Evaluating Generative AI Initiatives in Human Resources: Multiple Criteria Decision Analysis
DOI:
https://doi.org/10.52812/msbd.111Keywords:
Generative Artificial Intelligence, Human Resource Analytics, Analytical Ordinal Priority Approach, Grey Relational Analysis, Multiple Criteria Decision Analysis, Generative AI, GenAIAbstract
The current study introduces a systematic framework to address the critical challenge of prioritizing Generative Artificial Intelligence (GenAI) initiatives within Human Resources (HR) Management. Confronted with multiple high-potential yet resource-intensive options, HR leaders require an objective method for strategic investment. The study employs a Multi-Criteria Decision-Making (MCDM) methodology, integrating the Analytical Ordinal Priority Approach (AOPA) and the Dynamic Grey Relational Analysis (DGRA). Ten distinct GenAI use cases are identified and evaluated against eleven strategic criteria—spanning impact, feasibility, risk, and organizational momentum—based on the judgments of a diverse panel of experts from HR, Information Technology, Finance, Legal, and Operations. The results yield a validated, consolidated ranking of initiatives. The Employee Sentiment & Trend Analyzer emerges as the highest-priority initiative, followed by the Intelligent HR Helpdesk Chatbot and the Automated Recruitment Coordinator, while the Interactive Leadership Training Simulator is consistently ranked lowest. The study provides HR leaders with a transparent, data-driven framework for phased implementation, advocating for initial investments in initiatives that balance strategic value, strong return on investment, and manageable risk to build organizational confidence and momentum in the adoption of transformative AI technologies.
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