STRATEGIC MANAGEMENT IN THE AGE OF GENERATIVE ARTIFICIAL INTELLIGENCE: ADAPTATION OR DISRUPTION?

Authors

  • Rafael Desconsi Author

DOI:

https://doi.org/10.56238/arev7n7-108

Keywords:

Generative Artificial Intelligence, Strategic Management, Innovation, Disruption, Organizational Adaptation

Abstract

Generative Artificial Intelligence (GAI), represented by technologies such as advanced language models, image generation, creative automation, and predictive analytics, has emerged as one of the most transformative forces of the 21st century. Its ability to produce original content with a high degree of autonomy is directly impacting strategic management models across organizations of all sizes and sectors. This article investigates how Brazilian companies are incorporating GAI into their decision-making processes and long-term strategies, considering two main approaches: adaptation, characterized by the gradual integration of the technology into existing models, and disruption, understood as the complete restructuring of organizational frameworks and business models.

Using a qualitative approach based on a literature review and interviews with managers and experts from medium and large companies, the study aims to identify emerging patterns, challenges, and opportunities. The results indicate that companies adopting a disruptive posture—reorganizing structures and encouraging experimentation—tend to show greater innovation and competitiveness. On the other hand, organizations taking an adaptive approach may reduce risks but struggle to keep pace with market speed and changing consumer behavior. The article concludes that strategic management in times of GAI requires a new mindset that balances risk and boldness, planning and flexibility, while also considering the ethical, social, and human dimensions of technological transformation.

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Published

2025-07-08

Issue

Section

Articles

How to Cite

DESCONSI, Rafael. STRATEGIC MANAGEMENT IN THE AGE OF GENERATIVE ARTIFICIAL INTELLIGENCE: ADAPTATION OR DISRUPTION?. ARACÊ , [S. l.], v. 7, n. 7, p. 37113–37122, 2025. DOI: 10.56238/arev7n7-108. Disponível em: https://periodicos.newsciencepubl.com/arace/article/view/6480. Acesso em: 5 dec. 2025.