Theorizing Generative AI’s Role in Strategic Decision-Making: From Automation to Augmentation

Generative artificial intelligence (GenAI) is profoundly reconfiguring strategic decision-making models within large-scale organizations. However, its theoretical implications within service science and organizational science remain emerging. The prime purpose of this study is to synthesize service science doctrines with the management theory domain to develop a conceptual framework that positions GenAI as an agent of value co-creation in strategic processes, excelling its conventional position as a decision-support instrument. Grounded in service-dominant logic and bounded rationality theory, this study theorizes GenAI’s dual capacity role to augment human cognitive faculties through real-time scenario simulation, heterogeneous data synthesis, and predictive analytics while concurrently familiarizing systemic risks, comprising the perpetuation of latent biases inherent in training data and organizational over-reliance dynamics. By combining empirical case analyses with theoretical modelling, this study reveals how GenAI-mediated decision structural design reconfigures service systems, prompting decision velocity at the expense of ethical and epistemic accountability. This proposed conceptual framework suggests that GenAI’s transformative potential lies in its capability to operationalize augmented intelligence, wherein human-AI symbiosis fosters adaptive, data-driven strategic agility while imposing robust governance instruments to alleviate algorithmic opacity and stakeholder dissonance. The study practically contributes to the interdisciplinary discourse on AI-enabled service innovation by recommending testable hypotheses regarding GenAI’s impact on strategic foresight, resource orchestration, and organizational resilience, thereby projecting a research agenda for the responsible integration of generative technologies in enterprise strategic decision ecosystems.