Is Artificial Intelligence a Hard Major? What Students Should Know in 2026

Co-Founder and Chief Data Scientist

The academic demands of an artificial intelligence major are often seen as daunting, yet opinions vary widely on its difficulty. Enrollment in AI-related programs in the U.S. has surged by over 40% in recent years, reflecting growing interest despite the field's technical complexity. Many students wonder how challenging the coursework and skills truly are.

This article explores the rigor of artificial intelligence curricula, typical workload expectations, and the essential skills students need to succeed. It also examines key factors such as prior knowledge and learning styles that influence whether an AI major feels manageable or difficult for individual learners.

Key Benefits of Artificial Intelligence as a Major

Artificial intelligence develops adaptable problem-solving skills, attracting career changers seeking relevant, in-demand expertise in a rapidly growing field.
It offers flexible learning paths, supporting full-time workers balancing education with professional responsibilities through online courses and modular curricula.
Students gain confidence managing complex concepts, enhancing opportunities for academic growth and employment in a sector expected to grow 22% by 2030.

Where Does Artificial Intelligence Rank Among the Hardest College Majors?

Artificial intelligence is generally ranked among the more demanding college majors due to its extensive technical and analytical requirements. It often falls under computer science or engineering categories in national difficulty assessments, recognized for intense programming tasks in languages like Python and Java, advanced mathematics including calculus and linear algebra, and challenging theoretical subjects such as machine learning and data analysis.

The curriculum frequently includes significant lab work, projects, or practicums that demand substantial time beyond lectures. For instance, a 2023 survey reported that computer science students dedicate about 18-22 hours weekly to coursework outside class, a commitment likely matched or exceeded by AI students.

Perceptions of AI's difficulty can vary widely depending on the institution and student's background. Prestigious programs at schools like MIT or Carnegie Mellon tend to be more rigorous, while some state universities may offer more application-focused or flexible options. Students with strong skills in math and programming usually find it more manageable, whereas others may face challenges.

Compared to other fields, AI is often considered harder than majors such as marketing or journalism but on par with or slightly less tough than disciplines like pure math, physics, or electrical engineering. Ultimately, the level of difficulty is subjective and closely tied to a learner's prior experience, motivation, and academic preparation.

What Factors Make Artificial Intelligence a Hard Major?

Artificial intelligence is a demanding major due to substantial academic and technical skill requirements that challenge many students. The workload and analytical complexity create a rigorous environment necessitating perseverance and adaptability.

Academic rigor of artificial intelligence degree programs: AI curricula involve comprehensive coursework in mathematics, statistics, and advanced computer science. For instance, programs like Rice University's Bachelor of Science in artificial intelligence require around 67 credit hours, including multiple upper-level courses that build deep expertise.
Workload and skill requirements for AI majors: Students engage with complex topics such as algorithms, machine learning, probability, and calculus. Strong problem-solving skills are essential as they design and implement AI algorithms while considering ethical implications.
Technical complexity and analytical demands: The program covers foundational and advanced computing concepts dictated by ABET accreditation guidelines-including programming languages, security, and the societal impact of computing-requiring substantial intellectual effort.
Field-specific projects and research participation: AI students often handle capstone projects, research involvement, or system development. These activities are time-consuming and require practical application of theoretical knowledge.
Rapid technological evolution: Continuous learning and quick adaptation to emerging AI technologies add ongoing challenges, demanding flexibility beyond traditional academic work.

Those considering an AI major should recognize these factors contribute to its complexity. For students interested in intersecting education with lucrative career opportunities, exploring the highest paying certificate programs related to AI and computing can provide valuable insights.

How fast is vocational certificate attainment growing?

Who Is a Good Fit for a Artificial Intelligence Major?

Knowing the best students for artificial intelligence major is essential to succeeding in this challenging field. The right profile aligns with the skills needed to succeed in artificial intelligence, especially given the technical and analytical demands of coursework and research.

