Triggers of the Disruption Dynamics Maturity Model: Evaluating the role of Agentic AI as a pertinent Trigger impacting the Dimensions of Disruption

Abstract

Agentic AI has fast emerged as a potent technology promising to transform the businesses pervasively. Business leaders globally are intrigued by this fast-paced development and there is a perceived need to evaluate its impact. Using an integrative literature review, this paper investigates whether Agentic AI could be the next prominent trigger impacting the eight dimensions of the DDM model. The Disruption Dynamics Maturity Model (DDMM) was conceptualized to diagnose the onset of business disruption and help envision possible interventions at strategic or tactical management levels. Building upon a high-level approach, DDMM is empirically applied to diverse business situations capturing emerging scenarios and future possibilities. The DDM Model does an empirical analysis across its eight dimensions which serve as the key factors impacting the Business Disruption, namely: Value elements, Formfactors, Entities, Operating Model, Consumption pattern, Interrelationships, Skill gap, and Regulation. Recently DDM model was applied to some emerging use cases in the regional business environment wherein it empirically demonstrated the extent of Business Disruption in the Construction and Manufacturing Sectors in the UAE. Further, it was envisaged that as more and more scenarios are evaluated using this model, it is likely to reveal various pertinent triggers or forces that cause changes in the dimensions of Disruption Dynamics and impact their maturity levels. This revelation will further aid in understanding the interplay between the eight dimensions and in the diagnosis and interventions towards addressing the complexities of Business Disruption at large. Mainly by analysing the latest applications, use cases, white papers and industry reports, this paper attempts to evaluate Agentic AI as a recognizable trigger for DDMM and hence a possible catalyst to imminent Business Disruption, thereby aiding the business leaders in detecting any early signals of business disruption.