COGNITIVE BUSINESS INTELLIGENCE: INTEGRATING DIGITAL TWIN PERSONAS WITH REAL-TIME DATA STREAMS FOR AUTONOMOUS STRATEGY ADAPTATION – A HYBRID HUMAN-AI DECISIONING FRAMEWORK USING BEHAVIORAL ANALYTICS AND NEURO-SYMBOLIC REASONING IN BUSINESS ECOSYSTEMS

In the evolving landscape of cognitive business intelligence (CBI), this paper proposes an innovative hybrid human-AI decision-making framework that integrates digital twin personas with real-time data streams, underpinned by behavioral analytics and neuro-symbolic reasoning. The goal is to enable adaptive, autonomous strategy formulation within complex business ecosystems. This framework leverages advancements in AI cognition, real-time analytics, and digital representations of human behavior (i.e., digital twins), enhancing decision accuracy, resilience, and strategic agility. By aligning human cognitive models with artificial intelligence systems through neuro-symbolic integration, businesses can achieve context-aware responses, simulate stakeholder interactions, and optimize strategic trajectories in real time. Our approach is contextualized within the technological and organizational environment, characterized by increasingly autonomous systems, dynamic markets, and the fusion of symbolic and sub-symbolic AI paradigms.