Analytical Thinkers: These students excel at breaking down complex problems and enjoy logical reasoning. Their ability to approach issues systematically helps them manage the rigorous math and algorithm challenges found in AI studies.
Strong Mathematicians: A solid foundation in linear algebra, calculus, and statistics is critical. Students with confidence in these areas adapt well to the quantitative nature of AI tasks and data modeling.
Programming Enthusiasts: Comfort with coding and algorithm development is a must. Those who enjoy experimenting with various programming languages and building solutions often find the learning curve more manageable.
Curious Learners: Curiosity about how machines learn and make decisions drives deeper engagement. This trait fosters persistence and openness to iterative testing, which is vital for success in AI projects.
Collaborative Problem-Solvers: AI programs often require teamwork, and students who thrive in group settings can leverage diverse perspectives. They tend to learn effectively from both successes and failures, accelerating skill growth.

Many who embody these traits find they can navigate the program's challenges efficiently. For those interested in how their education translates to career advancement, exploring the best online certificate programs that pay well can offer valuable insight.

Breakdown of Private Fully Online Nonprofit SchoolsU.S. Department of Education, 2023

Source: U.S. Department of Education, 2023

How Can You Make a Artificial Intelligence Major Easier?

Many students find artificial intelligence challenging due to its heavy reliance on math, programming, and constant problem-solving. However, applying targeted strategies can significantly lighten the workload and improve comprehension throughout the major.

Establish a Strong Math Base: Focus on linear algebra, calculus, and statistics early to avoid struggling with advanced AI topics later.
Create Consistent Study Routines: Regular, scheduled practice leads to deeper understanding than last-minute cramming.
Learn Python Thoroughly: Building solid programming skills from the start simplifies coding tasks essential to AI projects.
Engage with AI-powered Learning Tools: Use quizzes and summaries generated by AI to actively test your knowledge and reinforce key concepts.
Utilize Academic Support Systems: Attend tutoring sessions, join study groups, and consult professors to clarify difficult ideas and stay motivated.

A graduate who majored in artificial intelligence shared that the toughest part was managing the complexity and volume of new concepts. She emphasized, "I realized I couldn't just passively read textbooks-I had to interact with the material." She adopted regular self-quizzing using AI tools, which helped identify her weak spots early.

Additionally, she found setting fixed weekly coding practice times and leaning on study groups essential for maintaining momentum. Reflecting on her journey, she said, "It wasn't about working harder but working smarter and being consistent that made the difference for me."

Are Admissions to Artificial Intelligence Programs Competitive?

Admissions to artificial intelligence programs tend to be highly competitive due to increasing interest and limited spots at top universities. Many programs receive a large number of applicants, but have relatively small cohort sizes to maintain quality and provide personalized education. Furthermore, these programs often require strong academic records and relevant experience in computer science or related fields, which narrows the applicant pool significantly.

Selectivity varies across institutions, with some schools expecting high GPAs, usually above 3.5, and completion of prerequisite courses such as data structures, algorithms, and mathematics. Additionally, some programs look for candidates with prior programming experience or research involvement in AI-related topics. The rising demand for artificial intelligence skills and career prospects contributes to more selective admissions over time, especially at prestigious universities.

When I spoke with a professional who majored in artificial intelligence, he described his application experience as both challenging and rewarding. "It felt intimidating at first because the requirements were stringent, and I wasn't sure if my background was strong enough," he recalled.

He emphasized spending months strengthening his programming portfolio and engaging in AI projects before applying, which ultimately gave him confidence and helped him secure a spot. His journey highlighted how perseverance and preparation play vital roles in navigating competitive admissions for AI programs.

Is an Online Artificial Intelligence Major Harder Than an On-Campus Program?

Online artificial intelligence programs are neither inherently harder nor easier than on-campus options; their relative difficulty depends on several factors including student motivation and program design. Academic demands and expectations tend to be comparable, though the learning experience varies notably between formats.

