What Are Different Career Paths in Artificial Intelligence?

Artificial intelligence is growing both vertically and horizontally across many sectors and domains. In this article, we explore what AI is, which domains it has made inroads into, and some details on the artificial intelligence career paths for both hardened professionals with relevant experience and newbies who often look for career opportunities in artificial intelligence.

More and more businesses are trying to build artificial intelligence into their products to stand out in the marketplace. AI helps them make their products stand out and helps them streamline many processes critical to the product’s design, development, and production. That’s why artificial intelligence career paths are in demand nowadays.

What Is AI for Beginners?

From a beginner’s perspective, Artificial Intelligence is the ability of a system to replicate the capabilities of human intelligence. It is when machines are simulated to undergo cognitive behaviors like learning and decision making by training the systems. It is a recurring process of data input, statistical analyses, and pattern formation to understand the behavior and generate results. We use AI in the forms of Google search algorithms, recommendation systems, autonomous weapons, and even self-driven automobiles. 

AI-based systems are defined by two approaches: Reactive Machines and Limited memory AI

Artificial Intelligence is a revolutionary technology that utilizes the machine learning reactive models and the limited memory models based on AI. 

The reactive machine simply takes up the input and produces some output without performing any learning. These machines belong to the first stage of AI systems. Examples of such systems are static machine learning models. 

The limited memory models enforce the storage of previous data and learning capabilities which help in generating better predictions for the future. The limited memory model follows two approaches. 

1. A team continuously trains the model with new data.
2. Training and renewing the models automatically in the AI environment. 

Further, there are types of AI like Theory of Mind and Self Aware AI whose mysteries are still unsolved. These approaches of AI are expected to interact with human emotions and intervene with their thoughts.

Before we start discussing on the subject “Is artificial intelligence a good career?”, let’s look at the types of AI we generally deal with. AI generally falls under two broad categories, namely Narrow AI and Artificial General Intelligence.

Types of AI

We should first explore AI types to understand career opportunities in artificial intelligence. All the real, and hypothetical AI problems and solutions, basically fall into three categories:

• Artificial Narrow Intelligence (ANI)

• Artificial General Intelligence (AGI)

• Artificial Super Intelligence (ASI)

Artificial Narrow Intelligence/ Narrow AI

Narrow AI also termed as weak AI, is a target-oriented AI approach that is designed to carry out singular tasks like internet searches, biometric recognition, and self-driven cars. These systems are trained to perform dedicated tasks with human-like intelligence. They are programmed with narrow constraints thus, the name Weak AI.

Narrow AI can work on either a reactive model or a limited memory model depending upon the volume of data and the required output. These systems are designed to interact with their users in a customized and natural manner. Narrow AI has kept on developing using deep learning, machine learning, and Natural language processing (NLP) algorithms. Most of the problems fall under the Narrow AI category, opening endless career opportunities in artificial intelligence.

Narrow AI examples:

• Voice assistants like Siri, Alexa, Cortana
• Watson by IBM
• Email spam filters
• Social media content monitoring
• Personalized recommendation systems
• Image/ Speech/ Face recognition
• Chatbots

Artificial General Intelligence/ Deep AI /Strong AI

Artificial General Intelligence also termed Deep AI is an approach wherein the systems can replicate human intelligence by undergoing self-learning capabilities.

Strong AI systems can think, analyze and react to problems like a human does without human intervention. In order to succeed in implementing Deep AI systems, the systems must be fed with a full set of cognitive capabilities to make conscious machines. Researchers and scientists are trying hard to get into the Deep AI universe such that it should have only a positive impact on the universe.

AGI may utilize the theory of mind approach of AI that enables interaction and bifurcation of emotions, beliefs, and cognitive processes of various intellectual beings. The fictional I-Robots and The Terminator portrayed in the sci-fi stories can be tagged as an implementation of Strong AI systems. 

Artificial Super Intelligence

Artificial Super Intelligence is the theoretical AI algorithm that may completely understand and replicate human behavior and intelligence. These may be self-aware and self-sufficient that can surpass human capabilities. The impact of the ASI may have multiple consequences in both positive and negative quadrants making its implementation under strict investigation.

Industry Penetration of AI

Although AI is making inroads into all industries gradually, industries where AI is making a significant impact are,

• Healthcare
• Customer Service
• Airline industry
• Cybersecurity
• Education
• Marketing
• Retail and E-Commerce
• Financial Markets and Services

Related: 15 Real World Applications of Artificial Intelligence

Is Artificial Intelligence a Good Career?

Is Artificial Intelligence a good career? Yes, it is! Artificial intelligence has been an integral part of the industries from every sector. Its algorithms and emerging innovations help the business to excel by unfolding the possibilities. 

