Machine learning and AI

AI and machine learning career paths, trends and job prospects

February 3, 2022 by Kimberly Doyle

Not that long ago, people worried artificial intelligence would eliminate human jobs. However, the fear of robots stealing our jobs has dissipated today as understanding grows of the opportunities AI and machine learning brings professionally and technologically.

Researchers at PwC found that, while AI will automate some jobs out of existence, “any job losses from automation are likely to be broadly offset in the long run by new jobs created as a result of the larger and wealthier economy made possible by these new technologies.” In the Future of Jobs Report 2020, the World Economic Forum estimates 85 million jobs will be displaced, yet AI will create 97 million new jobs by 2025.

This is good news for the economy in general — and even better for those looking to work in AI, machine learning or data science.

What is AI, and how is it used?

While more prevalent today, AI and machine learning are still considered emerging technologies for most organizations. They determine how to define and scale projects rooted in computers solving problems. But the technology is forecast to grow at a rapid pace. According to Gartner, the AI software market is expected to reach $62.5 billion in 2022, up more than 21% from 2021.

Organizations use AI and machine learning to capture and analyze information on everything from customer habits to process improvements. The technology is used to power customer service virtual assistants, build knowledge bases and even power autonomous vehicles, which Gartner says are the top three use cases. It’s also starting to play a significant role in cybersecurity to help security pros better understand threats and respond to risk.

As more and more devices get connected to networks, threat landscapes grow and so do hackers’ opportunities to steal your data. AI software and algorithms can analyze massive volumes of network traffic and recognize patterns that suggest malicious activity with a high degree of accuracy.

AI can also be used in malware detection and, more specifically, in the war against ransomware. Emmanuel Tsukerman, Infosec Skills author and professor of data science and machine learning, says AI, and more specifically, machine learning, can help detect and evade ransomware attacks with greater consistency than humans can. Think of it as the automatic production of rules using large amounts of data at scale.

“Let the data come up with the rules instead of trying to keep up by having a lot of people testing various rules,” Tusukerman says. With machine learning, you have a solution that can catch future attacks.

AI and machine learning careers

As organizations increasingly rely on AI and machine learning, more people are needed to build and maintain the projects and interpret the resulting data. Job prospects and salaries for professionals with these skills sets are bright. Generally, the Bureau of Labor Statistics projects a 15% increase in computer and information research jobs from 2019-2029, including positions like AI specialists and machine learning engineers. The median annual salary for this role reached $126,830 in 2020, potentially earning more in managerial roles.

More than 50,000 job openings are currently posted on Indeed for “Artificial Intelligence.” In 2021, the job board detailed the most in-demand jobs within AI and identified “data scientist” at the top of the list. These professionals work to glean insights from the large amounts of data they collect, and they are highly paid.

AI in cybersecurity

Jobs that specify AI for cybersecurity are fewer in number and therefore harder to find, but training in AI, machine learning and data proves helpful in landing any cybersecurity job. According to Emmanuel, those with machine learning in their background will be chosen over those who don’t because they are seen as someone who can immediately contribute to an area the organization is moving toward. “If you have machine learning or data science experience, you are an asset. It’s very useful to have these skills in addition to the practical usage of creating better solutions to cybersecurity problems.”

A strong computer science background is almost always preferred to land a career in AI cybersecurity. Numerous courses are available to round out your skills and zero in on specialty areas that interest you. Tsukerman has two learning paths in Infosec Skills, Cybersecurity Data Science and Machine Learning for Red Team Hackers. Both can help you better understand your options and learn the processes integral to AI work in cyber.

“I think there has always been a concern of getting automated out of our jobs,” Tsukerman says. “But I don’t see it as a problem. Machine learning is going to be more of a tool that enhances your ability, kind of like a computer, so you can do whatever a computer does. If you are filling out data, for example, you can do it on pen and paper, but on the computer, it’s faster.”

To learn more about Tsukerman’s courses and work in this growing field, watch the Cyber Work Podcast, How machine learning affects cybersecurity with Emmanuel Tsukerman.


Posted: February 3, 2022
Kimberly Doyle
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Kimberly Doyle is principal at Kimberly Communications. An award-winning corporate communicator and content strategist, she has focused on enterprise technology for more than a decade. Her consultancy has led her to support in-house corporate communications teams for numerous technology goals including cybersecurity, SaaS and cloud management, data exchange, enterprise pricing and business analytics.