Here is a comparison of key factors impacting the online vs on-campus artificial intelligence degree difficulty:

Academic Expectations and Workload: Core coursework such as advanced mathematics and programming maintains similar rigor across formats, with accredited online programs matching traditional standards.
Pacing and Flexibility: Online students benefit from more flexible scheduling that supports balancing work and family, but require strong self-discipline to avoid procrastination.
Interaction and Support: On-campus students gain from face-to-face faculty engagement and hands-on labs, whereas online learners often face less immediate feedback and more isolation.
Learning Environment: Online learners may struggle with distractions and technology issues, affecting engagement despite typically higher attendance rates than in-person counterparts.
Unique Challenges: The need for self-motivation and independence in online programs can increase perceived difficulty, though for some, the flexibility makes it more manageable.

For those exploring the best online artificial intelligence programs in the US, understanding these distinctions can guide better educational choices. Prospective students seeking alternatives to traditional study might consider reputable online options including those highlighted among the most affordable doctoral programs.

Are Accelerated Artificial Intelligence Programs Harder Than Traditional Formats?

Accelerated artificial intelligence programs are generally considered harder than traditional formats due to their condensed timelines, faster pacing, and increased workload intensity. Students in these programs must absorb complex material quickly, which significantly impacts their academic experience. Below is a comparison highlighting key differences between accelerated and traditional artificial intelligence learning formats.

Course Pacing and Content Density: Accelerated AI master's program difficulty stems from compressed schedules that cram the same core subjects, such as machine learning and natural language processing, into 12 to 18 months instead of the usual two years.
Workload Management: Accelerated artificial intelligence degree workload demands full-time dedication with fewer breaks, making it more challenging for students balancing jobs or family, whereas traditional programs offer more flexibility.
Academic Expectations and Skills: Fast-paced programs require heightened self-management and time commitment, often suited for highly motivated students who can maintain intense daily study hours.
Learning Retention and Stress: The rapid succession of assignments and projects in accelerated tracks may increase stress and risk of burnout, potentially affecting long-term retention compared to the steadier pace of traditional formats.
Flexibility and Structure: Traditional programs provide regular semester breaks and a gradual material progression, offering more balance compared to the rigid schedule of accelerated tracks.

Because of these challenges, prospective students interested in online learning options are encouraged to explore reputable accredited colleges online no cost to apply to find programs that best fit their lifestyle and academic goals while managing the accelerated Artificial Intelligence degree workload effectively.

Can You Manage a Part-Time Job While Majoring in Artificial Intelligence?

Managing a part-time job while majoring in artificial intelligence is achievable for some students but depends on key factors like course intensity, weekly study demands, and individual study routines. The workload in AI often includes complex math, computer science, and engineering tasks combined with labs and extended project cycles. Students who have flexible work schedules or less intensive course loads generally find it easier to maintain this balance.

Balancing work and study in artificial intelligence usually requires careful time management and prioritization. Many students opt for moderate credit loads and jobs with remote or shift-based hours to accommodate their academic commitments. The discipline's substantial lab hours and technical assignments can make sustained focus challenging, especially during project-heavy periods.

Support from tutoring, peer study groups, or AI-powered scheduling tools also helps students manage their responsibilities more effectively. Those with less structured study habits or accelerated program demands may encounter more difficulty sustaining both work and academic success.

What Jobs Do Artificial Intelligence Majors Get, and Are They as Hard as the Degree Itself?

Career paths for artificial intelligence majors vary widely in difficulty, responsibility, and required skills. While some roles match the rigorous demands of the major itself, others may feel less demanding or present challenges in different forms.

Machine Learning Engineer: Designs and maintains systems that enable computers to learn from data without explicit programming. This role demands advanced coding, mathematics, and familiarity with frameworks like TensorFlow or PyTorch, making it as challenging and technical as the major.
Data Scientist: Analyzes large datasets to create predictive models and support business decisions. The job focuses more on statistics and data visualization, often feeling less intense but requiring strong communication skills for practical implementation.
AI Research Scientist: Conducts foundational AI research, often involving deep learning or computational statistics. This career usually requires a PhD and is generally as rigorous, or more, than the degree, with emphasis on experimental design and publication.
Natural Language Processing (NLP) Engineer: Develops systems for understanding and generating human language, such as chatbots or translation tools. This role is demanding in a different way, prioritizing specialized linguistic and language model expertise alongside technical skills.
Robotics Engineer: Designs and programs intelligent machines for applications like automation or healthcare. Compared to academic AI, this job is often more hands-on and less theoretical, focusing on hardware-software integration rather than pure algorithmic challenges.

