Кто будет зарабатывать больше всех в ближайшие 5 лет (и куда лучше не идти)

Summary

The video’s central business principle is that money is moving away from tasks AI can perform on its own and toward people who use AI to do work that still requires human judgment, domain expertise, or accountability. The presenter argues that AI is more likely to reshape many jobs than eliminate them outright, but it is already changing entry-level hiring.

Market Signals and Key Metrics

• In Russia in March, there were nearly 23 résumés per IT vacancy, compared with HeadHunter’s typical competition range of 4–8. IT vacancies were down about one-third year over year.
• A Stanford study of US payroll data, as described in the video, found a sharp drop in hiring young workers in roles where AI can do the work. At the latest measurement, hiring was nearly 20% below expectations. The presenter says this decline was not evident in roles where AI assists workers.
• Employers worldwide reportedly pay almost 60% more for AI skills. The premium in Russia is currently around 5–15%, suggesting the local market may still be early in valuing those skills.
• Habr Career salary figures are self-reported medians, including bonuses. HeadHunter vacancy figures are generally lower and listed before tax.

Roles the Presenter Sees as Growing

Indicative Russian salary medians cited in the video:

• Machine-learning engineers and data scientists: About ₽220,000, with experienced specialists near ₽370,000. Entry requirements are high—programming plus strong mathematics—and few openings are aimed at beginners.
• Data engineers: About ₽250,000. They build the data pipelines that AI products depend on.
• DevOps, SRE, cloud, and MLOps specialists: SRE is cited at about ₽300,000, among the highest-paid non-managerial roles. MLOps may pay more, but the speaker says there is not enough data for a reliable median.
• Cybersecurity specialists: Application security specialists earn about ₽270,000. Positive Technologies estimates a Russian shortage of roughly 50,000 specialists, expected to worsen by 2027. However, the shortage is mainly for experienced workers, and security vacancies on Habr reportedly fell 40% in six months.
• Experienced backend developers: About ₽250,000. The speaker argues that AI increases the leverage of senior engineers, who can now do work that previously required a senior and roughly two junior developers.
• Product managers: About ₽290,000. As AI makes building cheaper, deciding what to build and for whom becomes more valuable. The speaker points to an emerging niche for product managers who understand both users and AI.
• Product analysts: About ₽250,000. AI speeds up tasks such as database queries, but interpretation and product judgment remain human work.
• Developers in banking and fintech: The WEF ranks fintech engineers highly for growth. The speaker cites developer medians above ₽360,000 at some companies and says similar work can pay about 1.5 times more in a bank than in a small agency.
• Test automation engineers: About ₽225,000, compared with about ₽130,000 for manual testers. The video presents automation as a practical way to move from a more exposed role into higher-value work.
• AI implementation for small and microbusinesses: An emerging, not-yet-standardized role helping businesses such as dentists, repair shops, and language schools apply AI. The presenter describes sending a prospective client an AI-assisted analysis of where the business was losing money. After reviewing it himself, he won a ₽160,000 project.

The presenter also gives a personal example of assembling and selling a service for ₽1 million within a week, without programming. He uses it to argue that people can test an offer and find customers directly rather than relying only on job applications.

Roles to Approach Cautiously

These are the presenter’s assessments, not claims that the occupations have disappeared:

• Frontend as a first job: Very few “Junior Frontend” vacancies nationwide; the cited median is about ₽86,000. Experienced frontend developers can still do well, but AI-generated interfaces make it a tougher entry point. Suggested paths include deepening product or design skills, or moving toward backend and AI-related work.
• Manual testing: About ₽130,000, compared with ₽225,000 for automation. The recommendation is to learn automated testing as the closest transition.
• Industrial engineering: Habr Career median around ₽110,000, reportedly down from ₽125,000 a year and a half earlier. HeadHunter offers cited are ₽60,000–₽90,000, with around ten vacancies nationwide using that title.
• Copywriting and editing without AI: Vacancies for copywriters, editors, and proofreaders reportedly fell about 40% over two years; the copywriter median is around ₽75,000. The suggested shift is from producing text to understanding the marketing strategy behind text that converts.
• Traditional graphic design: Median around ₽100,000. The speaker contrasts this with product design—designing how a product works—which he says pays over ₽200,000.
• Other areas flagged: Call-center operators and routine accounting, which the speaker says are particularly exposed to AI.

The video also cautions against assuming that technology roles are the only source of opportunity. In Russia in March, doctors had fewer than 2.5 résumés per vacancy, compared with 23 for IT. The WEF forecast cited in the video expects many new jobs by 2030 among farmers and delivery drivers as well as technology workers.

Business and Career Playbook

• Use AI to augment a profession, rather than treating “prompt engineering” as a standalone career plan. Combine AI with expertise in areas such as accounting, law, analytics, or marketing.
• Choose the industry as well as the job title. Compensation for similar work can vary substantially between banks, large technology companies, and small agencies.
• Prioritize work involving judgment, system design, and accountability. Examples include deciding what a product should do, building reliable data systems, and verifying that software works safely.
• For early-career workers, treat the first job as the main bottleneck. Build demonstrable experience and move toward higher-skill work—or create a small product or service and show it to prospective customers.
• Validate demand with a concrete offer. The presenter’s example is an AI-assisted business analysis sent directly to an owner, followed by a paid project. The practical lesson is to demonstrate a business outcome rather than wait for a job title or formal hiring process.
• Expect AI to change tasks before it removes whole occupations. A Russian HSE analysis cited in the video suggests task changes are more likely than complete job elimination for most professions.

Presenter and Sources

Presenter: Aren Zakria (also rendered as Aren Zakaryan in the subtitles), an entrepreneur building AI products and communities.

Sources cited: HeadHunter (hh.ru); Habr Career; World Economic Forum, Future of Jobs Report 2025; Stanford Digital Economy Lab; Anthropic; PwC; Positive Technologies; and research from Russia’s Higher School of Economics.