This blog explores the evolving landscape of AI Security in Supply Chain, focusing on practical guardrails, emerging risks, and key focus areas to help organizations build secure, trustworthy AI-driven supply chains.
- Practical AI guardrails for planning, logistics, and production systems
- Zero Trust, RBAC, and data classification for AI workflows
- Secure integration of identity, policy, and observability frameworks
- Lessons from real-world enterprise supply chain transformation
Afraz Neikar
Supply Chain CyberSecurity and AI Security Leader passionate about building secure, trustworthy AI-driven supply chains
As a Security Transformation Leader, I specialize in developing and executing comprehensive security strategies for global supply chain applications. With a strong focus on AI Security, Identity Modernization, Application Security, and Compliance, I lead large-scale security programs that drive risk reduction, enhance resilience, and support the organization’s security goals..
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Use Case: Predict product demand across regions and time periods using AI/ML models that integrate internal and external data sources, while maintaining strong data security, RBAC, and policy governance. Understand how Forecasting is enabled for your organization.. AI Security starts…
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Gartner Says Supply Chain Cybersecurity is at Peak of Inflated Expectations
https://www.gartner.com/en/newsroom/press-releases/2025-09-29-gartner-says-supply-chain-cybersecurity-is-at-peak-of-inflated-expectations Gartner highlights several major challenges that prevent supply chain cybersecurity from being a silver-bullet solution:
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Protecting Supply Chain from AI Driven Risks in Manufacturing
Key Points