Artificial intelligence may be to business today what the computer was in the 90s. If you are not already engaging with this technology in your workplace, you likely will be soon. AI powers the chatbots that respond to customer inquiries and the recommendation engines that prompt Amazon impulse buys. HR departments are using artificial intelligence to enhance recruitment, training, onboarding and retention. Organizations across industries are looking for ways to implement AI, machine learning, Big Data and intelligent systems to boost productivity and profits. The International Data Corporation (IDC) predicts global spending on artificial intelligence technologies will surpass $204 billion by 2025.
In short, widespread, large-scale AI investment is changing how business gets done and creating new opportunities for enterprising professionals with the right skills and credentials. “Acceleration of AI adoption and proliferation of smart, intuitive ML/DL algorithms will spawn the creation of new industries and business segments and overall will trigger new opportunities for business monetization,” according to Ritu Jyoti, group vice president of Artificial Intelligence and Automation Research in IDC’s software market research and advisory practice.
The AI boom has had a quantifiable impact on hiring. The World Economic Forum put AI and machine learning specialists second on its list of roles with the highest demand, just after data analyst and data scientist. There are more than 62,000 listings on LinkedIn Jobs seeking applicants with artificial intelligence skills. And the number of AI jobs posted in the first quarter of 2021 was 45 percent higher than the previous quarter, according to the information technology trade group CompTIA.
Demand for AI experts is still more than double the supply, suggesting now is the time to learn how to leverage technologies like machine learning, deep learning and natural language processing. The challenge ambitious professionals face is that it’s not always clear how to launch an AI-enabled career. You may be wondering whether you really need a master’s in artificial intelligence or how to choose the best AI graduate program. However, keep in mind that a dedicated artificial intelligence program may be limiting if your goal is to apply AI in your industry. The best AI master’s program might actually be a Master of Science in Computer Science like SMU Lyle School of Engineering‘s Online Master of Science in Computer Science with Artificial Intelligence Specialization (MSCS-AI).
Why You Will Need a Master’s Degree to Work in Artificial Intelligence
Early computer programmers were scrappy and thrived outside of academia. They played with code, experimenting, testing and learning from each other as computing systems became more advanced and more accessible. Consequently, jobs in software, IT and software development have historically gone to professionals with aptitude and experience, whether or not they had undergraduate degrees. A bachelor’s degree could get an IT professional pretty far in the early 2000s. Today, a bachelor’s degree might land you an entry-level software engineering job.
We are still at the precipice of artificial intelligence research, but the field is already complex because AI, as a discipline, is so broad. It encompasses machine learning, deep learning, neural networks, computer vision and natural language processing – each of which is an entire field of study. Additionally, AI and machine learning are at the intersection of myriad industries. Intelligent systems and machine learning algorithms power business and technical operations in software development, manufacturing, retail, cyber security, finance and other fields. Data processing automation tools are transforming data science and business analytics, making it easier for organizations to derive insights from data.
Given the complexity of artificial intelligence, it should come as no surprise that specialists in this field often have graduate degrees. Demand for AI specialists with advanced education is high. According to Datamation, 26 percent of artificial intelligence job listings require or prefer that candidates have master’s degrees. Organizations look for AI interaction designers, machine learning specialists and AI engineers whose advanced degrees speak to a broad skillset grounded in computer science.
Credentialed AI specialists can assess the applications of artificial intelligence in their domains and leverage its power, now and in the future. Degree types vary. Some artificial intelligence professionals have concentrated artificial intelligence master’s degrees. Others have degrees in machine learning, data science or robotics. Still others pursue computer science master’s degrees like SMU’s MSCS-AI. Ultimately, degree names are less important than program content. The best graduate degree programs in this field confer cutting-edge AI skills useful across fields.
What Artificial Intelligence Master’s Programs Teach
The coursework in AI master’s programs varies from institution to institution. Most universities expect incoming students to already have a solid grasp of basic computer science concepts related to mathematics, programming, data structures, algorithms and operating systems. Working from that baseline, core courses in the artificial intelligence master’s curriculum teach students how to identify the problems that AI can address and how to solve them with technology. Some programs are customizable. At SMU Lyle, for example, students in the online MSCS-AI program choose from among a range of electives, including Advanced Data Mining, Machine Learning and Neural Networks, Machine Learning in Python, Mobile Applications for Sensing and Learning, and Natural Language Processing and Internet Applications.
