By Dr. William Oliver Hedgepath | 08/04/2025
Computer science and information technology (IT) are two distinctly different fields. They may seem interchangeable since they both involve computers, but their core focus, intent, and methodologies are quite distinct.
What Is Computer Science?
Computer science refers to computer theory and how information is processed, stored, and communicated. It involves areas such as:
- Software development
- Computer programs
- Computational theory
- Artificial intelligence (AI)
- Programming languages
- Algorithms
- Machine learning
- Data structures
- Systems architecture
- Cybersecurity
- User experience design
Computer science professionals work to develop new technologies by advancing the science behind them. When it comes to building a self-driving car, for example, computer scientists are involved in creating the blueprint that indicates how that self-driving car works and why certain designs perform better.
What Is Information Technology?
In contrast to computer science, information technology is concerned with maintaining computer networks and implementing new technology. It focuses on the practical application of technology in organizational or everyday environments. Information technology is about maintaining computer systems, protecting infrastructure, and providing day-to-day tech support.
People who work in the IT field are concerned with system network administration and system management, as well as ensuring uninterrupted operations across various systems. They are also concerned with:
- Cybersecurity and network security
- Data protection
- Cyber education (training others how to recognize internal or external threats)
Many organizations and individuals use applications to store files on cloud servers, and IT administrators are responsible for protecting that information.
IT is the basis for controlling and managing the activities of the military, retail businesses, schools, and individuals.
Here’s a chart that summarizes the key distinctions and real-world overlaps between computer science and information technology.
| Domain | Computer Science | Information Technology |
|---|---|---|
Primary Focus | Theory, algorithms, machine learning, data science, software development, AI, software engineering | Infrastructure, systems engineering, network security, network infrastructure, database management, operating systems, computer networks, and technical support |
Goal | Invent and improve technologies through modeling, simulation, and code innovation | Implement, maintain, and secure technologies to support users and organizations |
Work Style | Abstract thinking, programming-heavy, mathematics, statistical modeling | Practical troubleshooting, integration, configuration, and hands-on system management |
Examples in Logistics | Designing machine learning models to optimize routing, predictive maintenance algorithms, and warehouse robotics simulation | Deploying cloud-based Enterprise Resource Planning (ERP) systems, managing Internet of Things (IoT) sensors in supply chains, and ensuring uptime of logistics dashboards |
Cybersecurity | Developing intrusion detection systems, cryptographic protocols, and anomaly detection algorithms | Configuring antivirus, firewall rules, identity access management, and responding to incidents |
Tools Used | Programming languages (Python, Java, C++), compilers, simulation environments, ML libraries (TensorFlow, PyTorch) | Database tools (SQL, NoSQL), enterprise software (SAP, Oracle), cloud platforms (AWS, Azure), and system monitoring tools |
Systems Thinking Application | Conceptual modeling of logistics networks, complexity analysis, and algorithmic optimization | Implementation of scalable systems, tech stack integration, and resilience planning in IT infrastructure |
Career Paths | Machine learning engineer, data engineer, software developer, AI researcher, computer scientist, or systems modeler | IT analyst, database administrator, web developer, network architect, information security analyst, cloud operations engineer |
Computer Science and Information Technology Are Integral to Our Daily Lives
Computer science and information technology are both vital parts of our daily lives. Without them, we wouldn’t have the computer systems, circuit boards, and microchips that run today’s self-driving vehicles, AI virtual assistants, smart devices, or chatbots.
We also would not have the robots used in manufacturing, inventory management, or household cleaning. The success of these technologies hinges not only on computing power, but also on the security and reliability of the networks that support them.
Predictions for the Future of Computer Science and Information Technology
The next few years should see significant advancements for both computer science and information technology. For example, the use of AI and machine learning will certainly continue to expand, especially in business operations that require advanced technology systems and more robust software solutions.
Also, the expanded use of neural network computer programs and computer systems will continue to lead to deeper learning in the field of computer science.
Similarly, the use of emerging technologies such as quantum computer technology is being explored by companies such as IBM®, Google® and Microsoft®. Quantum computer technology could potentially solve problems currently beyond the capabilities of today’s supercomputers.
Other fields that are continuing to see expansion include:
- Cybersecurity
- Blockchain technology
- Cloud computing
- Data engineering
- Computational systems
- Computer engineering
Understanding the distinction between computer science and information technology is essential for navigating today's career landscape. There are a variety of career paths available to individuals with a specialized knowledge and technical expertise in computer science or information technology, including jobs in:
- Project management
- Software development
- Data science
- Network administration/network management
- System administration
- Cloud computing
- Machine learning
- Cybersecurity
- Artificial intelligence
Jobs in these areas typically require a strategic mindset, practical skill sets, and a passion for the creation of technology solutions. Computer science professionals can align their paths according to their strengths in either hands-on technical application or theoretical design.
Also, career satisfaction in these areas often hinges on a blend of structured knowledge and adaptable tools as well as mastering everything from data structures to managing technological solutions. Whether you’re aspiring to develop cutting-edge applications or lead large-scale tech initiatives, gaining the right knowledge will equip you to thrive at the intersection of innovation and implementation.
Computer Science Degrees at AMU
For adult learners interested in studying computer science, American Military University (AMU) provides two degrees:
Courses in these bachelor's degree programs involve topics such as programming languages, operating systems, machine architecture and organization. Other topics include algorithms, data structures, information visualization, and designing for the web.
Students can choose from different concentrations (depending upon the program) so that they can gain the knowledge best suited to their career aspirations, whether they want to become computer scientists or IT professionals. The concentrations offered with these programs include artificial intelligence, cyber operations, and communications.
In addition, AMU also offers undergraduate certificates to supplement students’ knowledge. These undergraduate certificates include cybersecurity, digital forensics, enterprise web applications, and computer systems and networks.
For more information about AMU’s computer science programs, visit our information technology program page.
Note: Both programs have specific admission requirements.
IBM is a registered trademark of the International Business Machines Corporation.
Google is a registered trademark of Google, LLC.
Microsoft is a registered trademark of the Microsoft Corporation.
Dr. Oliver Hedgepeth is a full-time professor in the Dr. Wallace E. Boston School of Business. He teaches and publishes on artificial intelligence, reverse logistics, and transportation and logistics. Dr. Hedgepeth holds a bachelor’s degree in chemistry from Barton College, a master’s degree in engineering management from Old Dominion University, and a Ph.D. in engineering management from Old Dominion University.
Dr. Hedgepeth’s first career was with the Department of Defense (DoD) and the Defense Intelligence Agency (DIA), where he was a mathematician and an operations research systems analyst. He has 28 years of computer programming and computer systems experience.