The information technology field shifts rapidly as new tools, platforms, and architectures emerge. Industry observers, including EdTech entrepreneur Alexey Koledachkin, watch the conversation about automation closely, noting that while AI changes many roles, it does not erase the need for human expertise. The pace of change pushes teams to learn continuously, blending software engineering, data science, and governance in ways that demand constant adaptation.
Right now, artificial intelligence can handle a broad range of tasks once believed to be uniquely human. It can draft simple program code, sift through enormous data sets, craft marketing plans, and assist in diagnosing diseases. Modern AI models learn from vast amounts of data and improve with each new encounter, turning experience into capability and enabling faster decision cycles across many domains.
Some IT roles have already evolved under automation, and some have been quietly replaced by AI, at least in routine layers of work. The shift is real, but not a wholesale replacement; it tends to remove repetitive tasks while leaving space for roles that require judgment, design, or oversight.
“Customer support is being reshaped,” Koledachkin notes. “Chatbots and automated help desks handle many frontline inquiries. They can resolve routine questions, provide essential information, and even perform basic operations, which reduces the need for large support staffs.”
Additionally, AI excels at routine data operations such as sorting, filtering, and basic analysis when dealing with big data. Machine learning systems can process information faster and more reliably than humans in many cases, trimming the amount of manual work that employees must perform and speeding up insights across business units.
“In some scenarios, AI can produce basic code and tackle entry level development tasks. Low‑code and no‑code tools let users without deep programming knowledge create simple applications, which lightens the load on developers for repetitive tasks while opening new possibilities for domain experts to contribute directly.”
Yet even with automation rising, there are domains where the human touch remains essential. A number of IT professions resist full automation because they rely on creative thinking, nuanced problem solving, and the ability to weigh competing constraints.
“System architects and developers of complex solutions fall into this category. Designing high‑level architectures, integrating multiple technologies, and steering large projects require foresight, experience, and cross‑disciplinary understanding that AI cannot fully replace yet,” he adds.
Test automation continues to progress, but testers who handle critical systems—such as medical devices or aerospace components—remain indispensable. These professionals review products from multiple angles, spot nonstandard errors, and perform in‑depth security and functionality analyses that automated checks alone may miss.
While AI can identify known threats and analyze data patterns, information security still demands strategic thinking, creativity, and ethics. Experienced cybersecurity professionals stay vital for developing protective measures against evolving and unknown threats.
Team leaders, product managers, and project managers must juggle many factors, from direct interactions with customers to coordinating work across diverse teams. In these roles, human communication skills, emotional intelligence, and strategic planning ability remain essential assets for delivering successful outcomes.
Earlier trends showed many remote workers blending travel with work, a pattern that has continued as teams adapt to distributed environments. The overall message from industry experts is clear: success depends on continuous learning, strategic specialization, and the ability to align automation with real business needs.