New decision approaches and automated workflow systems are acquired by organizations due to AI development. The Digital-Augmented Agility system is integrated into an information processing organization, where artificial intelligence-managed decision methods are used to improve operational resilience and adaptable workforce system implementation. The ability of AI automation to refine processes in real-time and execute prediction-based decisions cannot be adequately determined through analytical methods from either Dynamic Capabilities Theory or the Theory of Organizational Routines. Researchers assessed financial sector agility using mixed research methods, including quantitative and regression models. Operational efficiency, shorter time-to-market, and superior work-team performance that integrates human resources with AI assets were gained by organizations utilizing AI systems. Employee interviews validated that positive operational effects were brought by AI decision automation to the workforce, while challenges in adapting to this transition were found by employees. Practical insights about AI-agile integration were built from research and direct industry interviews, contributing to engineering practice knowledge. This academic approach does not remain under the reflection of financial uniqueness but sees it as a challenge; its extension may reach into healthcare or direct operational functionality for supply chain management or other industrial engineering systems.