What to Learn When AI Already Knows Everything

Every year, September 1st follows a familiar format in Armenia: white shirts, bouquets, and the first school bell. This year, however, that ritual comes with a question that, until recently, had little place in the classroom: What should we teach in a world where machines can already write, calculate, code, and analyze, and are advancing faster than education systems can adapt?

This is no longer simply a question for educators. It is a question of national competitiveness, particularly for Armenia, where the technology sector has become one of the country’s main drivers of economic growth over the past decade.

The Gap Between Market Demand and Supply

Global data points to a clear mismatch: demand for AI-related skills is growing far faster than the supply of qualified professionals.

According to ManpowerGroup’s 2026 global research, AI skills have become the most difficult for employers to find, overtaking traditional engineering and IT skills for the first time. A 2026 analysis by the International Monetary Fund (IMF) found that approximately half of all job openings in emerging economies require at least one new digital or technological skill, compared with roughly 10% in advanced economies. In other words, labor markets in emerging economies are changing faster than their education systems can respond.

This global trend is directly reflected in the local market as well. Eleveight AI’s experience demonstrates how major AI infrastructure projects create demand for highly skilled professionals across a wide range of disciplines. AI data centers and computing platforms require network architects and senior server infrastructure engineers, as well as specialists in cooling, ventilation, and electrical systems. Eleveight AI draws this talent from Yerevan, Hrazdan, Dilijan, Sevan, and Gagarin, where the company’s AI factory is located.

According to company data, senior specialists make up the majority of Eleveight AI’s core team, while junior professionals account for approximately 20% of its workforce. This structure creates a natural mentorship environment, giving recent engineering graduates and students already working in the field the opportunity to learn from experienced professionals and gain hands-on experience with advanced AI infrastructure.

To support their continued professional development, Eleveight AI specialists regularly attend training sessions, seminars, and technical workshops across Europe, including in the Netherlands, Germany, and Italy. They then bring the knowledge, practices, and technical standards gained through these programs back to Armenia.

Five Emerging Specializations for Armenia’s Education System to Consider

Drawing on both global trends and Armenia's current situation, five directions can be identified where sector demand will steadily grow.

AI Infrastructure and MLOps Engineer: These professionals manage and optimize GPU clusters and scale the pipelines used for model training and inference. The development of infrastructure such as the Yerevan State University (YSU) supercomputer and Eleveight AI’s AI factory will create direct demand for this expertise.

Applied (Vertical) AI Engineer: Rather than developing foundation models, these specialists adapt and integrate existing AI systems into specific sectors, such as agriculture, healthcare, finance, and manufacturing. Armenia already has early examples, including agritech startups using AI for apiary management and precision spraying. However, this expertise is still largely being developed through self-directed learning rather than formal education.

AI Governance, Risk, and Compliance Specialist: Global trends show that a growing number of companies delay or halt AI projects because they lack the expertise required to ensure effective governance, transparency, and regulatory compliance. With a relatively small but well-trained pool of specialists, Armenia could build a meaningful competitive advantage in this field.

Armenian-Language Data and Language Model Specialist: Initiatives such as the Armenian text-to-speech model developed by Async (formerly Podcastle) demonstrate that building high-quality AI tools requires expertise at the intersection of linguistics, data curation, and machine learning. Armenia has a natural advantage in this area, yet very few university programs currently prepare students for this kind of work.

AI Product/UX Interaction Specialist: As AI models become more capable, their value increasingly depends on how effectively they are integrated into real-world products and workflows. Positioned at the intersection of technology, product management, and user experience, this could become one of the most sought-after specializations, particularly for people with strong analytical and problem-solving skills.

The Role of the AI Factory: Local Computing Power as an Educational Catalyst

Behind all this lies a question that often remains in the shadow. Even if universities train the necessary specialists, who will provide the computing power they need to learn, experiment, and conduct advanced research?

This is where locally available AI infrastructure can play an important role. The August 2025 Memorandum of Understanding between the governments of Armenia and the United States on an innovative partnership in AI and semiconductors signaled a growing national focus on this field. With Eleveight AI deploying NVIDIA Blackwell B300 GPUs, some of the world’s most advanced AI computing technology is now being deployed within Armenia.

The value of this infrastructure, however, lies not only in the scale of the investment but also in how its computing capacity serves the local ecosystem. Making advanced infrastructure available to students and early-career researchers can turn the status of being a “country with an AI factory” into tangible benefits for Armenia’s education and research systems.

Local computing power can make a measurable difference in three areas:

Faster experimentation: Greater computing capacity can reduce the time required for complex experiments from days to hours. This allows students and researchers to test more ideas, learn faster, and reach meaningful results sooner.

Larger-scale research: Tasks such as fine-tuning large models, running complex simulations, and analyzing large datasets become more feasible, expanding the scope of research that can be conducted in Armenia.

Talent retention: Access to high-performance computing within Armenia removes an important barrier for young engineers and researchers who might otherwise need to pursue advanced work and research opportunities abroad.

As another academic year begins, Armenia has an opportunity to build on its strong technical talent by connecting education more closely with the new roles emerging around AI. Relevant specializations, closer cooperation between universities and industry, and access to advanced local computing infrastructure can give students and researchers more opportunities to apply their knowledge and develop globally competitive expertise. With talent, education, and infrastructure moving forward together, Armenia is well positioned to turn its growing AI capacity into new knowledge, meaningful careers, and long-term value for the country