How to Get a PhD in AI

This guide overviews the steps and paths to earning a Ph.D. AI, from degree requirements to research topics.
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Updated on June 11, 2024
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  • A Ph.D. in AI will make you an authority in a rapidly evolving field.
  • It often takes 4-6 years and many steps to get a Ph.D. in AI.
  • Ph.D. students must balance coursework and research on their way to a degree.
  • The opportunity cost is high but can pay off with roles in academia and research.

Every day, something new surprises us about artificial intelligence, whether it's using deep learning models to make breakthroughs in molecular biology or inventing a new kind of selfie.

The exciting part? There's still so much to learn and explore in AI. If you have ideas and a strong passion for where to take things next, a Ph.D. in AI is a path you can consider taking.

It gives you the skills to use and shape AI to solve problems that may seem unsolvable, while opening up many high-paying AI positions in academia, research, and industry.

A friendly reminder:

Starting on the path to a Ph.D. may be intimidating, whether it's the years it takes to finish or the level of effort involved. But consider that over 52,250 people received their doctorates in 2021; if they can, so can you.

What is a Ph.D. in AI?

A Ph.D. in AI is the highest awarded degree in the field of artificial intelligence. It involves several years of study and research, culminating in a project, thesis, or dissertation of original academic research that expands our knowledge of AI.

The main focus of a Ph.D. in AI is research. Students spend about six years researching one topic. As a result, a Ph.D. can deliver substantial credibility. But it's not without risk.

Here are a few pros and cons of a Ph.D. in AI to consider:

Pros

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    Pro #1

    You can become an authority in one of the most important technologies of the present and future.
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    Pro #2

    You'll qualify for prestigious roles as a university professor, researcher, or scientist.
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    Pro #3

    You can use your research to make an impact as a leader working in policy or industry.

Cons

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    Con #1

    The opportunity cost is high, considering the time and effort.
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    Con #2

    Graduate school can be like a roller coaster, with tremendous highs and extreme lows.
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    Con #3

    Job competition for AI roles may increase if more people gravitate to the field.

How to Get a Ph.D. in AI

A Ph.D. in AI program takes between four to six years, during which you must start and finish many things. Degree requirements for a Ph.D. in AI vary from school to school, which doesn't make it easy to pin down exactly what you may need.

Here's a broad overview of the most common steps it takes to get a Ph.D. in AI, in loose chronological order:

  1. Earn a bachelor's or master's degree in a quantitative subject (i.e., artificial intelligence, physics, mathematics, computer science, or engineering).
  2. Receive high scores on standardized tests, such as the Graduate Record Examination (GRE), Test of English as a Foreign Language (TOEFL), and International English Language Testing System (IELTS).
  3. Apply to your graduate school, submitting test scores, letters of recommendation, purpose statements, and other related items.
  4. Complete two to three years of coursework, including core courses, electives, and research.
  5. Pass qualifying exams for Ph.D. candidacy, often in written and oral formats.
  6. Write and defend a dissertation of your independent and original academic research.

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AI Coursework and Research Topics

Ph.D. students are responsible for two main things: coursework and research. Most often, students take classes useful for their research that meet the program's criteria.

While courses can expand students' knowledge and aid their research, they also provide the needed technical skills to work in the field of AI. Examples of graduate-level courses in AI include:

  • Advanced Introduction to Machine Learning
  • Deductive Systems
  • Foundations of Informatics for Research and Practice
  • Advanced Data Analytics
  • Computational Neuroscience

Students have many options for what to research in AI. The topics vary from school to school but tend to cover similar ground. The following research areas at the University of Southern California are samples of what you might find at other institutions:

  • Machine Learning and Applications
  • Natural Language Processing
  • Knowledge Graphs
  • Scientific Data Analysis and Discovery
  • Multi-modal Understanding
  • Common Sense Representation and Reasoning
  • Computational Social Science
  • AI Fairness

Frequently Asked Questions About Getting a Ph.D. in AI

What are the admission requirements for a Ph.D. in AI?

Admission requirements for Ph.D. in AI programs vary. Many applications share similarities but may differ in what is and isn't required.

For example, admissions to the University of Georgia's Ph.D. in artificial intelligence program requires the following items:

  • Standardized test scores, including the GRE (assessing your quantitative and verbal skills).
  • Three letters of recommendation (UGA recommends university faculty and professional supervisors).
  • A sample of scholarly writing (such as a term paper, research report, journal article, published paper, or college paper).
  • A purpose statement.
  • A resume or curriculum vitae (CV).

Meanwhile, the machine learning Ph.D. at Carnegie Mellon University requires only GRE scores. However, CMU recommends including things like high test scores, research experience, and recommendation letters for applications to stand out.

How long does a Ph.D. in AI take?

The typical estimate for the length of a Ph.D. in AI program is 4-6 years. The actual length varies depending on a few factors, such as your background or the program design. You may finish quicker if you already have a master's degree or enroll in a streamlined doctoral program.

A typical student in Carnegie Mellon's machine learning Ph.D. takes five years to graduate. According to CMU's timeline, students tend to complete their coursework in their third year and start their thesis proposal in their fourth year.

Is a Ph.D. in AI Worth It?

Considering the time and effort it takes to get a Ph.D. in AI, it's a fair question. The answer is: it depends.

It may pay off if your goal is to work in academia or research. A Ph.D. in AI will allow you to become a professor at a research university or teaching school. Or, you can work in a research lab, getting involved in paths like technical safety or policy and strategy research.

If your goal is to become a millionaire (it probably isn't), then it's tough to say. There are some pretty cool success stories. For example, when Twitter paid $150 million to acquire an AI visual research company, each employee made over $10 million.

According to the Bureau of Labor Statistics (BLS), salaries in computer and information technology — including artificial intelligence — pay a median salary of $131,490 per year. The highest earners made more than $208,000.

It's worth noting that the BLS predicts more than 682,800 new computer and information technology jobs are coming in the next decade. Having a Ph.D. in AI will give you a considerable advantage compared to your competition, who often have master's degrees.

BestColleges.com is an advertising-supported site. Featured or trusted partner programs and all school search, finder, or match results are for schools that compensate us. This compensation does not influence our school rankings, resource guides, or other editorially-independent information published on this site.

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