It’s hard to go through a day without touching apps built in the early stages of artificial intelligence: from personalized content streams online, to the weather report, to the logistics that bring your Amazon order to your doorstep, AI is becoming a constant partner.
According to Bloomberg, this influence will only grow in the future. Citing a Zion Market Research study, Bloomberg reports that the global AI market, currently valued at $59.67 billion, will grow at a compound annual growth rate of 39.4% to $422.37 billion by 2028 — bigger than the 2022 GDPs of Austria, Ireland, and the UAE.
Image Source: ZionMarketResearch.com
This growth is attracting vast numbers of entrants into AI master’s programs, with many universities in turn expanding their AI capacities. According to Stanford’s AI Index, 73 leading universities reported increasing graduate offerings teaching practical AI skills by over 40% during the four academic years leading up to 2020, with faculty specializing in AI growing by almost 60% over the same timeframe. This growth is likely to continue over the next decade.
Entrants to these programs cite not only a booming job market but extremely high salaries as reasons for matriculating — but how much can you expect to earn with a master’s in artificial intelligence salary? In this article, we’lll break down expected compensation for a variety of advanced artificial intelligence jobs before providing some background on how you can start down the path to earning your own.
What salary can you expect to earn with a master’s in artificial intelligence?
According to PayScale, the average salary for someone holding a master’s degree in artificial intelligence is $102,848 — but the actual salary for AI professionals varies depending on several factors, including job title, specialization, location, and employer.
Based on PayScale’s data, the jobs with the highest paying AI salaries are:
Artificial intelligence engineers, who reportedly earn an average of $171,715, with top earners in the same profession earning upwards of $257,530 in annual salary.
Research scientists with AI skills, who reportedly earn an average base salary of $134,456.
Senior data scientists, who reportedly earn an average base salary of $117,438 and up to $150,000.
Machine learning engineers, who earn an average base salary of $106,055 and up to $150,000.
Factors that affect your salary when you have an MS in artificial intelligence include:
Skills: Having skills in subdisciplines like machine learning, robotics, and computer vision or with software like Python, Java, R, ApacheSpark, or Amazon Web Services can increase your competitiveness and salary potential from AI jobs.
Experience: AI specialists with more professional experience and seniority tend to attract more money in salaries than those just starting in the field.
Location: AI specialists working in locations like New York, Washington DC, San Jose, Seattle, and San Francisco on average earn higher salaries due to the higher cost of living and greater demand.
Specializations and additional certifications: Some industries, such as finance and government, require additional skills, subject matter expertise, or security clearances. Those with these extras will receive higher salaries in return.
Employer: Big tech companies competing for top artificial intelligence specialists offer higher salaries and attractive benefits for people with in-demand AI skills. Top employers include Google, Microsoft, and Facebook, among others.
We’ve covered the earning potential in various AI positions for those with master’s degrees in AI, as well as some factors that will impact this earning potential — but what exactly do you need to do to unlock it in the first place? In the next sections, we’ll explore just that: what a master’s in artificial intelligence entails, what kinds of people are good candidates for the degree, and what the day-to-day looks like for high-earning AI careers.
What’s a master’s in artificial intelligence?
A master’s in artificial intelligence is an advanced degree, usually offered by a computer science department, that’s intended to familiarize students with the landscape of artificial intelligence as well as give students the skills and other practical knowledge they need to undertake doctoral research or build and deploy artificial intelligence solutions in the industry.
Mathematics, especially statistics and linear algebra
Programming using languages like Python, R, and Java
Data pipeline skills such as data mining, data analytics, and data visualization
Potential knowledge areas:
Machine learning, including deep learning and neural networks
Natural language processing (NLP)
While you can expect most master’s programs in artificial intelligence to offer a curriculum more or less in line with the above, there are still significant differences in how programs design their curricula’s scope and structure.
At Northeastern’s Khoury College of Computer Sciences, for example, graduate students in the MS in artificial intelligence program first develop a comprehensive knowledge of artificial intelligence before choosing a specialization in robotics, machine learning, computer vision, intelligent interaction, or knowledge management. At Boston University, master's students have the opportunity to pursue independent projects, such as an MS thesis that they publicly defend in their final semester.
Northwestern University’s McCormick School of Engineering takes an interesting approach by offering dual tracks, one for those who plan to continue in artificial intelligence and one for those with advanced degrees who plan to take what they learn and return to their home discipline. In the former, MSAI, students will complete an internship with one of Northwestern’s industry partners or work on a project in Northwestern’s artificial intelligence laboratory before finishing off with a capstone project in their final semester. In the latter, MSAI+X, students will start with a programming and math bootcamp while foregoing these later components.
Who’s a master’s in artificial intelligence for?
Northwestern’s bootcamp requirement for students without a computer science or math background is instructive.
In general, applicants to artificial intelligence master’s programs are expected to have gotten their bachelor’s degrees in computer science, mathematics, or another technical field.
Though they don’t have a parallel track for students without a CS background, Northeastern similarly requires that incoming students have a strong background in computer science and mathematics. This background can be demonstrated by passing two placement exams on the fundamentals of computer science and statistics, probability, and linear algebra, respectively, or acquired before beginning study through the completion of two introductory courses.
Philadelphia’s Drexel University follows suit, requiring that students enter their Master’s in AI and Machine Learning program with a four-year bachelor’s degree or master’s degree in computer science, software engineering, or a related stem field with relevant work experience.