Edited By Christine Skopec
Review & Contribution By Kira McDonald
A Ph.D. in Artificial Intelligence offers a pathway to cutting-edge research and innovation. You can tackle complex challenges, shape technology’s future, and make an impact.
The upcoming “industrial revolution” is forecasted to be powered by artificial intelligence and intelligent systems. As a society that increasingly relies on advancing technology and automated processes, there’s a growing global demand for AI professionals. Consequently, many students are pursuing research in AI. Opting for an online Ph.D. in artificial intelligence provides a comprehensive understanding of the field, enabling individuals to contribute to cutting-edge technology and gain valuable technical knowledge. Through Ph.D. programs, aspiring researchers can conduct innovative research, expanding their expertise in theoretical and applied aspects of artificial intelligence. It opens doors to diverse career opportunities in academia, research institutions, and industry, where they can take on roles as AI researchers, professors, or data scientists. With the potential to address pressing societal challenges and drive technological advancements, Ph.D. holders in AI play crucial roles in shaping the future landscape of technology and its societal impact. Pursuing a Ph.D. in Artificial Intelligence offers intellectual fulfillment and empowers individuals to make significant and lasting contributions to the dynamic field of AI innovation and application.
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National University, headquartered in San Diego, California, was founded in 1971 to provide educational opportunities for adult learners and working professionals. It offers over 190 degree programs, including bachelor’s, master’s, and doctoral degrees, with flexible online and on-campus courses. Serving around 40,000 students and over 240,000 alumni, the university is recognized for its support of U.S. military members. Accredited by the WASC Senior College and University Commission (WSCUC), National University is committed to accessible and transformative higher education.
Find the Best Ph.D. in Artificial Intelligence Programs
Numerous colleges and universities offer Ph.D. artificial intelligence programs. But to find the best ones, students must carry out their fair share of research. An institution’s reputation, faculty qualifications, infrastructure, accreditation status, and program structure determine how good it is. For a doctorate program, students must also ensure the university is conducive to research. Based on these and other criteria, here are some of the best online Ph.D. artificial intelligence programs to choose from:
| Univ | Address | Tuition | Grad Rate |
| Carnegie Mellon University | 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213 | $48,496 | 92% |
Universities and programs are ranked by various factors, such as affordability, curriculum and coursework, reputation and availability, program length, statistics, the potential of employment, and return on investment for the students. For a more in-depth analysis, please read about our rankings methodology page.
What to Expect from a Ph.D. in Artificial Intelligence Program
A Ph.D. in Artificial Intelligence entails rigorous coursework, research, and preparation for academic careers, research institutions, industry, and government. Typically spanning 60-90 credits, the program covers advanced topics such as machine learning, natural language processing, and robotics. An online Ph.D. in artificial intelligence teaches students the process of learning by doing. It allows a lot of research and practical problem-solving. This doctoral degree will cover aspects of artificial intelligence, including human-AI interaction, AI for enterprise intelligence, AI design and development, and efficient AI solutions and applications. They engage in original research, working closely with faculty advisors to develop and execute research projects culminating in a doctoral dissertation. Upon completion, graduates are equipped for roles as AI researchers, university professors, data scientists, AI engineers, consultants, or leaders in AI-driven startups. The program offers a comprehensive pathway for individuals seeking expertise and leadership in this dynamic and rapidly evolving field.
Program Structure, Coursework, and Dissertation
AI Ph.D. programs largely comprise core courses, electives, and a dissertation. This program is interdisciplinary, trains Ph.D. students in the core topics of artificial intelligence, and offers a wide range of electives that offer an opportunity to specialize in various sub-areas of AI. During the program, they conduct independent research and are often required to undertake teaching or research assistantships. The nature of programs can vary because of the various study areas students can explore within the artificial intelligence sector. Some Ph.D. research programs are computational in nature and heavily rely on lab work, coding, and math. For instance, other research projects may involve questionnaires with a people-facing focus to determine how the public feels about the proposed legislation.
A Ph.D. in Artificial Intelligence comprises several distinct components, each crucial to successfully completing the program:
I. Coursework
Ph.D. candidates begin their journey by completing advanced coursework in Artificial Intelligence. These courses cover topics such as machine learning, deep learning, computer vision, natural language processing, robotics, and AI of ethics. The coursework gives students a solid foundation in AI’s theoretical and practical aspects.
