Rethinking Talent Cultivation in the Age of Artificial Intelligence: A Theoretical Framework Based on Capability Reconstruction

DOI

10.2991/978-94-6239-766-8_20How to use a DOI?

Keywords

Artificial Intelligence; Talent Cultivation; Capability Reconstruction; Human Capital; Educational Transformation; Simulation Analysis

Abstract

The rapid advancement of Artificial Intelligence has fundamentally reshaped the logic of talent cultivation. Traditional education systems, which primarily emphasize knowledge accumulation and cognitive training, are increasingly challenged by intelligent technologies capable of performing routine analytical, informational, and procedural tasks. Against this background, this paper develops a theoretical framework of capability reconstruction to explain how talent cultivation should be redesigned in the age of AI. The study conceptualizes talent capability as a multidimensional portfolio composed of cognitive capability, digital capability, social-emotional capability, and innovative capability. Building on this framework, a capability reconstruction optimization model is constructed to analyze how AI penetration changes the relative returns to different capabilities and influences institutional training strategies. To further clarify the dynamic implications of the model, simulation analysis is conducted to examine capability revaluation, institutional transformation thresholds, and equilibrium zones under alternative AI scenarios. The results indicate that the relative return to routine cognitive capability declines as AI penetration increases, while digital capability, innovative capability, and social-emotional capability become increasingly valuable. In addition, institutional transformation depends jointly on technological pressure and reform cost, leading to the coexistence of traditional, transitional, and reconstruction equilibria. The findings suggest that the key challenge of talent cultivation in the AI era is not merely the adoption of AI tools, but the strategic reconstruction of capability structures. This study contributes to the literature by extending human capital theory from accumulation logic to reconstruction logic and by providing a new analytical perspective for educational transformation in intelligent societies.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Yuanlin Wu
AU  - Huajun Zheng
PY  - 2026
DA  - 2026/09/04
TI  - Rethinking Talent Cultivation in the Age of Artificial Intelligence: A Theoretical Framework Based on Capability Reconstruction
BT  - Proceedings of the 2026 6th International Conference on Education, Information Management and Service Science  (EIMSS 2026)
PB  - Atlantis Press
SP  - 197
EP  - 212
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6239-766-8_20
DO  - 10.2991/978-94-6239-766-8_20
ID  - Wu2026
ER  -