Applying to Arizona State University for a graduate program in artificial intelligence raises two closely linked questions. First, which ASU programs focus on AI, and second, what are the GRE requirements for those programs. This article summarizes the ASU programs and departments that admit students into AI-related tracks, explains how ASU and individual programs treat the GRE, lists typical academic and application expectations, and outlines what competitive applicants should prepare. Where ASU does not publish program-specific information, the article explains how to confirm current policies with the department or Graduate College.
Quick answer
Arizona State University offers multiple AI-related graduate pathways through its computer science and engineering schools. GRE policies are not uniform across all ASU AI programs. Some programs list the GRE as optional or not required, while others may request GRE scores for certain applicants or under specific circumstances. Prospective applicants should check the specific program webpage and contact the graduate coordinator for the most current GRE policy. If a program does not publish GRE expectations, treat the GRE as optional but useful when it strengthens an application.
Program and admissions overview
ASU houses AI-related graduate training primarily within its Fulton Schools of Engineering and the School of Computing and Augmented Intelligence, along with interdisciplinary centers and research labs. Relevant degree pathways include:
- Master of Science in Computer Science with AI-related specializations or elective tracks
- Master of Science in Artificial Intelligence or related MS degrees if offered by specific departments
- PhD programs in Computer Science, Informatics, Engineering, or other fields with AI research groups
- Professional or online master programs that include AI coursework
Each program differs in structure, emphasis, and admissions expectations. PhD programs emphasize research fit, publication potential, and the ability to work with faculty advisors. Master’s programs may focus more on coursework, practical skills, and technical background. Funding availability is generally greater for PhD students than for master’s students, but ASU does not publish universal funding guarantees for every AI program.
Current GRE policy
There is no single Arizona State University GRE rule that applies to all AI programs. GRE requirements vary by degree level, school, and program. Use the definitions below to interpret program language when you review a program page.
GRE terminology and what it means
- GRE Required, the program explicitly requires official GRE General Test scores for all applicants or for specific applicant groups.
- GRE Recommended, the program encourages applicants to submit GRE scores but does not make them mandatory.
- GRE Optional, applicants may submit scores if they choose. Omitting scores will not automatically disqualify an application.
- GRE Waived, the program explicitly waives the GRE for certain applicants or for a period, often citing the Graduate College or temporary policy adjustments.
- GRE Not Considered, the program states it does not review GRE scores as part of admissions decisions.
When checking an ASU AI program page, look for exact wording in the admissions requirements. If a program’s GRE policy is not stated, contact the graduate coordinator listed on the program page. Also verify whether the Graduate College at ASU posts any campus-wide guidance that affects program policies.
Academic requirements
Application components for AI-related graduate programs at ASU generally include standard materials, with specific expectations depending on degree level. The table below shows common application items and how programs typically treat them.
| Application item | Typical expectation for AI programs |
|---|---|
| Transcripts | Official transcripts from all postsecondary institutions are required. International transcripts often require an evaluation. Check the program for transcript evaluation providers they accept. |
| Letters of recommendation | Usually 2 to 3 letters. For PhD applicants, letters addressing research potential are especially important. |
| Statement of purpose | Required. PhD applicants should include research interests and potential faculty matches. Master’s applicants should describe technical background and goals. |
| Curriculum vitae or resume | Required or strongly encouraged. Include programming projects, research, publications, and relevant work experience. |
| GRE scores | Varies by program. See the program page for the current policy. |
| English proficiency | Required for most international applicants unless otherwise exempted. See the program for accepted tests and policies. |
Academic preparation typically expected of competitive AI applicants includes coursework in data structures, algorithms, discrete mathematics, probability and statistics, linear algebra, and programming experience in languages such as Python or C++. Research experience, internships in AI, or relevant industry projects strengthen applications, particularly for PhD admission.
Program-specific expectations
Because ASU offers AI training through multiple units, learn the program-specific expectations listed on the department page. Below are program elements applicants should check and consider.
Coursework versus research focus
- Master’s (coursework-focused) programs emphasize advanced AI and machine learning classes, practical projects, and optionally a capstone or thesis.
- Master’s (research-oriented) or MS with thesis require a research proposal and faculty supervision. Strong programming and mathematical background are expected.
- PhD programs require demonstrated research potential, evidence of independent academic work, and alignment with faculty research interests.
