- AI is changing research roles, as newcomers are expected to become “system engineers,” combining AI and human thinking to coordinate projects.
- The research industry is shifting to a hybrid model where AI supports analysis while humans focus on strategic thinking and storytelling.
- However, junior work is at risk of turning into managing and training AI instead of direct observation, analysis, and hands-on experience.
- Previously, skills were built through debate, observation, interviews, and deep analysis—”slow” experiences that helped develop intuition.
- AI helps accelerate and scale up, but it may lead to the loss of critical deep-thinking and exploration phases.
- The risk is that researchers become “messengers of AI results” rather than interpreters of human experience.
- Future roles are polarized: being both an AI-controlling engineer and a strategic advisor capable of storytelling and influence.
- A major challenge is the lack of an environment to train critical thinking and real-world perception for the new generation.
- Core human values still lie in the ability to create emotion, empathy, and deep understanding of experience—things AI cannot yet replace.
📌 AI is upgrading the research industry but simultaneously eroding the foundation of traditional training. As entry-level researchers shift toward the role of “system engineers,” they may lose the chance to hone their intuition and deep thinking. The future is not about AI replacing humans, but about the requirement for humans to become the bridge between data and emotion. Without investing in these skills, the research industry risks losing the essence of understanding humanity.
