Monolithic supply chain systems have become a structural weakness for global brands contending with geopolitical shocks, tariffs, and demand swings. Cloud-native platforms, built around modular, API-driven services, are an answer, Cloud Native Now December 3 reports. They integrate IoT sensors, GPS data, and status feeds from suppliers, carriers, ports, and fulfillment centers into “digital control towers” that provide end-to-end shipment visibility on a single screen.
Elastic infrastructure is the second pillar. The article highlights findings from a 2025 PwC survey, in which 96% of cloud adopters in supply chain reported revenue gains via higher productivity and lower operating costs. Instead of scaling entire monoliths, cloud-native logistics platforms scale individual microservices and containers as demand fluctuates, while API-driven onboarding lets brands plug in new partners or tools without ripping out the core.
The article also stresses decentralized hosting across multiple regions to protect uptime, with failover between nodes and the ability to isolate compromised servers, plus continuously improving security baselines that would be cost-prohibitive for many in-house systems. Embedded analytics rounds out the stack, with cited McKinsey research that attributes 15% lower supply chain costs and 20% to 30% lower inventory backlogs to big data analytics.
Diagnostic and predictive models, layered onto unified data, enable not just root-cause analysis but scenario forecasting, while AI agents can trigger targeted actions such as weather-related delay notifications.
Multi-Agent AI Play
Shifting from infrastructure to intelligence, multinational IT company Fujitsu’s new multi-AI agent technology reportedly coordinates decisions across multi-company supply chains, AI Magazine December 2 reports. The basic premise is that each entity runs its own AI agents, and Fujitsu provides the collaboration layer so those agents can react to fluctuating market conditions and operational changes without exposing confidential data.
Beginning in January 2026, Fujitsu is planning field trials with Rohto Pharmaceutical, alongside a leading Japanese university, to test how the system optimizes day-to-day operations and supports rapid recovery from demand shocks or external disruptions. The company positioned this as a step toward broader adoption in manufacturing and other sectors with complex, multi-vendor supply chains.
Two core components ground the system, per the outlet. A “global optimal control” function infers preferred conditions for each partner using only limited information, then approximates an overall optimum for the shared supply chain. This is meant to enable effective collaboration across agents from different companies without requiring full data sharing.
In parallel, a secure “inter-agent gateway” governs how external AI agents interact. During setup, agents use knowledge distillation to train a student model from multiple teacher models, learning supply chain characteristics without centralizing raw data. In operation, the gateway repeatedly simulates agent behavior to detect malicious activity and prevent leakage of confidential information, while supporting distributed AI training. Fujitsu framed the work within its Uvance business model, arguing that secure, cross-border agent collaboration can strengthen resilience, reliability, and governance in multi-vendor environments.
What This Means for ERP Insiders
Cloud-native logistics will ratchet up expectations for ERP-connected supply chain visibility. As digital control towers, elastic microservices, and embedded analytics become standard in cloud-native platforms, ERP vendors and program leaders will face pressure to ensure core ERP data and workflows integrate cleanly into these environments rather than competing with them. That will influence decisions about how deeply ERP supply chain modules expose real-time telemetry, APIs, and event streams to external orchestration layers.
Multi-agent collaboration points to a new coordination layer above transactional systems. Fujitsu’s approach treats AI agents as negotiators of joint operations across multiple companies, with confidentiality preserved through optimal control and secure gateways. This suggests future scenarios where planning, allocation, and risk decisions are partly delegated to cross-organization agents that sit on top of ERP data, raising new questions about governance, auditability, and shared decision logic in extended value chains.
Security and governance must become central design criteria. The above use cases emphasize resilience not just in uptime and performance but in data protection, agent behavior control, and cross-border collaboration. Those evaluating supply chain roadmaps will need to treat capabilities such as decentralized architectures, zero-trust-style access for agents, and explainable multi-party optimization as core requirements if ERP platforms are to remain credible system-of-record anchors in increasingly autonomous, cloud-native supply networks.
