Preparing Your Child for the AI Era: Promising Majors, Future Career Outlook, and High School Preparation Strategies

The rapid advancement of artificial intelligence (AI) technology is dramatically reshaping the academic choices and career landscape that our children will navigate in the future. For parents of students currently attending high school in the United States, you’re likely wondering which academic fields will be most promising in the years ahead and how your child should prepare during their high school years. In this comprehensive guide, we’ll examine the major academic fields expected to see increased demand in the AI era, explore the industries and careers they connect to, and analyze high-paying, high-demand occupations projected for the next decade in the U.S. based on the latest data. Additionally, we’ll provide extensive recommendations for courses and extracurricular activities that high school students should consider to prepare for the AI era, offering practical guidance that parents can use in their children’s career planning. We’ll explore professional yet accessible information that takes into account the U.S. high school curriculum and current college admissions trends.

1. Promising Academic Fields in the Age of AI Development

AI development is creating changes across virtually every industry, leading to a surge in demand for talent in related fields. International organizations such as the World Economic Forum (WEF) project that technology, engineering, and security fields will experience the fastest growth between 2025 and 2030. Based on these trends, we can identify the following promising academic fields for the AI era. Let’s examine what students will learn in each field and the specific industries and careers they can pursue.

Computer Science

Computer Science stands as the fundamental cornerstone field of the AI era. Students majoring in Computer Science learn programming, data structures, and algorithms, providing the foundation for understanding the core principles of AI technology. Computer Science graduates can pursue diverse careers throughout the IT industry, including software developers, AI solution developers, and systems engineers. Since virtually every industry now utilizes software and AI, there’s high demand across a broad range of sectors—from big tech companies to finance, manufacturing, and service industries. Students who specialize in AI-focused roles such as machine learning engineers or AI researchers can directly enter the most promising career paths of the future.

Artificial Intelligence and Machine Learning

This path involves either majoring specifically in artificial intelligence or concentrating on machine learning within computer science programs. Machine learning specialization focuses on the development and application of AI algorithms, dealing with the core technologies of artificial intelligence. Through this major, students can become autonomous vehicle AI system developers, AI software engineers, or data scientists, participating in work that involves training big data and creating predictive models. AI/ML graduates work in various settings including AI research labs at tech companies, AI development teams at startups, and as machine learning specialists at cloud computing companies. They can also work as domain-specific AI model developers in fields like healthcare or finance. Meanwhile, as natural language processing (NLP) technologies like ChatGPT gain prominence, computational linguistics—a fusion of computer engineering and linguistics—is also receiving attention. This technology enables AI to understand and generate human language, leading graduates to careers as chatbot developers, speech recognition system engineers, and search engine language processing specialists.

Data Science and Statistics

As the saying goes, “data is the fuel of AI,” and the ability to work with data is essential in the AI era. Data Science majors learn to collect, analyze, and interpret large volumes of data—a crucial capability since many AI applications depend on data for model training and improvement. Through this major, students can grow into data scientists, data analysts, or machine learning specialists, with high demand across all industries that make data-driven decisions, regardless of sector—finance, healthcare, marketing, manufacturing, and beyond. Statistics also serves as a foundational discipline for data interpretation, with statistics graduates working as statistical analysts, actuaries, or data specialists at research institutions. For example, actuaries in the insurance and finance sectors use mathematical statistics and data analysis capabilities, representing a promising career field with approximately 22% employment growth expected through the late 2020s. Overall, Data Science and Statistics graduates perform a wide range of roles from AI model development to business data analysis, and their value will only increase alongside AI advancement.

Robotics and Automation

Robotics engineering represents the intersection of AI and mechanical engineering, where students learn the design, construction, and operating principles of robots. The robotics field is already experiencing rapid growth, and the application of AI technology to robots is becoming increasingly important. Robotics engineering graduates can pursue careers as robot software engineers, automation systems engineers, drone developers, or logistics automation specialists. Industrial robots that automate manufacturing processes, service robots used in homes and healthcare settings, and autonomous vehicles are all products of the combination of robotics and AI. For example, the automotive industry greatly needs personnel to develop autonomous vehicles that combine traditional mechanical engineering with AI, and the advancement of electric vehicles and autonomous driving technology is creating demand for AI-related knowledge among automotive engineering graduates. By majoring in robotics, students can become key personnel in the AI era across diverse industries including manufacturing, logistics, automotive, and aerospace.

