MHD spoke this week with Eugene Amigud, Chief Innovation Officer at Infios, following the company’s newly announced collaboration with Amazon Web Services (AWS) aimed at transforming supply chain execution with agentic AI.
What customer pain points in order management led Infios to pursue this collaboration with AWS?
Infios: Many companies still manage order fulfilment through fragmented rules and manual updates that slow responsiveness. We saw customers struggling with limited visibility, repetitive configuration work, and delays during demand spikes. We wanted a partner with world-class cloud infrastructure and AI expertise to help accelerate development, scale securely, and operationalise innovation. The AWS Generative AI Innovation Center provides exactly that – guidance, frameworks, and the ability to bring intelligent solutions to market faster.
Can you share an example of how these AI agents will work in a real-world scenario – such as detecting an anomaly during fulfilment?
Infios: Imagine a system flagging an order delay before a customer – or even the operator – notices. An AI agent can detect the anomaly, analyse root causes such as an inventory shortfall or carrier delay, and recommend corrective actions automatically. The operator reviews, approves, or adjusts the fix, resolving issues before they cascade.
The press release mentions “simplified workflow orchestration” – what does this mean in practical terms for your customers’ day-to-day operations?
Infios: Setting up new tools can be a huge time investment, especially when custom configuration is required for workflows. What we’ve built ensures that workflows will be able to be built and adjusted through natural interaction instead of complex configuration. Operators can describe what they need, like setting a new order-hold rule or rerouting based on inventory levels, and the system creates the workflow automatically, speeding up response time and reducing IT dependency.
Why was early 2026 chosen as the launch timeline for these AI-driven workflows?
Infios: We’re taking a measured approach to ensure these capabilities deliver real value at scale. The 2026 timeline allows us to complete testing with early pilot customers, refine the AI agents’ performance, and align closely with AWS’s roadmap for secure, enterprise-grade generative AI deployment.
Will this technology help smaller businesses compete with larger enterprises in supply chain execution?
Infios: A key benefit of the modular, API-driven design makes advanced AI capabilities accessible without enterprise-scale resources. Smaller businesses can adopt specific workflows, prove value quickly, and scale over time – gaining the same real-time visibility, adaptability, and decision intelligence that larger organisations rely on, but without the complexity.
What made AWS the right partner for this initiative compared to other cloud/AI platforms?
Infios: The AWS Generative AI Innovation Center helps selected AWS customers build, scale, and productionise generative AI solutions. We share a common focus on creating breakthrough customer experiences. This collaboration helped us define and prioritise key use cases, plan for scalable growth, and strengthen the foundation of our AI strategy.
How do you see agentic AI evolving in supply chain management over the next 3-5 years?
Infios: We expect agentic AI to move quickly from automating isolated tasks to orchestrating end-to-end execution, intelligently coordinating Order, Warehousing, and Transportation flows. In the next 1-2 years, these agents will not just respond to issues but anticipate them, continuously learn from events, and act across systems without human prompting. Beyond that, agentic AI could evolve into a fully collaborative network of autonomous systems—interacting across enterprises, suppliers, and logistics partners to self-optimise global supply chain ecosystems in real time.
What kind of ROI or efficiency gains are customers expected to see once these AI agents are fully deployed?
Infios: Customers can expect reductions in cycle times, fewer exceptions, and lower cost-to-serve. For example, order processing might shift from hours to minutes, manual interventions drop significantly, and labour and inventory costs fall. The goal is measurable performance uplift – typically in double-digit percentage improvements – rather than incremental change.
Will existing Infios OM customers need significant changes to their current systems to adopt these AI capabilities?
Infios: Our goal is to avoid the need for major system replacements. Most existing Infios Order Management customers can integrate agentic AI through our modular, API-first architecture. The intelligence layer sits on top of current workflows and data, so our customers can adopt capabilities incrementally, test use cases, and expand without disrupting core operations.
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