The fields like search engines, social media, education, geospatial analysis, healthcare, robotics, telecommunications, and many more have embarked on growth using AI capabilities. The emerging technology poses intriguing challenges to utilize the conventional algorithms in an agile way to ensure the success of the industry. 

The industries hire researchers and professionals that can apply machine learning, computer vision, and data analysis to the existing data to work out the overall growth. 

According to the insights, the market for Artificial intelligence will rise by over 1394.30 billion US dollars by the year 2029. This tremendous growth will push existing companies and startups to invest to discover potential growth in the sector. The reports predict a growth rate of at least 150% from 2020 with a CAGR of 20.1% during a decade [Source]. 

AI has tremendous opportunities but it lacks the professionals who are skilled enough to utilize it. It is a rewarding field that seeks never-ending learning procedures. The job roles are niche and require technical background along with hands-on experience. This section describes the prerequisites, skills, and career opportunities in artificial intelligence you can take up. 

Pre-requisites Skills for an AI job

Having a Bachelor’s or Master’s degree or any certification course in the IT and computer science, statistics, and data science fields can help to build a stronger cognitive foundation for the course. Although there are some specialized technical and nontechnical skills that can be essential to understand the AI algorithms and platforms.

Technical

• Programming languages– C++, R, Java, Lisp, Python, and Prolog are the programming languages that are used in learning AI fundamentals. Knowledge of classes and data structures helps in understanding the algorithms with ease. Python and R have gained more popularity due to their libraries, clear syntax, simplicity, and versatility. 
• Machine learning: Machine learning is a supervised learning algorithm that utilizes large datasets to enable decision-making and predictions from the patterns. ML is basically implemented using neural networks, which cluster the data based on pattern, image, and speech recognition.
• Natural Language Processing: A combination of computer science and linguistics to process and understand human languages. AI professionals will have to work on language, video, and audio processing including semantic and sentiment analysis.
• Data Science and Analytics: A repetitive process wherein the data is collected, manipulated, and drilled upon to extract useful insights from it. The analytics help in finding patterns necessary for supervised learning. AI professionals have to excel in the analytical approach toward data and numbers. 
• Database Management systems: Apache Cassandra, PostgreSQL, Couchbase, MLDB, and Microsoft SQL Server are the most used databases in machine learning and AI models.
• Applied mathematics and calculus: AI works on conventional techniques like linear regression, clustering, Bayesian modeling, random forest analysis, and logistic regression. AI professionals need to learn the procedures involved in the aforesaid techniques to use them in future AI algorithms.

Non-technical:

• Communication and Collaboration skills: The task of AI professionals is to portray the prospects of the fields to the stakeholders involved. The skilled professional will have to clearly identify the findings and convey the results to ensure success. In addition, Strong visualization skills may help in delivering uncovered insights and conveying them in alluring storytelling ways, to attain growth and outcomes. 

Upgrading the Skills

Intelligence is one’s ability to learn. In AI, learning and knowledge development is a never-ending learning process. The systems, as well as AI professionals, need to grow in the continually evolving aura of artificial intelligence.  Professionals can excel in AI careers by understanding the theoretical concepts and perfecting them in a real-world application. AI needs versatility and dynamism as a skill. AI is a unique crossover of the technology and knowledge of the field it is applied to. So, the professional must strive to get the fundamentals of both fields.

Artificial Intelligence Career Paths

Choosing an artificial intelligence career path is a win-win situation. AI jobs are niche in learning and earning too. Becoming an AI engineer is an ala-carte menu. One can customize the skill set according to the job role and personal capabilities. AI has a wide array of technologies, platforms, and algorithms to learn from. Different AI fields focus on perception, language, machine learning, knowledge building, decision making, and Human-AI interaction. 

Artificial Intelligence opens up vast possibilities for an aspirant to build their AI careers, but some of the major work roles to choose from are mentioned below.

India evolving with AI: Career Scope

The International Data Council forecasts that the AI software market in India will rise from USD 2767.5 million in 2020 to USD 6358.8 million in 2025 attaining a CAGR of 18.1 %. Combining AI, ML, and NLP to achieve machine-human Augmentation is estimated to rise by 60% by 2026.

Adoption of process mining controlling mechanism will hike by 30% in large enterprises to yield an additional profit of about 20%. AI will generate jobs in the healthcare, banking sector, financial services, marketing, retail, telecom, defense, and logistics.

Industries & AI

Artificial intelligence has marked its footsteps in almost every industrial sector. The business outlook has transformed dramatically with the use of machine learning, search personalization, and recommendations. This positive change has increased the productivity and efficacy of industries. Here are some major industries that look up for AI professionals.