Cybersecurity

The cybersecurity field is growing in importance alongside AI development. As digital assets of companies and governments increase, the demand for security experts to defend against hacking and cyber attacks is expanding. Students who major in cybersecurity or focus intensively on information security within computer science can pursue careers as information security analysts, security engineers, or network security administrators. Currently, cybersecurity experts are in very high demand across the U.S. government, finance, healthcare, and IT companies. According to the U.S. Bureau of Labor Statistics (BLS), “information security analysts are among the fastest-growing occupations as protecting sensitive information becomes a priority in the digital age.” In fact, the projected 10-year employment growth rate for information security analysts is approximately 33%, far exceeding the average for all occupations (around 5%). Since AI technology is also being used in cyber attacks, new roles such as AI-based security solution developers and AI security analysis specialists are emerging, making the roles of related majors even more diverse.

Electrical/Computer Engineering and IoT

The AI era is also driving innovation in hardware and infrastructure. Through Electrical Engineering or Computer Engineering majors, students can enter fields such as semiconductor chip design for AI computation, Internet of Things (IoT) device development, and cloud computing infrastructure construction. For example, graduates might become GPU/AI accelerator chip developers for rapid AI model training, IoT systems engineers connected to 5G networks, or cloud systems architects. Industries are actively pursuing projects that combine IoT and AI, such as smart factory construction in manufacturing plants, smart city infrastructure, and sensor networks for autonomous vehicles, creating demand for personnel to lead these initiatives. This hardware and network field knowledge only shines when combined with AI software, making it a hidden powerhouse that forms the foundation of the AI era. Electrical/Computer Engineering graduates take on key roles across various industries as hardware engineers at big tech companies, network engineers at telecommunications companies, and smart grid engineers in the energy sector.

Bioinformatics and Health Tech

AI technology is also driving innovation in medical and biotechnology fields, increasing demand for interdisciplinary majors that combine medicine and data science. Through Bioinformatics or Health Informatics majors, students can enter fields such as life sciences data analysis, AI drug development, and medical imaging AI. For example, bioinformatics specialists who work with genomic data use AI algorithms to analyze disease-related genes and contribute to drug development, while health informatics graduates can analyze electronic medical records (EMR) and healthcare big data to improve medical services. According to BLS occupational outlook, the overall healthcare field will show the largest job growth over the next decade due to factors such as aging populations, with particular growth expected in AI-powered medical services and pharmaceutical research. Therefore, interdisciplinary talent combining medical knowledge and computing skills are highly sought after at pharmaceutical companies, biotech startups, hospital data analysis teams, and government health agencies.

Additionally, fields like UX/UI design and Cognitive Science, which focus on the interaction between AI systems and humans, are becoming increasingly important. As AI products are used throughout our society, interest is gradually growing in UX designers and AI ethics specialists who help users utilize AI conveniently and ethically.

Note: Beyond the majors introduced above, foundational science and engineering fields such as mathematics, statistics, physics, and electrical engineering provide significant benefits for AI careers. Ultimately, AI technology requires knowledge from multiple fields, so interdisciplinary talent who can integrate AI into their areas of aptitude and interest will become increasingly important in the future. For example, students with strong interests in finance can become FinTech specialists in the AI era through Financial Engineering or Business Analytics majors, while those interested in environmental issues can grow into smart energy solution developers by adding data analysis skills to environmental engineering.

2. U.S. High-Paying, High-Demand Occupational Outlook for the Next Decade (2025-2035)

Examining the latest occupational projections from the U.S. Bureau of Labor Statistics (BLS), we can see that certain fields are expected to experience significant growth due to AI technology advancement and demographic changes. The healthcare sector and advanced technology fields are particularly expected to show both remarkable growth and high salaries over the next decade. Below are representative occupations expected to offer both high wages and high demand from 2025 to 2035 (growth rates reflect projected U.S. employment increases from 2023-2033, salaries represent 2024 median values).

