AI and Education: What to Learn When AI Knows Everything

What are we teaching in the AI era? Education, the labor market and the AI factory in Armenia

Every year, September 1 in Armenia follows a familiar format: white shirts, bouquets of flowers, the first bell. But this year, behind that same ritual stands a question that until recently wasn't on the school agenda: what are we teaching in a world where a machine can already write, calculate, code and analyze faster than we can teach people to do it?

This is no longer just a question of AI and education, but of national competitiveness, especially for Armenia, where the tech sector has become one of the main drivers of economic growth over the past decade.

The AI Skills Gap: Market Demand vs. Supply⁠

Global data shows a clear pattern: demand for AI-related skills is growing much faster than the market can train competent professionals.

• According to ManpowerGroup's 2026 global survey, AI skills have for the first time become the hardest capability for employers to find, overtaking traditional engineering and IT roles.
• According to a 2026 analysis by the International Monetary Fund (IMF), in developing economies roughly half of all job vacancies require at least one new digital or technological skill (in developed countries this figure is around 10%).

In other words, the labor market in developing economies is transforming faster than education systems can adapt.

This global trend is directly reflected in the labor market in Armenia too. As the experience of Eleveight AI shows, infrastructure projects like this are creating new demand for highly qualified specialists. In particular, AI data processing centers and server platforms are already drawing on a wide range of professionals, from network architects and senior server infrastructure engineers to cooling, ventilation and electrical systems engineers, coming from Yerevan as well as from Hrazdan, Dilijan, Sevan and Gagarin itself, where the company's AI factory is located.

According to Eleveight AI, senior specialists make up most of the team's core, while junior staff account for about 20% of the workforce. This creates a mentoring environment in which young engineers, whether recent graduates or working alongside their studies, get the chance to work with some of the most advanced technologies in the world right now.

At the same time, to ensure the continuous development of its staff, Eleveight AI specialists regularly take part in training, seminars and technical workshops in several European countries (including Amsterdam, Germany and Italy), bringing global standards back to Armenia.

AI and Education: 5 New Specializations to Build into Study Programs⁠

Based on both global trends and Armenia's current situation, we can single out 5 areas for which demand in the sector will keep growing:

1. AI infrastructure and MLOps engineer. Specialists who can manage and optimize GPU clusters and scale training/inference pipelines for models. The launch of infrastructure such as the Yerevan State University (Երևանի պետական համալսարան, YSU) supercomputer and the AI Factory will naturally create priority demand for this field.
2. Applied (vertical) AI engineer. Not someone who builds foundation models, but a specialist who can integrate existing AI tools into a specific industry: agriculture, medicine, finance or manufacturing. Armenia already has its first examples (for instance, agritech startups that use AI for apiaries or precision spraying), but they are growing thanks to self-taught specialists, not with the support of the education system.
3. AI safety, risk and regulation specialist (AI Governance). As global trends show, a growing share of companies are blocking AI projects precisely because they lack specialists in governance, transparency and compliance. This is a field where Armenia could build a competitive advantage worth noticing, even with a small but well-trained group of specialists.
4. Armenian-language data and language model specialist. Examples such as the Armenian Text-to-Speech AI model developed by Async (formerly Podcastle) show that building quality AI tools requires a special skill set at the intersection of linguistics, data curation and machine learning. This is a field where Armenia has a natural advantage, yet in practice almost no university program is training specialists with this profile.
5. Human-AI interaction and product specialist (AI Product/UX). The more powerful models become, the more it matters how they are integrated into real work processes. Sitting at the intersection of technology, product management and user experience (UX), this field could become one of the most in-demand, especially for people with a deeply analytical mind and a clear understanding of the problem.

The Role of the AI Factory: Local Computing Power as a Catalyst for Education⁠

Behind all of this stands a question that often stays in the shadows: who will provide the computing power once universities and researchers finally have the specialists but not enough infrastructure?

This is where the AI Factory comes in as a partner. Following the August 2025 memorandum of understanding between the governments of Armenia and the United States on an innovation partnership in AI and semiconductors, the country has seen an accelerated expansion of AI infrastructure. With Eleveight AI bringing NVIDIA Blackwell B300 GPUs online, Armenia has direct access to one of the most powerful technologies in the world.

But just as important as the scale of investment is how this capacity will serve the local ecosystem. This is the very link that can turn the status of "a country with an AI factory" into a real, tangible benefit for Armenia's research and education system, becoming a tool that students and young researchers in Armenia can turn to.

The real, measurable impact of having local computing power on a specialist's productivity shows up in three specific ways:

• Speed. A single experiment takes hours instead of days, so a specialist can run far more experiments, which speeds up both learning and the path to real results.
• Larger-scale problems. Fine-tuning large models, multi-layered simulations and large-scale data analysis become feasible, which opens up new directions for research.
• Keeping specialists in the country. When quality computing power is available in Armenia, one of the main reasons young engineers and researchers move abroad carries less weight.