Applied Artificial Intelligence: The Next Frontier for Academic Programs

February 15, 2024

AI is poised to change every aspect of our lives, from creating images of our wannabe slimmer selves to automating processes and accelerating scientific research and development. PWC predicts that AI could contribute up to $15.7 trillion to the global economy by 2030, with almost half (45 percent) resulting from AI-driven product innovations and enhancements.

The impact of AI on the workforce is also expected to be profound. Could AI replace many of the jobs we know today? This is a genuine concern. But as with many new technologies, AI is also creating new jobs and changing how others perform.

The AI Talent Rush

As businesses and organizations expand their use of AI, the job market for AI talent is booming. Gray DI’s Job Postings Dashboard shows more than 84,000 postings for jobs requiring AI-related skills in 2023. The average advertised salary topped over $126k. These jobs span industries from information technology to retail, wholesale, and insurance. Job titles include Data Scientists, AI Managers, and AI Programmers.¹

Competition for workers with AI skills is tight. A recent survey found that nearly three out of four employers prioritizing hiring AI talent have difficulty finding qualified candidates.

With the demand for skilled AI professionals growing and current demand exceeding supply, higher education institutions can play a critical role in developing new talent and upskilling the current workforce with Applied Artificial Intelligence programs.

Applied AI Programs in Higher Education

Applied Artificial Intelligence programs could take shape in a few ways – programs specifically focused on teaching the fundamentals of creating artificial intelligence software and tools and programs that focus on creating and applying AI solutions to specific domains or disciplines. These programs are applicable at the undergraduate and graduate levels and have high potential within executive education.

Artificial intelligence Programs

Academic programs specifically focused on Artificial Intelligence are not new, but they have remained relatively small and few. This is starting to change. This past fall, total enrollment in AI programs jumped 33%. New student enrollment jumped by 64%.

¹ These jobs are only ones that list skills associated with artificial intelligence.

2 charts. Chart 1: Total enrollment by artificial intelligence programs Chart 2: New student enrollment in artificial intelligence programs

Fifty-six programs reported completions at the bachelor’s level or above in 2022, up from 37 programs in 2021. At least 19 new Artificial Intelligence programs were announced in 2023.

We should note that “artificial intelligence” itself is multi-faceted. Often, the solutions behind it – such as machine learning, computer vision, neural networks, or natural language processing – are incorporated into computer science and similar programs that are not specifically labeled “artificial intelligence”.

But just as Cybersecurity programs evolved as an offshoot of computer science and information technology programs, Artificial Intelligence programs will soon split out and grow quickly, to become large programs in their own right.

“Applied AI” Programs

Colleges and universities could launch interdisciplinary programs or AI specializations that fuse AI skills with domain-specific knowledge, preparing graduates for specialized roles in AI-driven sectors. These programs could leverage particular areas of expertise and excellence within the institution and be taught, at least in part, by existing faculty. They would equip students with theoretical understanding and practical application of AI solutions. The curriculum would cover core technical areas like machine learning, computer vision, and natural language processing, combined with deep domain knowledge of a particular field or functional area, such as Environmental Science, Finance, Marketing, or Human Resources.

Marketing and Business in the Age of AI

For example, marketing is an area where AI is exploding (and generating annoying emails). It is used across the sales and marketing funnel for content generation, advanced analytics, precision targeting, and increased personalization. Cornell University offers a Marketing AI certificate program for marketing professionals to teach how to leverage AI and incorporate it into their marketing strategies.

Business schools are also incorporating AI into their curriculums. Northwestern University’s AI-focused MBA program (MBAi) is jointly offered by their Business and Engineering schools.  The program is “specifically designed for leaders operating at the nexus of business and AI-driven technology.”

Northeastern University offers four concentrations within its Master of Professional Studies in Applied Machine Intelligence for Business Ventures, Finance, Healthcare, and Human Resources.

Materials Science and AI

Applied AI programs are now being used for scientific discovery. For example, materials science is poised for a groundbreaking transformation with the integration of AI. Discovering new materials has traditionally been a time-consuming and relatively inefficient process. Scientists combine elements from the periodic table or tweak existing structures in the hope of discovering new combinations and materials. Not only is this process time-consuming, but it also limits the potential for discoveries by working primarily with known structures.

Enter artificial intelligence – specifically, Google DeepMind’s GNoME AI model. GNoME can sift through massive data sets and potential combinations of materials much faster than humans or even previous AI systems. It screens and assesses the materials for stability and suitability for various applications and identifies the most promising candidates for experimentation. GNoME has already been used to predict structures for 2.2 million new materials, 700 of which have gone on to be created in labs for testing. These new materials could be used for anything from EV batteries to solar cells and microchips.

The University of Southern California offers a Master of Science in Materials Engineering -Machine Learning program. The program targets students with undergraduate degrees in Materials Science or Engineering and industry practitioners who want to apply machine learning to their R&D efforts. The program focuses on applying machine learning to materials design, discovery, and processing.

As higher education leaders, embracing the potential of AI is not just an option; it is a necessity. Academic programs that teach students how to build and apply AI solutions across varied academic disciplines and industry domains will equip graduates with the tools and skills needed to thrive in a world increasingly shaped by artificial intelligence.

Elaine Rowles


Elaine works with Gray’s education clients on strategic planning projects, program portfolio evaluations, program feasibility studies, price benchmarking, and research-intensive custom project work. She has performed in-depth analyses of existing programs and institutions, as well as assessed demand and employment opportunities for new and emerging programs.

About Gray DI

Gray DI provides data, software and facilitated processes that power higher-education decisions. Our data and AI insights inform program choices, optimize finances, and fuel growth in a challenging market – one data-informed decision at a time.

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