Redefining the operating model for the agentic era

Industrial products companies are at a turning point. AI-enabled engineering is reducing the cost and time required to build production-grade software. This shift is changing how leaders think about architecture, investment and differentiation. 

For years, ERP and SaaS platforms helped companies standardize core processes. They also consumed much of the capital available for transformation. In many cases, that left less room to invest in customer and operational experiences that can set a company apart. 

Lean architecture offers a clear response. Keep the core stable. Move differentiation, intelligence and change to the edge. In this model, ERP remains focused on financial integrity, compliance, master data and core transactions. Experiences, orchestration and decision-making sit outside the core, where they can evolve faster without disrupting the backbone. 

This matters because the question is no longer whether organizations should build. The real question is what to build, where it should live and how it should be governed. AI now makes it more practical to develop custom software and agents where they can create advantage, not just efficiency.

Agents become a core part of how work is executed across systems. Some are embedded in enterprise platforms and support standard workflows. Others are built for specific customer and operational needs. Both can add value, but they need clear oversight as they scale across the business. 

That is why governance is essential. Organizations need to know what agents exist, what they are allowed to do, how they connect to other systems and how results are monitored over time. A shared registry and control layer can help manage this complexity and allow platform agents and custom agents to work together. 

Lean architecture helps organizations protect the ERP core, invest where differentiation matters and support faster change with less risk. In a market where software can be built more quickly and at lower cost, it creates a practical path from standardization to advantage.

How the model works in practice

A closer look at how core systems, agents and governance work together to support change.

The role of agents and governance

As organizations move toward continuous decision-making, agents take on a larger role in how work is carried out across systems.

Some operate within enterprise platforms and support standard processes. Others are designed for specific use cases closer to customers and operations, where needs change more quickly.

As adoption grows, so does the need for oversight. Without a clear structure, organizations risk duplication, inconsistency and reduced control.

A shared approach to governance helps address this. It provides visibility into what agents exist, what they are allowed to do and how they interact across systems. It also supports coordination, allowing different types of agents to work together with consistency and accountability.

With the right balance, organizations can maintain control while allowing faster change where it matters. This creates a more deliberate way to invest and adapt.