Assessing Readiness for AI-Human Integration Using a Hesitant Fuzzy Analytic Hierarchy Process: An Application in the Banking Sector

Abstract

With AI being incorporated into the core functions of organizations, understanding whether or not an organization is ready to work in conjunction with humans using AI will continue to grow in importance. Therefore, this study proposes a multi criteria decision making (MCDM) based methodology to aid firms in evaluating their potential for successful integration of AI and human capabilities. An “AI-Human Integration Readiness Index” is developed to provide a systematic means to evaluate the various capabilities regarding to AI utilization. In order to handle uncertainty and hesitation when experts are making assessments of an organization’s readiness, the proposed methodology uses the Hesitant Fuzzy Analytical Hierarchy Process (HFAHP) as a novel MCDM method. A total of four primary dimensions were used in developing the model which were established from conducting a thorough review of existing literature: (1) Strategic Alignment & Value Realization Readiness, (2) Data & Technical Infrastructure Readiness, (3) Human Capital & Adaptation Readiness, and (4) Trust, Governance & Institutional Legitimacy Readiness. The resulting index not only quantifies an organization’s current state of readiness but also acts as a diagnostic tool to assist organizations in identifying areas where they may require additional support or training.

Keywords

• Multi-criteria decision making
• AI-human integration
• AI-human integration readiness level
• Hesitant fuzzy analytical hierarchy process

Ethical Statement

Ethics committee approval was not required for this study because there was no study on animals or humans.

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