doubled for the past three years, and the number of job postings has increased
by 119%. As per statistics, it is also expected that approximately 70% of Enterprises will be
implementing AI in the next 36 months.
The landscape of AI Careers
AI is gaining a significant amount of attraction due to the recent innovation that was
spread in the headlines. It is an excellent opportunity for individuals to make a career in AI
with the growing adoption of technology among different industries. The need for skilful
professionals in the AI industry is pacing at a tremendous rate.
As per surveys, it is expected that there will be close to 2.3 million job opportunities
coming up by 2021. It is estimated that more than 0.5 million new job opportunities are
going to come up in the entire world with the integration of AI in different fields. The use
of AI is prevailing in almost every industry, like AI bots to help doctors, smart digital light
meters, smart retail, smart cities to monitor the traffic, smart mirrors, etc. There is a huge
need for skilled and qualified AI Engineers in the upcoming years.
Subsets of AI
With the development of Artificial Engineering in different sectors, there have come up
subsets under the domain of AI. These subsets are helpful to all those who are looking
forward to specializing and making their career in AI.
Let us have a look at the 2 main subsets of AI.
1. Machine Learning
Machine Learning is the biggest application of AI that provides all the systems to learn and
improve over itself through experiences without any need of programming. The concept of
Machine Learning focuses towards developing computer programs that can learn for
themselves through the data.
Now, let us have a look at the further subsets of ML.
Supervised Learning
It is a learning model that is developed to make predictions based on the given inputs from labeled responses. The Supervised Learning algorithm makes use of a known input dataset along with the known responses for that particular dataset to learn the development of classification models. Unsupervised Learning
The unsupervised learning algorithm is used to make predictions from the datasets that consist of input data without any labelled responses. The most common method of unsupervised learning is cluster analysis that is used to explore hidden patterns in several groupings of data. Reinforcement Learning
Reinforcement Learning is the process of training ML models to make several sequences of decisions. This process is tested to make a decision in any particular situation in order to maximize the rewards.
It is a learning model that is developed to make predictions based on the given inputs from labeled responses. The Supervised Learning algorithm makes use of a known input dataset along with the known responses for that particular dataset to learn the development of classification models.
The unsupervised learning algorithm is used to make predictions from the datasets that consist of input data without any labelled responses. The most common method of unsupervised learning is cluster analysis that is used to explore hidden patterns in several groupings of data.
Reinforcement Learning is the process of training ML models to make several sequences of decisions. This process is tested to make a decision in any particular situation in order to maximize the rewards.
2. Deep Learning
The concept of Deep Learning is a specific subfield of machine learning. Deep Learning
has turned out to be the most popular approach towards developing AI-machines that
can perceive and understand the world. In the case of Deep Learning, the entire data is
processed through neural networks and the features are automatically learned to be
optimal for the task. The practical application of Deep Learning can be found by
applying it on text, speech, images, and videos to draw out conclusions through
decision making as humans.
Now, let us have a look at the further subsets of Deep Learning (DL).
Computer Vision
Computer Vision is another field of AI that trains the computers to interpret the visual world and understand it with the help of digital images and videos from cameras and deep learning models. Natural Language Processing (NLP) & Conversational AI
Conversational AI is basically the use of messaging apps, speech-based assistants and chatbots to automate communication and create personalized experiences. With the development of Conversational AI, machines will learn the way of responding in a manner that can be understood by the human audience. In the upcoming times, NLP will significantly change our way of interaction with machines.
Computer Vision is another field of AI that trains the computers to interpret the visual world and understand it with the help of digital images and videos from cameras and deep learning models.
Conversational AI is basically the use of messaging apps, speech-based assistants and chatbots to automate communication and create personalized experiences. With the development of Conversational AI, machines will learn the way of responding in a manner that can be understood by the human audience. In the upcoming times, NLP will significantly change our way of interaction with machines.
Industries Using AI
The most common question that is asked by individuals in any session related to AI is that
which companies are currently utilizing AI, and are hiring professionals for the same. We
are here with the answer to your question. AI is not used in a single industry, but it has
several applications across a number of industries.
The most famous use of AI among the general public is the self-driving car. Another
important use of AI can be seen in predictive maintenance where predictions are made for
the need for maintenance so that it can be done beforehand. This leads to saving a good
amount. AI is used in day-to-day industries like transportation for scheduling of trains as
well as helps the Uber drivers for navigating routes. Smart cities are including AI in their
cities to reduce crime, enhance safety, and make the city energy-efficient. There are
several applications of AI currently known to humans, and new ones are coming up all the
time.
AI is utilized in the following industries in different ways:
Retail
Autonomous Cars, Banking & Finance, Gaming, Healthcare, Ecommerce, Transportation, Smart City, Construction, Robotics, Logistics, Medicine, Agriculture, Manufacturing.
Some of the tycoon companies like Microsoft, Accenture, Amazon, and IBM are already
utilizing AI. Machine Learning and Artificial Intelligence are innovations in every industry.
As per research, it is believed that there is going to be tremendous growth in job
opportunities in the market with the increasing use of AI and ML among different
industries. It is not essential that you need to work for an MNC company if you want to get
involved with AI and ML as most of the sectors like manufacturing, energy, finance,
transportation, healthcare, and farming are adopting these technologies.
Job Profiles in the AI Industry
With the advancement of AI in different industries, several job opportunities are coming up
in the market. AI and ML are broad categories of learning, but the job profiles are pretty
much accurate. Some of the job profiles in the AI Industry are listed below.
AI Engineer, Machine Learning Engineer, Data Scientist, Computer vision software eng., Deep learning engineer, Video Analytics Engineer, Data Engineer, Data Analyst
Future of AI
Currently, we are certain regarding one thing that there is a shortage of skilled AI and ML
professionals.
People will be able to see drastic changes occurring in different industries due to the
inclusion of AI. The use of AI is going to bring a significant change in employment
opportunities in the entire world among different industries.
The demand for AI Engineers has been increasing exponentially in the world. Companies
are looking for skilled professionals who are thorough with these technologies and also
possess hands-on experience.
If you are interested in starting your career in the AI Industry, then you need to buckle-up
and get trained and certified. The sooner you are done with your training, the sooner you
can get placed in such an exciting job.
