Orchestrating Big Data and Artificial Intelligence for Adaptive Digital Business Strategy
DOI:
https://doi.org/10.33050/qx8e0j55Keywords:
Artificial Intelligence, Adaptive Digital Business, Orchestration, Big Data, Thematic SynthesisAbstract
The rapid acceleration of digital transformation has changed the way organizations formulate and implement business strategies, requiring firms to become more adaptive, data-driven, and responsive to dynamic market conditions. This study aims to examine how big data and artificial intelligence can be orchestrated as integrated strategic capabilities to support adaptive digital business strategy. Using a qualitative conceptual approach, this study applies a structured literature review and thematic synthesis to analyze previous studies related to big data capability, artificial intelligence capability, governance mechanisms, intelligent business insight, and strategic adaptability. The results show that big data functions as a strategic foundation by providing diverse information from customers, markets, operations, and digital platforms, while artificial intelligence acts as an intelligent decision engine that transforms data into predictions, recommendations, automation, and actionable business insights. The findings also indicate that governance and human decision-making are essential in ensuring that the use of big data and AI remains reliable, transparent, accountable, secure, and aligned with organizational objectives. This study concludes that adaptive digital business strategy emerges from the continuous orchestration of data resources, AI systems, governance structures, human judgment, and strategic execution. The proposed framework contributes to digital business literature by explaining how AI-driven big data orchestration can improve decision quality, agility, competitiveness, innovation, operational efficiency, and sustainable digital value creation. In addition, the discussion is expanded to include cybersecurity, data privacy, secure data processing, and AI risk management as critical enablers of large-scale data-driven business systems.
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Copyright (c) 2026 Marviola Hardini, Sheila Aulia Anjani, Sherli Triandari, Fhia Amelia, Marta Rodriguez
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