Initiating complex workflows with simple text commands.

The 21st century has stress-tested the global supply chain. Climate shocks and geopolitical flare-ups have fractured the way we do business. Everything from tsunamis to Trump-era tariffs has exposed the fragility of just-in-time logistics. But what’s the fix to this uncertainty?

Consumers may be stockpiling beans in case the world order collapses, but manufacturers and their customers are betting on something less apocalyptic: supply chains driven by agentic AI.

As Anita Chowdhury from the Cambridge Innovation Institute puts it: “Companies must assume disruption is constant, not occasional. A resilient supply chain isn't just about backups – it’s about intelligent design.”

This new paradigm isn’t about building bigger buffers; it’s about creating a smarter, self-learning supply chain management tool that can accelerate data-driven decision-making to keep the wheels of business turning. OEMs and EMS need supply-chain tools that can predict and reroute around problems and even turn disruption into advantage.

The AI Inflection Point in EMS

Luckily, the integration of AI into daily business systems is no longer a future prospect; it's a current competitive edge. For many within the electronics manufacturing services (EMS) sector, AI is now reshaping how companies quote, source and manage complexity. Quoting platforms are using machine learning to optimize component selection. Predictive analytics foresee shortages before they become roadblocks.

But soon, with the emergence of agentic AI – AI that can reason, learn, and act independently – we will see whole chains of planning and mitigating actions being handled by robots. Pushpinder Singh, global supply chain transformation leader at IBM Consulting, outlines five of the capabilities essential for agentic AI that are coming together right now:

1. LLM core – The reasoning and natural language engine;
2. Planning capability – Task decomposition and orchestration;
3. Integration engine – Real-time actionability via system connectivity;
4. Memory – Institutional knowledge and historical insight; and
5. Feedback loop – Continuous learning and self-improvement.

With integration and feedback mechanisms in place, agents can carry out tasks like sending replenishment orders, notifying suppliers or rerouting shipments, all while learning from each decision.

Integration with multiple platforms and data points must be at the core of these new systems. But if we’re going to unleash these systems on our supply chain, we must ensure the security and accuracy of their data processing and decision-making powers.

Currently, while generative AI is being used in important ways, agentic AI is in beta or not being used at all: Some 61% of executives at the WSJ Tech Summit in February 2025 indicated they are experimenting with AI agents, while 21% aren’t using them at all.

Supply Chain AI

Many companies are talking about supply chain AI and the future of agentic AI, but few have been as open as companies like Luminovo, which are leading the transformation for many OEM and EMS companies with their software. In a recent interview, Luminovo’s COO Sam Mason explained its development roadmap and bullish plans for the full embrace of agentic AI.

Their AI-enabled tools are already automating traditionally manual, error-prone processes, like BoM interpretation and total cost calculation. And they are well on the way to creating agentic capabilities built on the strong foundations of their existing platform.

This kind of automation isn't just about convenience; it’s redefining how fast and accurately EMS companies can respond to a range of customer needs.

In the interview, Mason outlines the kind of capabilities Luminovo is delivering and working on:

BoM interpretation. Translating a new product design into production often finds its first bottleneck at the bill of materials (BoM) stage. These aren't always neat, standardized files. OEMs, dealing with complex designs, can hand over BOMs in various formats – from detailed spreadsheets to densely packed PDFs. This can slow the quoting process and lead to mistakes in interpretation. AI can change the speed and accuracy of this process, with the right software transforming data into quotes.

Part recommendations. Supply-chain fragility means component availability can shift overnight. The ability to pivot to alternative parts – while still meeting spec, compliance and cost targets – is critical.

Modern supply-chain software is making AI part suggestion engines that solve these problems. These tools will be able to assess lifecycle status, RoHS/REACH compliance and availability in real-time, then recommend substitutes that are in-stock and compatible. This will minimize delays in sourcing and ensure resilient production planning. And it won’t require engagement with multiple, complex platform interfaces to bring together alternative suggestions; it will be as simple as asking a question. Explains Mason: “If you realize there’s a compliance issue ... you could just ask the AI, ‘What’s a suitable alternative?’ It will look through your inventory as well as the market.”

Total landed cost calculation. Unit price is just the tip of the iceberg. Accurate procurement decisions require visibility into the full landed cost: tariffs, customs duties, shipping, packaging and fees.

These are some of the hardest data to assemble and understand, but Luminovo’s total cost of ownership module does these calculations automatically. By pulling data from distributor offers, country-of-origin info and tariff schedules, it works out exactly what each component actually costs to get to a facility. This empowers quoting teams and avoids surprises later.

Procurement workflows via prompt. The longer-term prize for Luminovo will be agentic supply-chain management, where procurement professionals can initiate complex workflows with simple text commands.

• Monitoring for disruptions
• Communicating with suppliers
• Making low-risk sourcing decisions
• Summarizing changes for human approval.

These capabilities will create a more autonomous, intelligent supply-chain management system that will keep users informed but unburdened from the daily grind of data-led decision making.

“Eventually, AI will communicate on your behalf, summarizing and acting on supply chain insights so you can focus on what matters,” Mason says.

The AI-Ready EMS

If you build electronics, nothing wrecks a schedule faster than a part shortage or a quote that takes two weeks. Agentic AI – software that can read a BoM, scan live inventories, compare tariffs and even trigger the purchase order – solves that. But trying to bolt these tools onto a single brand’s data stack is the slow lane. The organizations most capable of leveraging AI at scale are the EMS partners who will utilize these tools effectively. After all, they still:

Own the richest data pool. An EMS processes hundreds of programs daily, pulling live feeds from distributors, freight carriers, customs brokers and test houses. That volume can train AI models to spot shortages, price swings and compliance snags long before an in-house system fed by one product line could.

Run battle-tested processes. The best EMS firms have decades of quality gates, export-control checks and cybersecurity baked in. AI doesn’t replace those guardrails; it accelerates them.

Protect IP and reputation. With audited data lineage, strict access controls, and human-override protocols, mature EMS providers give brands the speed of AI without the compliance headaches of running it alone.

What’s certain is that the selection process for OEMs working with EMS is going to change. The emphasis is going to move from the importance of individual relationships between businesses and their suppliers to the unshakeable quality of their processes. OEMs will soon pick EMS partners for their digital muscle, not their address books. EMS firms that stand out will offer:

• Real-time visibility – instant alerts the moment a part goes short or a price spikes;
• Autonomous agents – AI workflows that automatically reroute orders and surface costed alternatives, with every action logged for audit;
• Audit-ready traceability – full decision history, pricing, and source data captured in one place; and
• Seamless integrations – plug-and-play links for OEM design tools, planning platforms, and ERP systems.

When those pieces click together, supply-chain shocks will be absorbed before they hit your build schedule.

Ed.: This article was first published in the Escatec EMS Review and is republished with the author’s permission.

Asmin Perviz is manager, Design & Development (D&D) at ESCATEC (escatec.com); asmin.perviz@escatec.com.

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