AI and Computer Science: Career Options and the Path Forward | GCU Blog

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Read time 7 minutes

Published On Apr 21, 2025

Written By

Brenda Decker

Senior Digital Content Specialist, Grand Canyon Education

College of Engineering and Technology

Tags

AI|Computer Programming|CS and IT|Information Technology|STEM in Focus

¹ Stryker, C. and Kavlakoglu, E. (2024). What Is AI? IBM. Retrieved Feb. 18, 2025.

²U.S. Bureau of Labor Statistics. (2024, Aug. 29). Computer and Information Research Scientists – Job Outlook. Occupational Outlook Handbook. Retrieved April 9, 2025.

³ Pecan. (2024, May 7). Decoding Artificial Intelligence Job Titles. Retrieved April 8, 2025.

⁴ Magill, K. (2023, July 6). Jobs of the Future, Now Hiring: AI Job Titles and What They Do. Dataspace. Retrieved April 8, 2025.

⁵ U.S. Bureau of Labor Statistics. (2024, Aug. 29). Computer Systems Analyst. Occupational Outlook Handbook. Retrieved Feb. 25, 2025.

⁶ U.S. Bureau of Labor Statistics. (2024, Aug. 29). Information Security Analyst. Occupational Outlook Handbook. Retrieved Feb. 25, 2025.

⁷Sweeten-Shults, L. (2023, Dec. 12). Virtual Reality Gym, Pirate Ship Projects a Treasure. GCU News. Retrieved Feb. 25, 2025.

⁸ Silicon Valley Innovation Center. (2024, May 23). Proliferation of AI Across Industries. Retrieved March 26, 2025.

⁹COVID-19 has adversely affected the global economy and data from 2020 to 2023 may be atypical compared to prior years. Accordingly, data shown is effective September 2024, which can be found here: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook, Information Security Analyst, retrieved Feb. 23, 2025.

¹⁰Linkedin. (2025, March 19). Will AI Be Writing 90% of Code in Six Months? Retrieved April 9, 2025.

Approved and verified accurate by the assistant dean of the College of Engineering and Technology on April 9, 2025.

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Will Computer Science Be Replaced by AI?

Dr. Artzi explains that while AI will play a significant role in automating many jobs across various industries, it is unlikely to fully replace computer science or programmers. He said, “In the next two to four years, AI may advance to the point where it can develop its own software, improving in ways we can't even imagine today.”

However, Dr. Artzi emphasizes that human involvement will remain essential. “AI may take on more tasks, but it’s up to us to ensure we maintain an edge over it by focusing on new careers that manage and guide AI.” This perspective highlights the ongoing need for human creativity and oversight in the development of AI.

For example, in Dr. Artzi's CST-320: Human-Computer Interaction and Communication course, students like Jack Utzerath and Hunter Jenkins developed a virtual reality gym as their end-of-semester project.⁷ The VR program uses an AI personal trainer to guide users through exercises and teach them about gym equipment, helping beginners build confidence and learn proper form.⁷ This project showcases how AI can enhance user experiences in educational and interactive environments within computer science.

Additionally, Dr. Artzi highlights recent GCU student projects that leveraged applied AI concepts, developed through hands-on internships, industry collaborations and innovative initiatives, such as:

Machine learning translator converting COBOL code to Java
Smart meeting cost estimator for Outlook and Teams
Conversational agent extracting info from large software documentation
Fall detection sensors for water pools
Smart image analysis
AI-driven learning paths for mental health counseling

AI developers do not stop when a program works correctly. They develop methods for continuously improving the performance and accuracy of AI applications.

Dr. Isac Artzi

“While AI may assist in programming, graduates must prove their creativity, innovation and problem-solving abilities to maintain the human edge in software development,” according to Dr. Artzi. For a deeper exploration of this topic, check out the blog post on whether AI will replace programmers.

