AI Drives Salaries Higher: How Digital Skills Are Reshaping Job Offers

The ability to work with artificial intelligence is pushing salary offers higher across job listings. According to data from the online university Zerocoder, vacancies that mention neural networks and AI tools consistently offer better pay than those that do not. IT RUSSIA spoke with Zerocoder co-founder Kirill Pshinnik about the findings.

– The study covered 2,544 job listings, including both roles that mention neural networks and those that do not require AI skills. The comparison shows that across most professional clusters, AI competencies are linked to higher salary ranges. If we exclude the Data Science segment, the average salary offer in roles requiring AI skills stands at 116,100 rubles (approximately $1,530), compared to 96,600 rubles (approximately $1,270) in roles without such requirements. In other words, the market values applied AI skills at roughly a 20% premium.

– What about digital fields specifically?

– The effect is especially clear in marketing, data analytics, and SMM. For marketers, the average salary range in vacancies requiring AI skills is 101,500–152,000 rubles (approximately $1,340–$2,000), compared to 88,100–116,500 rubles (approximately $1,160–$1,530). For data analysts, the gap is even more pronounced: 133,300–201,800 rubles (approximately $1,750–$2,660) versus 115,500–147,400 rubles (approximately $1,520–$1,940). SMM managers with AI skills also see stronger offers: 78,600–115,400 rubles (approximately $1,030–$1,520), compared to 74,100–93,200 rubles (approximately $970–$1,230). In practical terms, that translates into salary increases of about 27.5% for data analysts, 25% for marketers, and 16% for SMM professionals.

– What about creative roles, like design?

– For designers, the gap is less pronounced but still noticeable. Vacancies that require AI competencies offer an average salary range of 90,400–116,000 rubles (approximately $1,190–$1,530), compared to 76,600–117,500 rubles (approximately $1,010–$1,550) in roles without any mention of neural networks. This suggests that for designers, AI is already starting to be seen as a practical working tool – one that increases speed and creative variation – but it does not yet consistently lead to a sharp rise in the upper end of the salary range.

Among early-career generalists, the difference is also present, although less significant. This points to an important trend: even at the entry level, employers increasingly expect candidates to have at least a basic command of modern AI tools.

– What about programming roles? Are neural networks a requirement there?

– The Data Science and developer cluster turned out to be the only notable exception. In this segment, vacancies that do not explicitly mention neural networks show a higher average salary range than those that list AI competencies: 201,400–237,200 rubles (approximately $2,650–$3,120) versus 150,900–203,600 rubles (approximately $1,990–$2,680). This distribution likely reflects the structure of the roles themselves. In this professional group, AI is often specified in more numerous junior positions, while a portion of mid-level and senior roles with higher salaries are described without highlighting neural networks as a distinct skill. As a result, this cluster can distort the overall picture and requires separate analysis.

– Which tools should candidates learn to qualify for higher salaries?

– The most commonly mentioned tools include ChatGPT, Midjourney, Claude, Stable Diffusion, DALL-E, Gemini, Cursor, and GigaChat. Each professional field is developing its own stack of in-demand solutions.

In marketing, design, and SMM, generative tools for content and visual creation are leading the way. For data analysts and developers, the demand structure looks different: employers are more often looking for specialists familiar with LLMs, Claude, Cursor, language models, and applied uses of AI in analytics and software development.

– How do you assess this trend overall? Is it a passing trend or a deeper change in the labour market?

– AI skills are moving from a fashionable add-on to a practical competency that directly affects the economics of hiring. Employers are not paying for the mere fact that a candidate is familiar with neural networks, but for the ability to use them in day-to-day work – to speed up content production, improve analytical accuracy, automate routine tasks, and enhance outcomes within a specific function.

Today, AI operates as a layer on top of a profession. It is particularly effective at increasing a candidate’s value in roles where results can be scaled more quickly through automation, generative tools, and intelligent assistants. Professionals who know how to apply AI in practice tend to command higher salaries. For employers, this skill is increasingly shifting from a bonus to a baseline expectation.