Tech jobs have quite the reputation for high pay, with average salaries soaring into the six-figure range, even for mid-level positions. So, it should come as no surprise that most people who make a career change to tech in search of a bigger paycheck.
If you take a look at tech job salaries listed by the US Bureau of Labor Statistics (BLS), computer and information research scientists sit comfortably at the top, making over $126,000 a year. Many of these research scientists work on today's cutting-edge technologies utilizing artificial intelligence (AI) and machine learning (ML) tools.
Another perk of the field? AI jobs are not just for machine learning engineers and data scientists. You'll find job postings in marketing, sales, management, and project management, not to mention all the entry-level pathways in software development.
What can you really expect to make with an AI skill set? And how much does an advanced degree affect your average annual salary? In this article, we'll discuss:
Working in AI and ML might seem a bit niche to outsiders. In fact, it's anything but. The International Data Corporation (IDC) predicted in 2020 that global spending on AI technologies will double in just four years. With that growth comes a burgeoning AI job market. And that's just the beginning. The AI market is slated to expand over 1000 percent in between 2023 and 2030. That's not a typo.
The irony here is that many people feared that AI technology would replace human jobs—from factory workers to, well, online writers. And this concern is not unfounded. Many tech pros confirm that yes, robots will replace many of our current roles. But the resulting opportunities that arise should keep humans from having to do repetitive tedious tasks and allow us to focus on more creative and strategic work. Additionally, all the positions required to monitor, maintain, and further develop AI will only continue to grow as we discover new possibilities for this technology.
Experts across the tech world seem to make predictions every year about when AI will touch every aspect of our lives. Back in 2014, a Pew Research poll predicted that this would happen by 2025. Others believe that computers will learn as quickly as humans by 2050. No matter the prediction, there's little doubt that AI will permeate most industries soon.
As for current job opportunities, you have your pick from a long list, including:
With the help of an AI engineer, computers are identifying early signs of disease, prescribing necessary tests, and suggesting treatments much more quickly and accurately than humans. AI is also being used in healthcare with patient billing, communication among specialists, global health trend analytics.
Manufacturing still tops the charts when it comes to AI-related jobs. The industry has used automation for decades, helping with everything from warehouse organization to ensuring sustainable supply chain management.
You'll spot AI-related job titles across the financial field, including in cyber security, and machine learning algorithms. The latter are used "to detect fraud, automate trading activities, and provide financial advisory services to investors."
Students and job candidates utilize AI-powered online tools every day for advice on where to go to school and which career move to make next. Artificial intelligence engineers also have created teaching bots, such as language-learning apps and textbook generators. Some students are using AI for writing assignments and hoping they won't get caught. That's generated a new business: AI text detection.
Do a quick search for AI and machine learning jobs in your field and you'll notice something interesting. Many job titles and their descriptions are relatively interchangeable. Analytics India Magazine elaborated on this in a recent piece: "Many times, employers may voluntarily keep the titles more generic, given the multidisciplinary nature that involves the use of statistics, mathematics, software engineering, neural networks, analytics, and visualization, among others."
The AI field is still rapidly evolving; job titles will become more specific as time goes on. As for now, you'll likely see these roles in the highest-paying positions.
As ambiguous as some job titles can be, the roles and career paths themselves are highly specified once you’re in the field. You'll see this demonstrated both in an AI master's degree curriculum and job descriptions.
For example, some computer scientists specialize in computer vision or natural language processing. Others work as algorithm engineers. Like other engineering-focused fields, you need highly specific skills to ensure the product is a success.
Other options include marketing, business development, or project management. These professionals still need a background in computer science, but combine it with their business expertise.
If you take a look back at that salary listed by the BLS, you'll notice that it specifically applies to professionals who hold a master's degree. Graduate and doctorate degrees are not necessary for all AI and ML jobs. Unlocking leadership roles, however, is a another story.
Each year, more and more top universities offer a Master of Science in Computer Science (MSCS) or PhD in computer science with a specialty in AI or ML. These programs offer students—both online and in-person—the chance to build foundational knowledge and gain hands-on experience in some of the most complex AI realms.
An artificial intelligence master’s can take from two to five years. Many universities offer part-time, online, or hybrid programs for busy professionals. You also can find one-year graduate certificate programs. Note that this is not the same as earning an MS.
In such a highly technical and developing field, universities want to make sure each prospective student is on the same page when the cohort first meets. While students come from all different backgrounds and levels of experience, they likely have a bachelor's in a related field, experience with programming languages, and industry experience.
For example, Southern Methodist University requires a bachelor's in topics related to math, computer science, or the quantitative sciences. You'll also need at least two professional references, a personal statement, and a resume.
Other schools require prerequisite courses such as linear algebra, Python training, and several semesters of calculus.
Artificial intelligence programs typically combine theoretical topics on AI with hands-on study of technical applications. In most cases, the balance of these courses depends on two factors: your chosen concentration and whether you choose to write a thesis.
Steven Institute of Technology, for one, requires a mathematical foundation course, four core courses, three concentration-focused courses, and either two electives or one thesis project.
Universities home in on the many areas of AI and ML by encouraging students to choose a concentration. In some cases, you'll be asked to select a focus by name with set courses. In others, you can build a custom specialization around your elective courses.
Johns Hopkins, for example, asks new students simply to choose an applied track or a theoretical track for their core courses. Electives include topics like intelligent algorithms, cloud computing, robotics, and data visualization.
Finding the right program for you is dependent on your professional goals. You could opt for a school like Carnegie Mellon, with a famous research lab in which you could end up working on projects that impress prospective employers. You also can choose a program geared toward part-time, online students to continue your career during your studies. Here are a few national favorites.
Two years of full-time, in-person study is not always feasible—or even the best option—for every student and learning style. The following programs offer flexible online master's degrees in AI:
Questions or feedback? Email firstname.lastname@example.org