The taxing reality of integration in industrial automation

(See Festo at Machine Building South, 8 July 2026, on stand 17)

For decades, industrial automation has promised simplicity while quietly delivering complexity. Each new technology layer - smarter sensors, faster controllers, more capable drives - has undoubtedly improved performance at the component level. But at the system level, combining these technologies comes with a hidden surcharge: the engineering effort required to make everything work together.

Let's call it 'the integration tax'. It doesn't appear on a purchase order, but it is paid in commissioning delays, programming workarounds and hours spent resolving compatibility issues rather than improving machine performance. For many manufacturers, engineers and machine builders, it has become an accepted cost - but we need to change this dynamic.

The cost nobody budgets for

Integration has always been central to automation, but the scale and impact of the integration burden have changed. Following the advent of digitalisation and the IIoT, machines are no longer standalone systems. They are expected to connect across production lines, interface with plant-wide data systems, and support higher-level performance analytics. Achieving this level of connectivity across multiple components and systems, usually from multiple manufacturers, is not simple. And when it goes wrong, the price is delayed commissioning, re-programming, and talent hours spent on compatibility rather than capability.

This problem is being compounded by skills shortages, making experienced automation engineers increasingly difficult to recruit and retain. In addition, energy costs remain volatile, making efficient operation more important than ever. Under these conditions, time spent on integration is no longer just inconvenient; it is a direct constraint on productivity and competitiveness.

The automation industry has responded by continuing to optimise components: faster cycles, higher precision, more data. But if the effort required to integrate these components increases at the same pace, is the system any more efficient? What if we are optimising the wrong variable?

Picking the wrong fight

The ongoing discussion around pneumatic versus electric motion is one example of picking the wrong fight. Each technology has clear strengths. Pneumatics offers high-speed, high-force actuation with relatively low infrastructure cost. Electric drives provide precision, flexibility and programmability.

The challenge is not choosing between these technologies, but in combining them effectively. However, many machine designs still treat them separately. Integrating pneumatic and electric systems therefore requires additional interfaces, custom programming and careful coordination between different engineering disciplines. This adds complexity and introduces risk.

A more productive approach would be to focus on unified motion architectures. In this model, the choice of technology is driven purely by application requirements, not by integration constraints. Pneumatics, electrics and software operate within a shared framework, using consistent communication principles and open standards.

Adopting this approach, the advantage no longer lies in selecting the "right" motion technology in isolation, but in the ability to deploy multiple technologies seamlessly within the same system. The manufacturer or machine builder who can combine all three in a unified data architecture - without custom middleware or proprietary lock-in - has a competitive advantage over one who can't.

Designing for the full lifecycle

Achieving this automation nirvana is not easy, because the integration tax is not just a one-off cost. It persists throughout the entire machine lifecycle.

Disconnected design environments can require engineers to re-enter data between tools. Simulation models may diverge from physical implementations, leading to delays during commissioning. Documentation can become outdated, making maintenance and troubleshooting more difficult. Over time, these inefficiencies accumulate.

Lifecycle thinking addresses these issues by maintaining a continuous flow of information from initial design through to operation and maintenance. Data generated during engineering is carried forward into commissioning. Operational data is fed back into optimisation and future design iterations.

This continuity reduces duplication of effort and improves transparency across teams. Maintenance personnel work with accurate, up-to-date information. Engineers can refine designs based on real-world performance data. Decisions made early in the project retain their value over time.

The lifecycle perspective means automation is no longer defined solely by a choice of hardware or software components. It becomes a set of decisions and data that evolves throughout the machine's lifespan.

From connectivity to User Experience

Connectivity is often presented as the solution to integration challenges. However, simply linking devices together does not eliminate complexity or necessarily improve data flow. A connected system can still be difficult to configure, operate and maintain. What matters more is system adaptability.

This is where software and AI can change the equation, applied as an integral layer that allows automation systems to respond intelligently to their environment and to the people using them. This creates systems that do more than exchange data. Using AI, devices can recognise each other and configure themselves automatically. Operational data can be analysed in real time to identify anomalies before they develop into failures. Interfaces can present information in a way that adapts to the user, not the other way around.

Applied correctly, AI changes how automation is experienced. Instead of interacting with multiple layers of technology, engineers and operators engage with a system that behaves coherently and predictably. This represents a subtle but important transition: from systems that are merely connected to systems that are inherently intuitive.

In this context, the most advanced automation systems are not those with the most features, but those that make complexity invisible. The architecture may be complicated, but the user experience is simplified.

Achieving seamless automation

Reducing integration effort requires systems that are inherently easier to connect, expand and maintain. This necessitates moving from proprietary hardware and software to open architectures, widely adopted protocols and consistent design principles.

Festo Seamless Automation provides such a solution. It brings together pneumatic and electric motion, software and AI within a single, consistent system architecture. The concept ensures that components work together seamlessly within a shared structure using a combination of standardised protocols, modular system design and open architecture across all technologies. The result is continuous data flow from field devices through to higher-level control and analytics, without the need for custom interfaces or repeated engineering effort.

Seamless Automation extends beyond connectivity. A continuous digital thread supports the entire lifecycle, from design and commissioning through to operation and maintenance. Data generated at each stage is carried forward, reducing duplication and ensuring that systems behave as expected when deployed.

The practical impact is a significant reduction in development and programming effort. Tasks such as system design, product selection and commissioning can be completed more quickly and with less risk, allowing engineering teams to focus on application performance rather than system integration. That recovered time can then be applied where it creates real value: improving machine performance, optimising energy use, enhancing reliability, or developing new capabilities. Rather than being consumed by system complexity, engineering capacity is redirected towards innovation.

Reclaiming engineering capacity

The idea that integration complexity is unavoidable has been deeply embedded in industrial automation for many years. It has shaped design practices, project planning and even expectations around what constitutes a "normal" commissioning process. The concept of the "integration tax" is useful in highlighting this long-standing inefficiency. What was once accepted as an inevitable covert cost is being recognised as an avoidable consequence of fragmented system design.

Approaches such as Festo Seamless Automation provide a new model: one in which inherent compatibility ensures that devices, data and hardware work together as a unified whole, so technology becomes an experience, not a burden. But the real value of seamless automation is not simply technological. It lies in what it enables. Every hour not spent resolving compatibility issues is an hour that can be invested in improving machine performance, reducing energy consumption or developing new capabilities. In other words, automation is no longer just about hardware, software or connectivity. It is about how effectively engineering time is used.

Ultimately, the most effective automation systems are not those that demand the most attention, but those that require the least. As connectivity, architecture and AI combine to create more adaptive systems, complexity can be managed at the system level rather than by the engineer. That inversion, where sophisticated technology results in a simpler human experience, is what will define the next phase of industrial automation.