With the rise of modern artificial intelligence (AI) systems (incl. large language models, generative coding tools, and automation), the world of IT professionals is undergoing a significant transformation. What seemed like the distant future a few years ago is rapidly becoming reality.
Almost Every IT Job Will Be Affected
According to various research studies, approximately 92% of IT jobs are expected to undergo either a significant or moderate change in the coming years. This shift particularly affects beginner and mid-level specialists: around 37% of entry-level roles and 40% of mid-level roles are likely to be significantly transformed.
What’s Becoming Less Relevant?
Basic programming and repetitive coding tasks. AI systems can now perform many routine and structured tasks.
Data maintenance, documentation, content-level operations, information lookup, and basic SQL administration are also becoming less critical.
Jobs involving predictable, highly structured workflows are the first to be automated.
What’s Becoming More In-Demand?
AI literacy, prompt engineering, and the ability to work with large language models. These are becoming standard across many IT roles.
Data analysis, critical thinking, and decision-making. People who can understand and interpret outcomes, as well as make strategic choices, are highly valuable.
Soft skills: creativity, communication, teamwork, adaptability, and ethical reasoning — all of which AI cannot replicate effectively (yet).
The Latest Studies (as of 2025) Paint a Clear Picture of How IT Work Is Evolving:
97% of IT employees already use generative AI tools in their daily work (coding, assistance, documentation, research, etc.). However, there is also a growing concern: as AI adoption increases, more professionals are becoming uncertain about the security of their jobs.
What Should You Do To Stay Relevant?
Don’t expect stability. If your job revolves around routine coding, maintenance, basic development, or data processing, your role is highly likely to change.
Invest in skills that are hard to automate (analytical, AI-tooling, creative problem-solving, communication, etc.).
Be prepared for continuous learning. Growth areas include AI/ML engineering, data analytics, system architecture, cybersecurity, project management, and systems integration.
AI presents both a challenge and an opportunity to rethink your goals, acquire new skills, and become more valuable.
