Title: METHODS TO ASSESS AND DEVELOP AI-READY COMPETENCIES ACROSS TECHNICAL AND NON-TECHNICAL TEAMS
Author:
Syrotenko Viktoriia
Abstract:
Objective: The organization is trying to determine and educate a mixture of technical and socio-gamous abilities that make teams sincerely prepared for AI. This document seeks to distill reliable methods for evaluating and developing these capabilities in mixed professional groups.
Methods: Integrative evaluation of the harvested fifteen reviewed empirical research published in 2021 and 2025. The use of a socio-technical lens was coded in addition to 5 dimensions-design, dimensions tool, sample profile, intervention and final results of meters-to-ate.
Results: Evidence closer to three families: AI literacy evaluation, self -defense of readiness and overall performance simulation. While the literacy tests provide granularity, the simulation of higher switching gaps between the encoders and the patron with a group of workers. Development strategies are clustered into modular knowledge of micro-sanding, place of mentoring and mixed quarantine AI; The most continuously increases technical fluency and ethical judgment. In particular, context-management moderators with management, maturity of facts, psychological safety-integrate effects up to 0.35, which indicates that the tools on one length are omitted.
Conclusions: The synthesis of heterogeneous evidence provides a four-stage cycle-a audit of the brand, holes analysis, tailor-made, iterative re-evaluation-which can be introduced into the current HRIS dashboard. Future longitudinal experiments should verify predictive electricity cycle for innovation and maintenance, especially in resources limited. Such work will improve taxonomy of competencies and will say evidence route for international groups.
Keywords: Readiness AI; Competence assessment; Literacy AI; increasing strategy; Passfunction groups; Socio-technical HR; Integrative evaluation.
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