Czy AI zastąpi zawód: kierownik ds. badań technologii informacyjno-telekomunikacyjnych?

Kierownik ds. badań technologii informacyjno-telekomunikacyjnych faces very high AI disruption risk with a score of 79/100, primarily due to automation of data processing and analytical tasks. However, this role will not be replaced entirely—AI will transform rather than eliminate it. Leadership, research planning, and innovation in emerging technologies remain distinctly human strengths, making hybrid human-AI teams the likely future model.

Czym zajmuje się kierownik ds. badań technologii informacyjno-telekomunikacyjnych?

Kierownicy ds. badań technologii informacyjno-telekomunikacyjnych oversee research initiatives in ICT, planning and managing technical investigations while monitoring emerging technological trends. They evaluate the strategic significance of new developments in information and communication technology, develop staff training programs, and provide technical direction. This role combines strategic foresight, team leadership, and deep technical knowledge to guide organizational ICT research priorities.

Jak AI wpływa na ten zawód?

The 79/100 disruption score reflects a polarized skill landscape. Routine analytical work—data processing (54.93 vulnerability), LDAP administration, information extraction, and mathematical calculations—faces immediate automation pressure. Task automation is moderate (48.91/100) because research leadership inherently requires human judgment. However, AI complementarity is strong (72.74/100), meaning these leaders will increasingly partner with AI tools. Literature research, data mining, and statistical analysis are becoming AI-enhanced rather than displaced. Conversely, emergent technology awareness, business relationship building, and systemic design thinking remain resilient (core leadership competencies). Near-term: operational efficiency gains as AI handles data preprocessing. Long-term: the role evolves toward strategic technology assessment and innovation governance rather than tactical research execution.

Najważniejsze wnioski

• Routine data analysis and mathematical computations will be heavily automated, reducing time spent on technical groundwork.
• Leadership, strategic planning, and research innovation remain inherently human—these are the future core of the role.
• AI-enhanced research tools (literature analysis, data mining, statistical modeling) will augment rather than replace human researchers.
• Success requires upskilling in emerging technology evaluation and AI-human collaboration management, not protection from displacement.
• Organizations will need fewer traditional research managers but more who can synthesize AI-generated insights with strategic vision.

Wynik zakłócenia AI NestorBot obliczany jest na podstawie 3-czynnikowego modelu wykorzystującego taksonomię umiejętności ESCO: podatność umiejętności na automatyzację, wskaźnik automatyzacji zadań oraz komplementarność z AI.