Securing Industrial Networks: AI-Driven Fundraising And Business Models For Smart Manufacturing

Abstract

The increasing complexity and interconnectivity of smart manufacturing systems have made industrial networks highly susceptible to cyber threats, necessitating robust and adaptive security strategies. This study investigates the role of artificial intelligence (AI) in enhancing industrial cybersecurity, while also exploring AI-driven fundraising mechanisms and innovative business models that support secure digital transformation. Using a mixed-methods approach, data were collected from 50 manufacturing firms and leading AI fundraising platforms. Statistical analyses, including multiple regression and principal component analysis (PCA), revealed that higher AI maturity, effective capital allocation, and adoption of scalable security models significantly improve cyber-resilience. AI-powered fundraising platforms demonstrated superior efficiency in capital matching, while service-based security models such as Cybersecurity-as-a-Service and Managed AI Security Services offered high returns on investment and operational scalability. The study also found that discrete manufacturing systems tend to be more cyber-resilient than process-based systems due to greater modularity and integration potential. These findings highlight the importance of aligning technological, financial, and operational strategies to secure industrial networks effectively. The research provides actionable insights for industry stakeholders, policymakers, and technology innovators seeking to build resilient and future-ready smart manufacturing infrastructures.