Nurse Practitioner – 46% employment growth projected, median salary approximately $129,000. As advanced nursing personnel who partially replace physician demand and handle primary care, explosive growth is expected due to aging populations and increased healthcare demand.

Data Scientist – 36% employment growth, median salary approximately $112,600. As data-driven decision-making becomes important across industries, demand for data analysis and machine learning specialists is rapidly increasing.

Information Security Analyst – 33% employment growth, median salary approximately $124,900. With corporate and institutional movements to strengthen cybersecurity, demand for network and data security specialists is expected to increase significantly.

Physician Assistant – 28% employment growth, median salary approximately $133,000. As healthcare professionals who work in teams with physicians to provide care, both high growth rates and high compensation can be expected due to expanding medical services.

Medical and Health Services Manager – 29% employment growth, median salary approximately $118,000. As management positions responsible for operational management and medical service coordination in hospitals and care facilities, growth is significant due to healthcare industry expansion and efficiency improvement needs.

Computer and Information Research Scientist – 26% employment growth, median salary approximately $140,900. As occupations leading advanced computing technology and AI algorithm research, demand is particularly high in big tech research and development (R&D) sectors.

Software Developer – 18% employment growth, median salary approximately $132,300. As digital transformation accelerates across all industries, steady demand for software engineers continues, with high salaries expected as cloud and AI application software developers.

Actuary – 22% employment growth, median salary approximately $125,800. As specialists handling risk analysis and pricing in insurance and finance sectors, professional workforce demand and compensation are increasing as mathematical statistics and AI-powered prediction become more important.

Other opportunities are being created across various fields due to technological advancement and economic changes, such as logisticians and financial analysts. For example, in the power generation sector, the transition to renewable energy is projected to show very high growth rates of up to 60% for occupations like wind turbine technicians. However, since these occupations have moderate salary levels, careers that combine both high wages and high growth tend to be concentrated mainly in the technology and healthcare fields mentioned above.

Overall, it’s expected that professionals with AI and data utilization capabilities and advanced technology knowledge, along with healthcare and welfare field professionals responding to population aging and quality of life improvement trends, will be the two main pillars driving the U.S. job market going forward. Parents should use these trends as reference to help their children find the intersection between fields that interest them and promising future occupations.

3. Educational and Extracurricular Activity Recommendations for High School Students Preparing for the AI Era

U.S. college admissions comprehensively evaluate both students’ academic coursework and extracurricular achievements. Therefore, it’s important to build relevant knowledge and skills while demonstrating passion starting in high school. Particularly for students aiming for careers in AI or advanced technology fields, which high school subjects they take and what special activities they participate in can make a strong appeal to college admissions officers. Below, we’ll organize recommended courses and programs that high school students should consider to prepare for the AI era, regardless of grade level, along with recommended extracurricular activities.

Recommended High School Course Selections (AP, IB, Dual Enrollment, etc.)

Mathematics Courses: Mathematics is so important it’s called the language of AI. Students should take calculus during high school to build a solid foundation. If possible, studying statistics can also help develop data interpretation skills. Since AI algorithms utilize concepts like linear algebra, for IB programs, we recommend choosing advanced mathematics like Mathematics: Analysis & Approaches HL.

Computer Science Courses: Students should take programming/computer science classes offered by their school whenever possible. If AP courses are offered, taking AP Computer Science A (introductory Java programming) or AP Computer Science Principles (computer science overview) is helpful. This allows students to develop basic coding skills and problem-solving abilities. For IB program schools, choosing IB Computer Science HL allows for in-depth learning of algorithms and data structures. If schools don’t offer these subjects, students can take coding classes at local community colleges (Dual Enrollment) or utilize online MOOC courses.

Science and Engineering Courses: Science course selection can vary depending on the AI application field of interest. For example, students interested in robotics should study physics and introductory engineering to learn mechanical principles and basic electronic circuits. Those interested in bio/medical AI should take advanced biology or chemistry courses to prepare for related college majors. AP courses like AP Physics C and AP Biology may also provide college credit recognition and are worth attempting.