Here are a few examples:
Deductive Systems
This course includes symbolic-mathematical logic and examining the propositional calculi, mainly focusing on problems in formalizing logic and mathematics. Students learn to construct semantic proofs, construct derivations in a natural deduction system, symbolize complex sentences of English using predicate logic with identity, and construct proofs of fundamental semantic meta theorems for models of predicate logic with identity.
Data Mining
In this course, students will be introduced to data mining and its related areas, teaching them to apply these to problem-solving. The course caters to preparing for machine learning and data mining research and science, bioinformatics, and engineering learners looking to apply data mining tools to solve problems.
Machine Learning
This course expounds on the art of using a computer to solve computational issues without using specific software, known as machine learning (ML). To tackle real-world problems, students will rigorously apply machine-learning approaches to real-world data. The course also covers the fundamental ideas behind several machine learning techniques, including anomaly detection, deep learning, and ensemble learning with a neural network, etc., will be covered in this course.
Artificial Intelligence
In this course, students are familiarized with standard blind and heuristic search techniques used in AI applications and their computational complexity. They are also taught the standard ways of knowledge representation used in AI. The course also covers common philosophical issues raised by AI researchers.
Ethics and Artificial Intelligence
In this course, students are exposed to the concepts and connectionist models in neural networks. Applications, learning methods, and parallel distributed processing are among the topics covered. Hopfield networks, self-organizing and Grossberg networks, bidirectional associative memory, feedforward networks, and perceptrons are also taught in the course.
Electives include:
- Evolutionary Computing
- Knowledge-Based Systems
- Logic and Logic Programming
- Computational Intelligence
- Data Science
- Data Science Practicum
- Advanced Representation Learning
- Advanced-Data Analytics
- Privacy-Preserving Data Analysis
- Introduction to Robotics
- Human-Computer Interaction
- Philosophy of Language
- Model Theory
- Seminar in Philosophy of Mind
II. Research
A significant portion of the Ph.D. program is dedicated to original research in Artificial Intelligence. Under the guidance of a faculty advisor, students conduct in-depth research on a specific topic within the field. This research may involve developing new algorithms, designing AI systems, analyzing data, or exploring ethical considerations in AI applications.
III. Dissertation
The culmination of the Ph.D. program is completing a doctoral dissertation. The dissertation is a comprehensive research document that showcases the student’s original contributions to the field of Artificial Intelligence. It typically includes an introduction to the research topic, a review of relevant literature, a description of the research methodology, present results, and a discussion of findings.
IV. Defense
Once the dissertation is complete, Ph.D. candidates must defend their research findings before a committee of faculty members. During the defense, students present their dissertation and answer questions from the committee members. The defense allows them to demonstrate their expertise in their research area and defend the validity of their findings.
Some topics of research areas within Artificial Intelligence offer opportunities for exploration, innovation, and impactful contributions to the field so that students can pursue research include:
- Explainable Artificial Intelligence
- AI for Healthcare
- Autonomous Systems
- Ethical AI
- Reinforcement Learning
- AI for Natural Language Understanding
- Computer Vision
- AI and Creativity
- AI for Social Good
- Multi-Agent Systems
- Deep Learning Techniques
- Transfer Learning in AI
- Federated Learning
- AI-driven Personalization
- AI in Cybersecurity
- Human-Robot Interaction
- AI in Education
- AI in Finance
- Evolutionary Computation
- AI-driven Environmental Monitoring
Learning Outcomes and Skills Gained
A Ph.D. in artificial intelligence online is a degree that offers an in-depth understanding of artificial intelligence and its nuances. This program makes students capable enough to independently analyze and research real-world problems and find solutions much better than bachelor’s or master’s degree holders can. Some of the skills they can showcase after completing their doctoral programs include the ability to:
- understand the repercussions of AI system application to organizations;
- develop AI systems to meet business needs;
- gain expertise in the implementation of AI frameworks to improve business;
- develop and automate organizational processes;
- create organizational intelligence by making use of a holistic approach based on business, company, and technology needs;
- develop a robotic process to manage business processes that help in increasing & monitoring their efficiency;
- decide and create a framework in which AI and the IoT may function, which includes enterprise functions, interactions with people, and environments;
- demonstrate expertise in solving real-world problems by applying problem-solving, critical thinking, and cognitive computing skills.