Faculty fit and research areas
Identify faculty working on topics such as machine learning, natural language processing, computer vision, robotics, reinforcement learning, fairness and ethics in AI, and AI systems. A well-targeted statement of purpose that names potential faculty advisors and explains how your background aligns with their work improves your candidacy for research programs.
Portfolio and code samples
Submitting links to GitHub repositories, published papers, technical blogs, or project demos can be valuable for applicants whose strengths are demonstrable through code or projects. Some programs explicitly invite portfolios, while others evaluate them informally when provided.
Competitiveness and applicant profile
Admissions decisions for ASU AI programs are made holistically. Expect the process to consider GPA, technical coursework, letters of recommendation, research or industry experience, statement of purpose, and sometimes GRE scores if requested. Use the following qualitative guidance when assessing competitiveness.
- PhD programs are typically highly competitive. Successful applicants demonstrate research experience, strong letters from research supervisors, and clear fit with faculty research areas.
- Research-focused master’s programs are competitive, especially when funding or assistantships are offered.
- Coursework or professional master’s programs are competitive, with admissions emphasizing technical readiness and practical experience.
If a program publishes typical student profiles, review that information. If no profile is published, do not infer averages or minimums. Instead, present your strongest evidence of preparedness and contact the program for guidance about competitiveness.
International applicant considerations
International applicants should pay attention to the following aspects when applying to ASU AI programs.
- English proficiency. Most programs require TOEFL, IELTS, or accepted alternatives unless you meet an exemption. Check the program for the accepted tests and required scores. ASU may list campus-level or program-level minimums.
- Transcript evaluation. International transcripts may require a course-by-course evaluation or submission of original documents with certified translations. Confirm acceptable evaluation services on the program page.
- Credential documentation for funding. If you apply for assistantships or fellowships, the department will indicate how to submit documents for funding consideration. Funding processes can vary by program and by degree level.
- Visa and immigration timing. Admissions offers, visa documents, and orientation schedules have set timelines. Starting the visa process early is wise, and the university international student office provides guidance on F-1 visa paperwork and financial documentation.
Frequently asked questions
Does Arizona State University require the GRE for AI programs?
There is no single answer for all AI programs at ASU. GRE policies vary by program and over time. Review the specific program’s admissions page and the Graduate College guidance. When the policy is unclear online, contact the program’s graduate coordinator to ask whether GRE scores are required, recommended, optional, or not considered for your application cycle.
Will submitting GRE scores help if my GPA or academic background is weak?
Possibly. If a program accepts GRE scores, a strong GRE can supplement an application that lacks coursework depth or a high GPA. However, programs evaluate applications holistically, so strengthen other components such as letters, a clear statement of purpose, projects, or research experience. Confirm whether the program will consider GRE scores before relying on them to offset other weaknesses.
Do PhD applicants have different GRE expectations than master’s applicants?
PhD programs place greater emphasis on research potential and faculty fit. Some PhD programs may be more likely to request GRE scores when they are available, while others rely primarily on research letters, publications, and academic preparation. Check each program’s PhD admissions page for specific directions.
How can I confirm the current GRE policy for my program?
Steps to confirm GRE policy:
- Visit the specific program page in ASU’s School of Computing and Augmented Intelligence, Fulton Schools, or the relevant department.
- Check the program admissions or frequently asked questions section for GRE language.
- Contact the listed graduate program coordinator or admissions email. Use a concise question referencing the application cycle and your applicant status.
- Check the ASU Graduate College policies pages for any campus-wide updates that affect GRE requirements.
Final thoughts
Arizona State University offers several pathways to study artificial intelligence, and admissions practices vary by program. GRE policies are not uniform and can change across application cycles. Prospective applicants should prioritize verifying the GRE requirement on the program page and by contacting the graduate coordinator. Emphasize academic preparation in core CS and math subjects, document programming and research experience, and prepare targeted materials that demonstrate fit with the program and faculty research. For international applicants, confirm English proficiency and transcript evaluation requirements early. Treat the GRE as one potential component that may strengthen an application when accepted by the program, but do not assume a fixed campus-wide rule without verification.
Arizona State University Graduate Admissions Resources
Looking for broader Arizona State University graduate admissions information? The following guide covers university-wide admission requirements, GRE policies, application materials, funding considerations, and international student requirements.
