For years, enterprise asset management has often been viewed as a necessary cost of doing business: maintain the equipment, fix what breaks, keep operations running.

That mindset is changing.

In a recent Future of Supply Chain conversation with SAP’s Ryan Jones and Richard Howells, we explored a bigger question: What happens when asset management becomes part of supply chain strategy rather than a function sitting on the sidelines?

Because while we are busy making the supply chain smarter, we can easily forget what actually keeps it moving.

Machines. Production lines. Warehouse systems. Generation assets. Fleets. Critical infrastructure.

And when one of those goes down, the disruption doesn't stay in the maintenance department.

A broken asset doesn't create a maintenance problem. It creates a business problem.

Think about what happens when an asset needs attention.

In many companies, the information needed to make a good maintenance decision is scattered across the organization. Parts information is somewhere. Technician skills and capacity are somewhere else. Field updates arrive later. Financial information sits in the ERP.

As Ryan put it, “If we're thinking about parts and materials and inventory, maybe this means parts information is in one spot. If we're looking at technician information, what skills, what are their capacities, maybe this is in a different system.”

The consequence is bigger than a maintenance problem.

“Executives are really worried about operational disruption and increasingly safety,” Ryan said. “So not really just that maintenance performance”.

The opportunity is to bring that context together. Enterprise asset management (EAM) connected with materials, HR, projects, finance and safety creates a much more complete picture of what is happening, and what needs to happen next.

That matters because an asset rarely fails in isolation.

“By having all of this information together in asset management, it really does feed this virtuous cycle of improvement.” Ryan adds.

The real cost of downtime happens after the machine stops

Here's the part we often underestimate. Ryan calls it the “ripple effect.”

“The real risk here isn't just the downtime,” he explained. “It's the downstream effects that happen as a result.”

Production can be affected. So can payroll, finance, projects and customer commitments.

“This is touching production. This is touching time and payroll. This is touching finance. This is touching projects. This is touching all these different areas of the business that are really impacted.”

That's why Ryan believes asset management needs to be much more deeply connected to the business. And that connection can also change the perception of maintenance itself.

“The realm of asset management has been perceived as a cost center. But in reality it can be a significant revenue driver and one that helps businesses grow.” he adds.

That's a meaningful shift: from asking how much does maintenance cost? to asking how much business value can better asset performance create?

And getting there requires much more than a maintenance schedule.

“You need the asset criticality, you need previous failures, parts availabilities, technicians who can work on this, certifications, safety requirements, or customer commitments.”

When all of that comes together, maintenance becomes something more powerful: a program that can continuously improve business performance.

AI's killer app may be helping people ignore most of the data

Then there is AI.

And perhaps the most useful application isn't making another dashboard, but deciding what humans don't need to look at.

Consider a water pump throwing off temperature and vibration signals. In a large operation, thousands of alerts can arrive every day. Ryan's description was brilliantly simple: “A company might have thousands of alerts per day. It's very difficult to filter through these as a reliability engineer.”

That's where AI agents could help separate the signal from the noise.

As Ryan explained, AI can help “filter through these alerts and noise” so that “what's going to a reliability engineer is truly the most pertinent information.”

It can suppress alerts, create notifications for important ones and bring the reliability engineer into the loop when human judgment is needed.

The same applies to scheduling. Agents can look at work orders, available resources and technician capabilities, helping automate assignments while reducing manual effort and errors.

And perhaps most practically, AI can give technicians context before they start a job. Add safety considerations and natural-language interaction, and the goal isn't to remove the technician from the process. It's to help them arrive better informed and execute faster and more safely by giving them better information at the moment it matters.

That's a much more interesting future.

Stop automating silos

There is one trap, though.

We can put AI on top of a fragmented process and end up with faster silos.

Planning has its data. Scheduling has its data. Dispatch has its data. Reliability engineering has its data.

Ryan's advice is straightforward: “Stop treating these different departments as silos, but as different maintenance or field service departments that are all working together in unison with unified data to continuously improve those different areas.”

Because the path to an autonomous supply chain doesn't start with an AI agent. It starts with knowing what is happening across the assets that make the supply chain possible.

The autonomous supply chain still depends on physical reality

A lot of excitement going around autonomous supply chains. But autonomy doesn't mean the physical world disappears. In fact, it makes the physical foundation even more important.

As Ryan put it: “Those autonomous operations, they depend largely on the physical assets that are keeping those supply chains running.”

Whether it's a production line, warehouse system or utility grid, when those assets stop, the supply chain can stop with them. That leads to perhaps the most important takeaway from our conversation: “The future of supply chain isn't just about autonomous decisions. It's about connected assets, connected data and connected teams.”

The future of supply chain isn't just about smarter planning or autonomous decisions. But it's about connected assets, connected data and connected teams. Because the path to an autonomous supply chain starts with knowing what is happening across the assets that make the supply chain possible.

Want to hear the full conversation? Listen to the latest episode of Future of Supply Chain: The New Era of Field Service and Asset Management with SAP's Ryan Jones.