Areas of Specialization for Ph.D. in Artificial Intelligence Students
Considering artificial intelligence is broad in scope, students can specialize in one of its sub-fields to gain specialized knowledge that can lead to unique job opportunities and higher pay. Here are some Ph.D. in artificial intelligence online concentration areas students can consider:
| Area of Specialization | Description | Career Options |
|---|---|---|
| Machine Learning | This specialization teaches the development and use of a computer system capable of learning and adapting without explicit instructions. It uses algorithms and statistical models that help analyze and draw inferences. | Data scientist, AI architect, AI engineer, business intelligence analyst/developer, software engineer, software developer |
| Deep Learning | This concentration is a subfield of machine learning that studies algorithms inspired by the structure and function of the brain, called artificial neural networks. | Software engineer, data analyst, data engineer, research analyst, software developer |
| Machine Vision | In this specialization, students learn about the technology used to provide imaging-based automatic inspection and learn applications such as process control, automatic inspection, and robot guidance. | Machine learning engineer, data scientist, business intelligence developer, AI engineer |
| Natural Language Processing | This specialization is an interdisciplinary subfield of computer science, linguistics, and artificial intelligence dealing with the interactions between computers and humans. It teaches how to program computers to analyze and process large amounts of natural language data available. | NLP researcher, NLP analyst, NLP scientist |
| Data Visualization | This specialization deals with the graphic representation of information and data. Students learn the best communication methods when dealing with large amounts of data. | Data visualization engineer, data analyst |
Full-Time and Part-Time AI Ph.D. Programs
Artificial intelligence Ph.D. programs offer flexibility, allowing students to choose between full-time or part-time enrollment. Full-timers typically dedicate themselves to their studies, completing the program in about four to five years. On the other hand, part-timers balance studies with other commitments and may take around six years or more to graduate.
The time required for completion heavily depends on the complexity of the dissertation topic and the depth of related research. Writing a dissertation involves extensive research, analysis, experimentation, and writing, contributing to the overall duration. Resource availability, faculty support, funding, and data access may also impact the timeline.
Regardless of enrollment status, full-time and part-time Ph.D. students must demonstrate a deep understanding of their research area, contribute new knowledge, and successfully defend their dissertations. Thus, while the duration may vary, the goal remains the same: to produce well-rounded researchers capable of advancing artificial intelligence.
Accelerated Ph.D. in Artificial Intelligence Programs
Accelerated artificial intelligence Ph.D. programs allow students to earn their doctorates in a comparatively shorter time than the stipulated four to five years. With dedicated full-time study and research, and providing the research topic and dissertation do not consume too much time and effort, they can complete their Ph.D. in artificial intelligence in three to four years. Universities do not explicitly label their programs “accelerated”; many simply encourage interested candidates to complete their studies faster by providing extra support. Few colleges providing an accelerated Ph.D. in Artificial Intelligence include
Admission Requirements for Ph.D. in Artificial Intelligence Programs
The admission requirements for artificial intelligence Ph.D. programs vary considerably from one college to another. The program normally requires an upper second-class honors degree (or its foreign equivalent) in a relevant field from an accredited university as entry criteria. Computer science, science, mathematics, statistics, and engineering (electronics/electrical) are among the disciplines relevant to artificial intelligence, in which a student is expected to have a background. Some Ph.D. in artificial intelligence programs additionally call for applicants to have programming knowledge; the preferred language will depend on the research project. Notably, applicants with academic or professional data science or machine learning qualifications are frequently favored. The list of some standard admission requirements to get into a Ph.D. in AI includes:
- A master’s degree in relevant fields like AI, computer science, or machine learning
- A Professional Résumé that reflects relevant work experience
- GRE scores (usually required in the absence of work experience)
- Letters of Recommendation
- A Personal Statement that describes research interests
- Submission of prior research work or a master’s thesis
- An online or offline interview