The best computer science master’s programs do more than teach hard skills. Top full-time and part-time academic programs in the field of artificial intelligence are people-driven and offer plenty of networking opportunities, access to strong alumni networks and the support of invested faculty members. They also teach students how to apply the concepts covered in classes in their professional spheres.
Demand for AI skills is growing across industries. While companies like Amazon, NVIDIA and Microsoft hire the lion’s share of artificial intelligence degree holders, the market for AI talent in banking and finance, media, transportation and manufacturing is growing. The healthcare industry, in particular, is investing heavily in digital transformation, according to PwC’s annual Pulse Survey. Research firm Reports and Data predicts that the global healthcare AI market will be worth more than $61 billion by 2027.
The Rise of AI Master’s Degree Programs
Artificial intelligence master’s programs are still relatively new in higher education. From the time the term ‘artificial intelligence’ was coined in 1956 up until the early 2000s, experimentation in AI mostly took place in academic settings and research facilities. AI has since blossomed into its own field of study and a thriving career pathway. Computer science degrees with specializations, like SMU Lyle’s MSCS-AI, are built around artificial intelligence’s growing list of real-world applications.
The relative newness of artificial intelligence master’s degrees is one reason for the significant variation you’ll find between program format, curricula, prerequisites for admission and graduation requirements. Naming conventions at universities also vary widely and include Master of Business Administration in Artificial Intelligence, Master of Engineering in Artificial Intelligence, Master of Science in Data Science and AI and Master of Science in Artificial Intelligence and Machine Learning.
What distinguishes one program from another is often the target domain or industry. A program administered by a university’s business school might focus on the benefits of AI for business and be more holistic, centering on AI-enabled decision-making and automating business intelligence. In contrast, an artificial intelligence master’s program administered through an engineering school might be more technical, focusing on topics like systems development and computation. Given that, the difference between a Master of Science in Artificial Intelligence program and an AI-focused computer science program may be negligible.
You Don’t Have to Choose Between Artificial Intelligence and Computer Science
We know that artificial intelligence is here to stay, but there’s no way to predict the full scope of its utility. Researchers have only scratched the surface of what AI can do. Does that mean it’s too early to go all-in on AI? Maybe. In fewer than 10 years, a broader range of applications of machine learning and AI will have opened up, and the artificial intelligence skills you gained might feel out-of-date. At this stage of AI’s development, a graduate degree program grounded in computer science may provide more career flexibility and more competency longevity than a concentrated program. Studying computer science and AI, versus just artificial intelligence, will help you adapt to the unpredictable range of opportunities you’ll encounter in the future.
The extraordinary level of buzz surrounding the potential of technologies such as AI, data mining and computer vision has been enough to fuel investment and drive up salaries. More than 80 percent of businesses already use AI-powered technology, and across industries, artificial intelligence skills carry a wage premium of 11 percent. However, that buzz alone can’t support sustained growth. It will be professionals with broad skillsets grounded in computer science that help organizations take advantage of future opportunities associated with applications of AI we haven’t discovered yet.
Right now, artificial intelligence specialists have the option of staying siloed. Over the long term, professionals who specialize in AI but have a broader set of competencies will likely be the most competitive. By all indications, majoring in computer science and concentrating in AI is a smart move. As a Lyle School of Engineering student, you will gain a deeper understanding of computer science, transferable artificial intelligence skills and the critical thinking abilities necessary to implement AI technologies ethically in various systems. Because SMU Lyle’s MSCS-AI program isn’t focused on specific applications of artificial intelligence, you can go on to work in various roles in AI software development, AI system infrastructure design and AI application deployment, as well as in non-technical roles in which you will address business and operational challenges using AI and other technologies. This suggests the answer to the question ‘What master’s degree is best for artificial intelligence?’ isn’t a specific program at a specific university. Rather, the best AI master’s degree program is the one that helps you become an AI expert while also honing related skills that help you excel in your field.
It’s not too late to start studying AI. Apply now to pursue SMU’s 10-course online master’s in artificial intelligence, and in just about two years, you’ll have the skills to make your mark in this fast-growing field. Financial aid is available.