Designing an AI-Driven Talent Intelligence Solution: Exploring Big Data to extend the TOE Framework
This addresses talent management issues for organizations, but it is incremental as it builds on existing frameworks with AI enhancements.
The study tackled the problem of improving talent management by developing an AI-driven solution for career guidance, resulting in a design artifact that integrates machine learning techniques within a moderated technology-organization-environment framework.
AI has the potential to improve approaches to talent management enabling dynamic provisions through implementing advanced automation. This study aims to identify the new requirements for developing AI-oriented artifacts to address talent management issues. Focusing on enhancing interactions between professional assessment and planning attributes, the design artifact is an intelligent employment automation solution for career guidance that is largely dependent on a talent intelligent module and an individuals growth needs. A design science method is adopted for conducting the experimental study with structured machine learning techniques which is the primary element of a comprehensive AI solution framework informed through a proposed moderation of the technology-organization-environment theory.