Co-Evolution Dynamics: Demand-Driven Innovation, Adaptive Validation, and Iterative Scaling Between Digital Commerce and Cybersecurity (2025-2026) - LK, Guo (International Journal of Multidisciplinary Research, 2026)
Artificial intelligence (AI) has catalyzed a co-evolutionary relationship between digital commerce and cybersecurity, operating through a tripartite cycle: demand-driven innovation (cybersecurity AI tools evolve to address unmet commercial needs), adaptive validation (commercial deployment validates and refines security technologies), and iterative scaling (validated tools scale to broader use cases, generating new demands). This review synthesizes 5 key studies (2025-2026) to unpack the co-evolution logic: commercial demands for SMB inclusivity, privacy-compliant marketing, and operational continuity drive innovations in modular AI, PETs, and risk-cost balanced security; commercial deployment validates these technologies’ practicality, adaptability, and user trust; iterative scaling expands their reach to more industries, business sizes, and regions—sparking new demands and completing the co-evolution cycle. Findings reveal that: co-evolution is fueled by bidirectional learning—commerce teaches security tools practicality, and security teaches commerce resilience; modular AI architectures and PETs are the technical backbone of co-evolution; SMBs are the primary demand generators and scaling catalysts. This framework offers a dynamic, progressive perspective on cross-domain collaboration, guiding stakeholders to leverage AI for sustained mutual advancement.