• Education
• Transportation and logistics
• Healthcare and life science
• Agriculture
• Manufacturing and marketing
• Ecommerce and Retail 
• Defense
• Banking and Insurance
• Cyber security 

Step to take up an AI job

Starting with any one of the artificial intelligence career paths and landing a job is a comprehensive process of learning and developing the theoretical as well as practical AI models. Although AI provides a cluster of opportunities it lacks skilled professionals who could drill out the gems of the field. AI knowledge building can be taken as a gradual process starting from the basics of programming and database management to gaining expertise in algorithms of machine learning and AI skills. 

How to Switch Career to Artificial Intelligence

Before switching a career to Artificial Intelligence, you have to understand that it is a constantly evolving domain. You have to have that constant thirst for knowledge. The knowledge that you gain today might not be relevant 3-5 yrs down the line. So let’s break up the path for you into two streams, one for the people new to IT and the other for people with IT experience but in non-AI technologies.

Non-IT background

If you are coming in from a non-IT background, you may be coming in with a wealth of domain knowledge that AI can use to improve the system. However, you could also use your domain knowledge and new skills to give yourself the edge. Let’s list down the skills you should gain before or while on the switch over to AI.

• Firstly, gain enough skill in Python, the easiest programming language. Get the programming DNA right. You can start with simple coding exercises and scale up quickly in Python. To learn to program, you need to know a few concepts in computer science. For example, you could start writing algorithms for smaller programs, giving you a general understanding of ML algorithms.
• Learn about database management systems.
• For Machine Learning, Deep Learning, and Neural Networks, an understanding of mathematics are important. So pick up the required knowledge in mathematics. If you don’t plan to get your hands dirty with ML code, you can skip this one.
• Learn Probability, Basic Statistics, and Random Variables.
• Learn about Machine Learning Algorithms. What is the objective of Machine Learning? How is Machine Learning achieved? What are the packages and tools that assist in programming ML/Deep Learning/Natural Language Processing?

Each of the above requirements might require you to gain further related knowledge.

IT background

It would be safe to assume that you have some experience with programming languages and database management systems from an IT background.

• Gain programming experience in Python or R.
• Use Data Visualization packages in Python or R to draw meaningful visualizations. Then, learn how to weave your story around the visualizations.
• Gain knowledge in Machine Learning, Deep Learning, and Neural Networks.
• Brush up on Statistics-Probability, Combinatorics, Bayesian Statistics, and Descriptive Statistics.
• Try Machine Learning in Python or R. Learn about pandas, Scikit Learn, Seaborn, and the packages available in Python for data science and machine learning algorithms.

In Conclusion

Before starting into the field of AI, beginners often think about “Is artificial intelligence a good career or not?” but to harness the power of AI truly, you need to master the skills and be industry-ready to achieve unmatched targets. Established businesses and AI startups have largely invested in AI to increase business productivity. 

The incrementing data and need for data analytics open up wider opportunities to build artificial intelligence career paths. All you need is guidance to ensure success in the field. 

Integrated courses from AnalytixLabs like Business Analytics 360, Artificial Intelligence engineering, and Full stack applied AI are designed to help in conquering the AI prospects and help in securing a high-paying job in AI. You can also level up your skills in AI with a PG course.

FAQs

1. Is artificial intelligence in demand?

Yes, AI is a hot trend in the industry. AI has observed an inclination in the past 5 years and is still expected to attain its peak by 2030. AI’s ability to simplify complex tasks, and reduce human involvement to increase the productivity of the business makes it an indispensable part of the industries.  

2. What job will I get if I study artificial intelligence?

Artificial intelligence offers a wider array of job profiles from the beginner to the expert level. You can be an AI, ML developer, or Data scientist if you carve for high-end technical jobs. Or you can be a computer vision engineer, robotics engineer, or Business analyst depending upon your interests in the field. There is a great scope in the telecom and cyber security sectors if you master AI skills.

3. How do I start in any artificial intelligence career paths?

Planning, hard work, and execution are all you need to land up in the AI space. You need to understand the basics, pursue a degree, and get specialization in the area of interest from the available branches of artificial intelligence then, you are good to go. You can upgrade your technical and analytical skills by enrolling in the variety of courses available. 

4. Is artificial intelligence high paying?

AI is a niche field providing alluring salary packages at entry-level as well as experience levels. All you need is to be perfect in the skills you work on. The annual salary may be approximately 6 lakhs to 8 lakhs while those with mid-level and high experience may range between 15 lakhs to 50 lakhs. 

Have further questions? Do you have something to share? Post them in the comments section below, and we can help you out.

You may also like to read:

1. How Do Artificial Intelligence & Different Components of AI Work?

2. Top 60 Artificial Intelligence Interview Questions & Answers

3. What Is the Future of Data Science and Artificial Intelligence?

4. What Is Eligibility for Artificial Intelligence Course?