What’s the first thing that comes to mind when you hear ‘artificial intelligence’? If you’re thinking of sci-fi television like Person of Interest or Mr. Robot, you probably have been taken in by the various myths surrounding the field. As an emerging field, seeing adoption only in the last decade or so, AI is still commonly misunderstood. So are artificial intelligence jobs. AI is a nascent industry. Even the world’s renowned experts are still figuring out. The world’s best companies are making mistakes: Apple’s new credit card, powered by an AI engine was investigated for being sexist; Amazon withdrew its AI-based recruiting tool for being biased; IBM Watson is known to have given unsafe recommendations for treating cancer. There are only a handful of professionals who have the expertise and experience to mentor the next generation of AI specialists.

Myth busting About Artificial Intelligence Jobs

All this and the evolving nature of artificial intelligence itself gives rise to myths and misconceptions among those outside the industry. To be able to gain the skills and build an artificial intelligence career, you need to have clarity. In this blog post, we’ll bust some myths and clarify misconceptions around artificial intelligence jobs.

Myth #1: Artificial intelligence and machine learning are the same

In its simplest definition, AI is making computers perform tasks that would typically need human intelligence. Machine learning is a subset of AI, which provides computer systems with data and algorithms through which they automatically learn and improve. AI is an umbrella term covering a wide range of areas, while ML is its specific application. You can read in detail about machine learning vs deep learning vs AI here.

Myth #2: Artificial intelligence jobs are only for PhDs

Narrow AI puts systems to do specific tasks, like most business applications today. General AI enables computers to apply learning in different contexts, through autonomous thinking and problem-solving. In the early stages, only PhDs did any kind of artificial intelligence jobs. But today, most narrow AI jobs are available to graduates and postgraduates in statistics, mathematics, computer science, economics and other related subjects. In fact, several jobs are willing to consider the practical experience in lieu of educational qualifications as well.

Myth #3: AI engineers don’t code

Not true. AI engineers are responsible for taking their ideas into production. So, they need to be able to code. If you look at any of the artificial intelligence jobs available presently, you’ll notice that all of them expect candidates to have programming skills. The most common programming language is Python, but knowing R, Java, or even Scala can be a significant advantage. 

Myth #4: Past experience is wasted while transitioning to an artificial intelligence career

This is the most harmful myth among experienced professionals. Someone with 5-10 years of experience in technology jobs like programming, testing, application development, DevOps etc. will have the foundation to work in high-tech AI jobs. Someone with similar experience in any vertical — banking, insurance, healthcare, e-commerce etc. will have the industry knowledge to apply AI to their use cases. Past experience can act as a differentiating asset for experienced professionals making the transition. Here is some career advice for making the shift seamlessly.

Myth #5: Individuals can’t do AI on their own; it needs a large team

This entirely depends on the scale of the project you’re taking on. Some large scale projects might need big teams like the ones at Google, Apple, NVidia and so on. There are also a number of projects that can be done by freelance AI professionals. Companies looking for one-off consulting, exploring AI strategy, building pilot projects etc. are always looking for qualified individuals to help them.

Myth #6: There are not enough artificial intelligence jobs in India

You’ll be surprised at how many AI jobs are vacant in India today. Nasscom conducted a survey which found that there will be 800,000 artificial intelligence and big data analytics jobs available by 2021, but there will be a demand-supply gap of 140,000. Fresh graduates aren’t gaining skills and experience quickly enough for the jobs that are opening up.

Myth #7: Freshers can’t get AI jobs

There are several indigenous startups in the artificial intelligence space coming up in India. While they will have highly qualified founders, chief data scientists and architects, they are looking for freshers and early-stage professionals to build the product from the ground up. This opens up exciting opportunities for those with AI skillsets either self-learned or through certifications. 

Artificial intelligence jobs are not just the most sought-after tech roles today, but they were also the best paid, with a great opportunity for growth. LinkedIn names the ‘artificial intelligence specialist’ as #2 in their 2020 emerging jobs report. It is the #1 emerging job in the US. It is also one of the most well-paying jobs across industries. Whether you’re a fresher or an experienced professional, AI opens doors to what can be the future of tech. Don’t let common misconceptions stop you from pursuing an AI career if you feel interested in it. For a structured AI-ML online learning program that includes 1:1 mentorship, hands-on experience through capstone projects, career coaching and a job guarantee, consider Springboard.