Citation

Bukar, Umar Ali and Sneesl, Radhwan (2025) Resilience Thinking Artificial Intelligence Integration Framework. The Smart Life Revolution, 1. pp. 1-20. ISSN 9781003509196

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Abstract

This chapter discusses the architecture, applications and integration of Artificial Intelligence (AI), providing a foundation for conceptualising the Resilience Thinking Artificial Intelligence Integration Framework (RTAIF). The RTAIF explores the concept of resilience in the context of AI integration, focusing on how individuals, organisations and societies can effectively absorb, adapt and transform in response to the challenges and opportunities presented by AI technologies. The RTAIF outlines three key capacities for resilience: absorption, adaptation and transformation. Absorption is discussed as the initial capacity to withstand AI-related disruptions without significant alterations to core functions and structures, emphasising the importance of maintaining stability and continuity. Adaptation is highlighted as a proactive response, involving adjustments to practices, strategies and structures to better align with the evolving AI landscape. This capacity requires flexibility, learning from experience and modifying approaches to harness AI's benefits while managing its ethical concerns. Transformation, the highest level of resilience, is examined as a comprehensive overhaul of existing systems and mindsets, aimed at not only surviving AI's impact but thriving in a future where AI is deeply integrated into societal functions. This section explores the fundamental conditions for transformation, including communication, the ability to unlearn and relearn, adoption and adaptation strategies, mindset shifts, the choice of appropriate technologies and tools, and continuous process improvement. Through detailed discussions and examples, this chapter discusses RTAIF for understanding and enhancing resilience in the face of AI integration, offering valuable insights for stakeholders across various sectors aiming to navigate the complexities of the AI era effectively.

Item Type:	Article
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions:	Others
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	30 Jun 2025 08:13
Last Modified:	30 Jun 2025 08:13
URII:	http://shdl.mmu.edu.my/id/eprint/14183

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