Online Ph.D. in Artificial Intelligence No GRE Programs
The Graduate Record Examination (GRE) scores are a benchmark for judging whether a student can conduct independent study and research; most colleges grant admission based on this score. However, many universities have moved away from this requirement over the past few years. It is worth noting that online Ph.D. artificial intelligence no gre programs, and those that require the GRE offer the same quality and credentials. Some colleges providing such programs include:
How to Ensure a Ph.D. in Artificial Intelligence Program is Accredited
Accreditation is a seal of trust and credibility of a university. It assures students and potential employers that the programs offered by the accredited university are authentic and of top-quality standards. Only degrees from accredited institutions are valid and accepted when seeking a job or financial aid. Here are the six regional accrediting agencies that grant regional accreditation to universities across the country:
- New England Commission of Higher Education (NECHE) [5]
- Middle States Commission on Higher Education (MSCHE) [6]
- Higher Learning Commission (HLC) [7]
- Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) [8]
- Northwest Commission on Colleges and Universities (NWCCU) [9]
- Western Association of Schools and Colleges (WASC) [10]
- Senior College and University Commission (WSCUC)[11]
Apart from these, a Ph.D. in artificial intelligence online program can also be programmatically accredited by:
Read more about accreditation and its importance in the Guide to Accreditation.
Free Artificial Intelligence Courses
Some reputable universities offer various free artificial intelligence courses. These provide insight into mathematics, data science, AI, machine learning, deep learning, and software engineering and can help students understand the real-world applications of AI. Here are a few to explore:
| Course | Description | Provided by |
|---|---|---|
| Data Science: Linear Regression [17] | This course teaches students how to implement linear regression, one of the most common statistical models used in data science. The course also teaches how to examine the relationship between various variables. | Harvard University |
| IBM Data Science Professional Certificate [18] | In this course, students learn how to build different data science skills and use various tools to process data and extract useful information for practical applications. | Coursera |
| High-Dimensional Data Analysis [19] | In this course, students learn about dimension reduction, mathematical distance, multiple-dimensional scaling plots, factor analysis, and dealing with batch effects. They also learn advanced concepts like principal component analysis. | Harvard University |
Ways to Pay for Ph.D. in Artificial Intelligence Program
The costs of obtaining a doctorate in artificial intelligence are substantial. According to Education Data, the average cost of a Ph.D. in the United States is $98,800 [20]. Many prospective online students may struggle to afford the high tuition and associated research costs, even if they have no other out-of-pocket expenses (such as books, supplies, or meals). External funding opportunities for students pursuing a Ph.D. in artificial intelligence online may be used to cover some of their education costs. These include:
Scholarships
Scholarships are popular among students because they do not require repayment. Individuals, organizations, and universities award them with academic excellence and achievement.
FAFSA
The Free Application For Federal Student Aid (FAFSA) is an application for federal financial aid that prospective and current college students can fill out to check their eligibility for federal aid.
Fellowships
Predoctoral fellowships, also known as Ph.D. fellowships, are special grants given to doctoral students. Accepting a fellowship as a Ph.D. candidate frequently comes with strings attached, such as a required project or using funds for specific objectives. Several awards and fellowships are available to assist in retaining or recruiting the most promising students.
Private Student Loans
Banks, credit unions, and private lenders give students education loans against interest payments. Students can borrow up to 100% of their study costs. However, taking out a loan can lead to debt if the borrowed money is not paid back on time. To mitigate this, students can look for donors and grants to help repay loans.
Grants
Grants are financial assistance for students with special requirements offered by not-for-profit organizations, foundations, or the federal government. The grant award can cover all educational expenses, including tuition, books, library fees, housing, transportation, and research materials.
Graduate Assistantships
Students who work with faculty in teaching or research can apply for graduate assistantships. Volunteering graduates frequently receive a monetary stipend or a tuition fee reduction in exchange for their efforts. Graduate assistantships are of two types – teaching and research.