Other Humanities and Social Studies Courses: Students interested in AI ethics or technology policy should take a balanced selection of philosophy, economics, and sociology courses to broaden their perspectives. Since U.S. universities prefer well-rounded STEM talent, achieving good results in diverse fields outside the main major is also important.

Academic Tip: Students interested in AI should definitely master calculus, statistics, and basic computer science during high school if possible. With this foundation, they’ll be much better prepared to handle advanced courses like machine learning and data science in college.

Extracurricular Activity Ideas to Build Skills and Demonstrate Passion

Coding/Robotics Club Participation: If your school has computer science clubs, robotics clubs, hacking clubs, or data science clubs, participate actively. Creating projects with friends in clubs and competing in competitions builds teamwork and problem-solving skills while providing excellent experiences to highlight in college application essays. If your school doesn’t have related clubs, starting one yourself is a great way to demonstrate leadership. For example, students interested in AI can create an AI research group to study regularly or work on small AI projects together.

Official Competitions and Hackathons: Challenge yourself in competitions where you can test your skills and demonstrate creativity. Participating in FIRST Robotics or VEX Robotics competitions as a school representative team provides practical experience in robot design and programming. Participating in hackathons allows you to complete creative programming projects with a team in a short time frame. Many hackathons and AI competitions for high school students are now available, providing opportunities to build actual AI models and develop problem-solving abilities. For example, participating in data analysis competitions like Kaggle or AI idea contests and winning awards can be major strengths in college admissions.

Scientific Research and Internship Experience: If you have clear interests in specific fields, we recommend challenging yourself with research projects. Many summer university lab internships and science camp programs are available for high school students. Programs like Stanford University’s AI4ALL select a small number of high school students to work on projects with AI professors and researchers. Reading research papers and conducting small-scale research demonstrates deep understanding and passion for the field. You can also inquire about research participation with nearby university professors or apply for high school intern positions at medical or corporate research labs. Whether for a few weeks or an entire vacation, internships allow you to learn real-world problem-solving, gain mentorship, and receive recommendation letters.

Personal Projects and Competition Submissions: Completing small AI/programming projects based on self-study is also very helpful. For example, students can create simple websites or apps, or build mini robots using boards like Raspberry Pi. These personal projects can be objectively demonstrated by publishing code on Github or submitting to school science competitions. Participating in open-source communities and contributing to open-source projects is also recommended. Contributing code to open source allows collaboration with developers worldwide while gaining actual software development experience, and having publicly available work creates excellent portfolio material.

Related Field Volunteer Work and Other Activities: Consider various creative activities related to AI beyond just coding. For example, challenging yourself in science olympiads or math competitions helps build foundational academic capabilities. You can also plan volunteer projects that use AI to solve community problems (e.g., volunteering to teach seniors how to use AI speakers at senior centers). These activities provide a foundation for growing into an engineer with social responsibility.

Activity Tip: College admissions officers want to see passion and achievement in the intended major through extracurricular activities. Therefore, guide your child to participate continuously and deeply in a few activities from the above list that interest them. Having even one or two projects that they led and created results from can be a major strength in admissions. Additionally, mentoring from teachers through these activities, competition awards, and recommendation letters will also help with college preparation.

Conclusion: For Our Children Preparing for the Future

The future that today’s students will face is rapidly changing due to AI and other advanced technologies. However, the core remains unchanged. The capabilities needed in any era are the ability to learn new things and the creativity to solve problems. High school is the time to develop these fundamental learning abilities and attitudes. Parents should guide their children to explore their own interests while using the directions suggested in this article as reference to prepare for promising future fields in a balanced way.

The American education system is open. The experiences of trying various challenges and going through failures and successes during high school will be great assets even after entering college. Fields that will survive and thrive 10 or 20 years from now certainly exist. Today’s small efforts and choices will come together to determine the big direction so that our children can ride the waves of the AI era. With parents’ consistent interest and support, we hope that children can prepare for the coming future with anticipation rather than fear.

Thank you.

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