AI Career Opportunities

New Career paths are being created every day. The most exciting catalyst is space exploration. This will require intelligent robots (driven by AI software) to pilot spaceships, build bases on other worlds, manage life support on spaceships and remote planets, etc.

Dr. Isac Artzi

AI is revolutionizing industries and with it comes a variety of specialized career paths. These roles span multiple sectors, offering opportunities for those with a background in both AI and CS. “My students are at an exciting pivotal point in the evolution of humanity, contributing to advancements as transformative as the invention of the steam engine, electricity, flight and nuclear power reactors,” said Dr. Artzi.

These specialized roles play a key part in advancing artificial intelligence, offering unique opportunities for professionals with a background in AI. Exploring a career in these areas could be a valuable option if you have a specific interest in AI. Here’s a look at emerging roles in the AI industry:^3,4

Machine learning engineer
Natural language processing (NLP) engineer
Language model trainers
Computer vision engineer
AI ethicist
AI product manager
Prompt engineers
API integration experts

Let’s take a closer look at some of the primary functions and work responsibilities within AI industries:

Optimize ML scheduling systems and monitor performance
Manage compute capacity for scalable AI operations
Improve inference scalability and model capabilities
Support ML system design and infrastructure
Refine encoding and tokenization processes
Develop and maintain model interaction APIs
Evaluate and benchmark AI model performance
Design and verify reinforcement learning algorithms
Shape and monitor AI model behavior
Boost performance and efficiency of AI systems

In addition to this scope of work, AI skills are needed in various industries, such as healthcare, finance, automotive and entertainment.^5,6 As AI continues to expand its capabilities, professionals who can bridge the gap between technology, business and ethics will be key players in shaping the future of AI.

The Role of Artificial Intelligence in Computer Science

Artificial intelligence refers to computer systems that can perform tasks usually done by human intelligence or use brute force to calculate all possible solutions to a problem by far superseding human analytical capabilities.¹ These tasks include decision-making, perception, language processing and pattern recognition. As a key subfield of computer science, AI leverages core CS principles, such as algorithms, data structures and programming, to develop systems that can simulate human cognition. AI also encompasses various specialized areas, including machine learning, natural language processing (NLP) and computer vision, all of which rely on computer science fundamentals.¹

Dr. Isac Artzi, associate professor in the College of Engineering and Technology at Grand Canyon University, explains, “AI is an extension of CS, with its core foundation rooted in linear algebra, such as vectors, matrices, linear transformations and statistics. These methods are translated into algorithms, a core component of CS and implemented through programming languages.”

AI and computer science are inextricably linked. AI applies CS principles to create intelligent machines capable of learning, reasoning and problem-solving.

Dr. Isac ArtziAssociate professor, College of Engineering and Technology

Areas such as machine learning, natural language processing (NLP), robotics and computer vision are examples of AI technologies built upon computer science’s foundational principles. As AI evolves, the need for experienced professionals who have years of industry experience and understand both the theoretical and practical aspects of CS and AI continues to grow faster than average.² This increasing complexity underscores the importance of a strong mathematical and programming foundation, which is essential for truly understanding and working in the field of AI.

Difference Between CS and AI

Computer science covers various topics, including algorithms, data structures, software engineering and systems design. It focuses on the design, optimization and development of computing systems. In contrast, AI adds complexity by aiming to replicate human cognitive functions, such as learning, reasoning and problem-solving through computational methods. While CS provides the foundational tools, AI pushes the boundaries of these tools to create systems capable of autonomous decision-making.

Dr. Artzi highlights two distinct tracks in AI: "theory, which advances slowly and steadily and implementation, which drives revolutionary change." He continues to state that theoretical advancements focus on the mathematical foundations of intelligent behavior, while implementation involves applying these theories to create practical AI technologies.

“At GCU, we teach students both the theory behind AI and its practical applications,” noted Dr. Artzi.

While CS and AI are closely related, AI goes beyond traditional CS by tackling the challenge of mimicking human intelligence. It requires deep integration of mathematics, programming and domain-specific expertise.