Fully Funded Ph.D. in Artificial Intelligence Programs
Finding a university that offers a fully funded Ph.D. program in artificial intelligence is tricky. However, many universities provide fully funded programs in computer science with an AI specialization or machine learning with a specialization in AI. These fully-funded Ph.D. programs often cover tuition costs for the duration of the program, provide a stipend or salary, and offer health benefits to select students who can contribute to research activity and impact the field of study.
Career Opportunities and Salaries for Ph.D. in Artificial Intelligence Students After Graduating
AI Ph.D. programs increase career opportunities and allow for specialized work in AI; thus, employers offer Ph.D. holders higher salaries than other degree holders. Moreover, the Ph.D. opens up careers in research, academia, and government sectors like hardware development, cyber security, software development, database administration, or network security. Here’s a list of potential careers for individuals with a Ph.D. in Artificial Intelligence:
- AI Research Scientist
- AI Research Engineer
- AI Consultant
- Machine Learning Researcher
- Data Scientist
- Natural Language Processing (NLP) Specialist
- Computer Vision Engineer
- Robotics Engineer
- Deep Learning Engineer
- AI Ethics Specialist
- AI Product Manager
- AI Solutions Architect
- AI Systems Developer
- AI Educator/Professor
- AI Entrepreneur/Startup Founder
- AI Policy Advisor
- AI Project Manager
- AI Technical Lead
- AI Analyst
- AI Business Development Manager
Some of the career options available for artificial intelligence Ph.D. students are:
| Occupation | Skills Required | Median Annual Salary | Job Growth (up to 2032) | Job Description |
|---|---|---|---|---|
| Computer and Information Research Scientists [21] | Analytical skills, communication skills, detail-oriented, interpersonal skills, logical thinking | $136,620 | 23% (much faster than average) | Computer and information research scientists are responsible for designing innovative uses for existing or novel technologies. They study & solve complex problems in computing for business, science, and medicine. |
| Data Scientists [22] | Analytical skills, math skills, communication skills, problem-solving skills, detail-oriented, interpersonal skills, logical thinking | $103,500 | 35% (much faster than average) | Data scientists design, verify, evaluate, and revise algorithms and models. They employ data visualization software to display research information and identify the available and pertinent data to the project. |
| Computer Systems Analysts [23] | Analytics skills, business skills, communication skills, creativity, organizational skills | $102,240 | 10% (much faster than average) | Computer systems analysts, sometimes known as systems architects, analyze a business’s current computer systems and processes and develop new ones. They also oversee the installation and configuration of new systems, customize them, and test them to ensure they work as expected. |
| Quality Assurance Analysts [24] | Analytics skills, business skills, communication skills, creativity, organizational skills | $124,200 | 25% (much faster than average) | Software quality assurance analysts create and carry out software tests to find issues and understand how the product functions. They conduct exploratory and software testing using manual or automated methods and assess the outcomes. |
Certifications and Licensing for Ph.D. in Artificial Intelligence Graduates
Professional certifications in AI are an excellent way to complement a doctorate in artificial intelligence. These advanced certifications are intended to demonstrate expertise in a specific area of AI. A Ph.D. should be sufficient evidence of knowledge and ability, but additional credentials can boost a résumé and open up more job opportunities. Many businesses and organizations provide general, vendor-specific, and vendor-neutral (third-party) certifications. Here are a few examples:
Artificial Intelligence Engineer (AiE) Certification [25]
The AIE certification, administered by the Artificial Intelligence Board of America (ARTiBA), is among the most potent qualifications in AI today because it creates opportunities for faster career growth and more challenging projects and roles for candidates by demonstrating their readiness for developing AI applications and designing AI-based solutions for the full range of use cases and user industries.
International Association of Business Analytics Certification (IABAC) [26]
The IABAC demonstrates proven knowledge of the core concepts of artificial intelligence and cutting-edge tools for managing and delivering artificial intelligence assignments following global best practices.
United States Artificial Intelligence Institute Certifications [27]
The United States Artificial Intelligence Institute (USAII) is dedicated to addressing the global demand for filling the AI skills gap and the workforce shortage. It accepts responsibility for fostering the growth of the necessary talent, potential, and skills to be effective and well-qualified in artificial intelligence. USAII offers four certifications:
- Certified Artificial Intelligence Engineer (CAIE)
- Certified Artificial Intelligence Consultant (CAIC)
- Certified Artificial Intelligence Scientist (CAIS)
- Certified Artificial Intelligence Prefect (CAIP)
Intel Edge AI Certification [28]
The Intel Edge AI Certification teaches candidates how to use the latest Intel developer tools and platforms to create their portfolios of edge AI solutions. The certification program includes virtual classroom instruction and hands-on projects.