Artificial intelligence is widely considered one of the more challenging majors, often associated with high workloads and lower average GPAs, reflecting the technical and mathematical rigor required. For those questioning is working in artificial intelligence as challenging as studying it, the answer depends on the role and individual adaptation to ongoing learning demands.

Students or professionals seeking the best careers for artificial intelligence majors might also explore certification courses that pay well to complement their core AI skills and widen their opportunities in this rapidly evolving field.

Do Artificial Intelligence Graduates Earn Higher Salaries Because the Major Is Harder?

Artificial intelligence graduates do tend to earn higher salaries, but this is not solely because the major is more difficult. While the coursework is challenging, requiring strong foundations in mathematics, computer science, and statistics, the primary driver of higher pay is the strong market demand for AI skills. Employers value the specialized abilities students develop, especially practical, real-world experience, which often leads to salary premiums ranging from 19% to 56% over similar roles without AI expertise.

Consequently, the difficulty of the major supports skill development, but it is the market's need for these competencies that most directly influences earnings.

Several variables impact the salaries of artificial intelligence graduates beyond academic rigor. Industry sectors such as technology, finance, and healthcare offer the highest compensation due to their intense demand for AI professionals. Geographic factors also matter significantly; for instance, an AI engineer in San Francisco may earn upwards of $245,000, whereas in Columbus, Ohio, the average salary is closer to $104,000.

Experience and job level further contribute, with senior roles often surpassing $350,000 annually. Additionally, relevant internships and project portfolios can substantially boost starting salaries, underscoring the value of hands-on expertise alongside formal education.

What Graduates Say About Artificial Intelligence as Their Major

Louie: "Majoring in artificial intelligence was definitely challenging, but the learning experience was incredibly rewarding. Despite the high cost of attendance, which averaged around $35,000 per year, the specialized skills I gained have opened doors to amazing career opportunities in tech. Looking back, I'm glad I invested both time and money into such a forward-thinking field. "

Mel: "Reflecting on my journey through artificial intelligence, I'd say the major is tough but manageable with dedication. The financial burden was noticeable, considering tuition and resources, but the personal growth and insight into AI's potential impact made it worthwhile. This field has reshaped how I view technology and its role in society."

Zach: "From a professional standpoint, artificial intelligence is a demanding major that requires strong analytical skills and persistent effort. The cost of attendance is high, typically over $30,000 annually, but the return on investment in terms of job prospects and salary potential is significant. Pursuing this major was a strategic decision that's already paid dividends in my career."

Other Things You Should Know About Artificial Intelligence Degrees

Is artificial intelligence considered a STEM major?

Yes, artificial intelligence is considered a STEM (Science, Technology, Engineering, and Mathematics) major. It combines elements from computer science, mathematics, and engineering to develop systems that mimic human intelligence. The technical nature and rigorous coursework align it closely with other STEM disciplines.

Do artificial intelligence majors require strong programming skills?

Strong programming skills are essential for artificial intelligence majors. Students need proficiency in languages such as Python, Java, or C++ to implement algorithms and work with AI frameworks. Programming forms the foundation for developing machine learning models and other AI applications.

Are math skills important for success in an artificial intelligence major?

Mathematics is a critical component of artificial intelligence education. Topics like linear algebra, calculus, probability, and statistics play a major role in understanding AI algorithms and data modeling. Students without a solid math background may find this aspect challenging but can develop skills through dedicated study.

Is teamwork important in an artificial intelligence major?

Teamwork is important in artificial intelligence programs because many projects require collaboration across different expertise. Students often work in groups to develop complex AI systems, combining skills in software development, data analysis, and domain-specific knowledge. Effective communication and collaboration enhance learning and project outcomes.