The path to autonomous production

In the first part, we outlined the three phases of autonomous print production development, culminating in the ‘dark factory’. While the technological possibilities are impressive, they raise a key question: How can print service providers translate this vision into concrete business decisions? For automation to generate real value, a clear strategy is needed. In this second part, we address these strategic imperatives and set out a concrete roadmap.

Technology is a prerequisite, but it cannot replace strategic direction. The decisive factors are how automation is used and embedded within existing structures, and its contribution to business success. In practice, three principles summarise many decisions: prioritising value creation over pure volume, utilising human skills where they are most effective, and viewing sustainability as an integral part of operations.

The concept of growth is changing. Rather than focusing on the number of pages, we should focus on the value generated per order and per page. Mass customisation – personal print products at scale – can make communication more relevant, reduce waste, and increase profit margins. When production is demand-driven, efficiency pays off twice over: overproduction is reduced, capital tied up in inventories is freed up and waste is avoided. The end result is a model in which smaller print runs can have a greater impact than larger ones.

The ability to produce the right quantity of products at the right time is becoming a key sustainability factor. Automation helps avoid excess inventory and returns, as well as the waste of resources, by making processes more predictable and enabling material flows to be accurately matched to demand. In particular, packaging printing demonstrates how data-driven processes can facilitate the pragmatic implementation of regulatory requirements, such as providing more suitable packaging sizes and using less filling material. Sustainability thus becomes a natural consequence of efficient, well-managed processes rather than a separate add-on.

Rather than replacing people, automation and AI transform the nature of tasks and create new areas of focus. As repetitive tasks decrease, the ability to provide an overview, make decisions, and think creatively becomes increasingly important. Human judgement is required for valuable contributions such as selecting viable business models, developing strong customer relationships, expanding the portfolio and meaningfully integrating new technologies into everyday life.

Therefore, the next wave of investment will be in both machines and the digital infrastructure that holds everything together. System integration, data quality and clear governance will enable long-term, scalable progress.

The path to autonomous print production rarely involves an overnight technological leap. Instead, it is the result of a strategically structured sequence of investments and organisational decisions. Those who plan ahead can gradually create the conditions necessary to remain competitive, grow effectively and strengthen their organisation.

The four most important areas of action can easily be translated into concrete programmes and implemented over time.

• Consistently link MIS, ERP and pre-press and production systems to connect existing automation islands.
• Improve data quality by identifying processes that still rely heavily on manual input and gradually automating or validating them.
• Make the most of potential uses, bearing in mind that clean, structured data forms the basis of all subsequent automation stages.

• Expand sensor technology and the logging and analysis functions in order to transform alarms into reliable predictions and enable earlier decision-making.
• Tie service contracts more closely to performance data and system access, creating transparency and improving downtime planning.
• Implement initial pilot projects for predictive maintenance or AI-supported workflows to establish learning curves and measure the real benefits early on.

• Set up continuous production lines to ensure a steady flow of orders without any waiting time between steps.
• Introduce barcode-controlled processes, inline inspections and automated feedback loops to ensure quality control throughout the production process.
• This will increase production speed, reduce sources of error and free up skilled workers, who currently spend a lot of time on these tasks.

• Join existing platforms or build your own to forward orders flexibly to the location that best meets your requirements in terms of capacity, cost and delivery time.
• Standardise your interfaces to enable new partners to connect more quickly, eliminating the need for individual developments.
• With decentralised production models, you can scale up quickly without losing proximity to customers.

Although the transition to autonomous production shows promise, it also presents technical, organisational and strategic challenges. Investors looking to invest sustainably should consider these factors from the outset, as they can significantly impact speed, costs, and acceptance within the company.

Complexity of integration
Cloud platforms and iPaaS can minimise technical friction losses. Nevertheless, legacy systems, individual scripts and special cases are still widespread. It is therefore important to plan for adaptations, security checks, ongoing data maintenance and the coordination of heterogeneous systems, since hidden project costs often arise in these areas.

Actively shaping talent and change
Although robots and AI are changing job profiles, entire roles are not being replaced automatically. This is precisely why targeted retraining, digital work instructions and reliable digital twins are important: they preserve expertise and help to maintain quality standards in an increasingly automated environment. If knowledge is only stored in people's heads, it is difficult to scale up quickly.

Dependence on platform providers
The more you rely on external platforms, the greater the risk of becoming locked in. Therefore, strategies for data portability and exit options should be defined early on to ensure you can still act, even if providers, prices or conditions change. Open interfaces and transparent data models are essential protective mechanisms, not just desirable ones.

Quality assurance is key
Zero touch only works if there is trust in the automated control loops. Those performing fewer manual checks must invest more in inline controls and closed feedback loops, since errors discovered late in the process can be costly in an automated workflow. Therefore, quality becomes a prerequisite rather than a form of downstream control.

• Order data is created once and used consistently throughout the entire process, from planning and printing to further processing.
• Operators work with digital work instructions and can access AR- or MR-based assistance systems as required.
• Maintenance measures are planned proactively and managed as part of the production process, rather than occurring unexpectedly as emergencies.
• Set-up times are reduced, operating times are increased, and quality remains stable as product diversity continues to grow.

Autonomous print production isn't a showcase for technology, it's a direct response to pressing market realities: skills shortages, sustainability imperatives, and mounting margin pressure. The path forward begins with networked automation and predictive intelligence, establishing zero-touch processes where material and information flows synchronise seamlessly, without delays or bottlenecks.

The better companies leverage data, integrate systems and design robust workflows, the more efficient, resilient and adaptable they become. Investing in digital infrastructure therefore means securing capacity, reducing risk and creating space for high-value applications that will define the next growth cycle in print.