Global Tech Council’s Certified Artificial Intelligence (AI) Developer [29]
The Certified Artificial Intelligence (AI) Developer certification was created by AI experts and covers questions ranging from basic concepts to the very core of AI. The certification program’s training is meticulously curated and well-designed, providing in-depth knowledge of various aspects of AI.
Additional Resources for Ph.D. in Artificial Intelligence Graduates
Joining a professional organization offers students various options to better their careers in artificial intelligence. By using the resources these organizations provide, students pursuing artificial intelligence doctoral programs gain in-depth knowledge, upskill, and interact with a pool of industry specialists, giving them much-needed exposure. Here are a few organizations to consider:
| Title/Resource | Description |
|---|---|
| American Association for Artificial Intelligence [30] | The American Association for Artificial Intelligence is a nonprofit scientific society devoted to advancing the scientific understanding of mechanisms underlying thought and intelligent behavior and how they can be embodied in machines. |
| Association for Computational Linguistics [31] | The Association for Computational Linguistics is an international scientific and professional society that caters to people working on problems involving natural language & computation. |
| Association of Data Scientists [32] | The Association of Data Scientists oversees standardization in data science and works towards integrating its various branches. The organization also encourages data science education and assists students in integrating high professionalism into their work. |
| Electrical and Computer Engineering Department Heads Association[33] | The Electrical and Computer Engineering Department Head Association (ECEDHA) is one of the most prestigious academic organizations representing all major electrical engineering, computer engineering, and related programs at universities all over North America. |
| Institute for Operations Research and Management Science [34] | The Institute for Operations Research and Management Science (INFORMS) offers its members numerous benefits. It provides networking opportunities and sponsorship, facilitates research and development, and more. |
FAQs About Ph.D. in Artificial Intelligence Programs
Why should you do an online artificial intelligence Ph.D. program?
Online Ph.D. in artificial intelligence programs are just as credible as offline, provided you pursue the degree at an accredited university. Online programs are a perfect fit for those with work demands or family and other commitments because they offer the flexibility of schedule, pace, and limitless location.
What can you do with an online artificial intelligence Ph.D.?
Is an online Ph.D. in artificial intelligence worth it?
How hard is it to get a Ph.D. in artificial intelligence?
What are the concentrations in an artificial intelligence Ph.D.?
How do you get a Ph.D. in artificial intelligence?
Citations:
New England Commission of Higher Education (NECHE)
Middle States Commission on Higher Education (MSCHE)
Higher Learning Commission (HLC)
Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)
Northwest Commission on Colleges and Universities (NWCCU)
Western Association of Schools and Colleges (WASC)
Senior College and University Commission (WSCUC)
Computing Sciences Accreditation Board (CSAB)
Accreditation Board for Computer Engineering and Technology (ABET)
Data Science Council of America (DASCA)
Artificial Intelligence Board of America (ARTiBA)
Central Blockchain Council of America (CBCA)
Harvard University: Data Science: Linear Regression
Coursera: IBM Data Science Professional Certificate
Harvard University: High-Dimensional Data Analysis
Education Data – Average Cost of a Doctorate Degree
U.S. Bureau of Labor Statistics – Occupational Outlook Handbook – Data Scientists
U.S. Bureau of Labor Statistics – Occupational Outlook Handbook – Computer Systems Analysts
U.S. Bureau of Labor Statistics – Occupational Outlook Handbook – Quality Assurance Analysts
Artificial Intelligence Engineer (AiE) Certification
International Association of Business Analytics Certification (IABAC)
United States Artificial Intelligence Institute Certifications
Global Tech Council’s Certified Artificial Intelligence (AI) Developer
American Association for Artificial Intelligence
Association for Computational Linguistics
Association of Data Scientists
Electrical and Computer Engineering Department Heads Association
Disclaimer:
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