Machines run, sensors measure, data is generated - and then what? In many industrial companies, this is exactly where the IoT approach ends. Data ends up in silos, doesn't find its way into business processes, and in the end nobody makes better decisions than before.
Yet the potential is enormous. The global IIoT market is expected to generate sales of around 251 billion euros in 2025 and grow to around 414 billion euros by 2029 - an annual growth rate of almost 13%. In Germany alone, a market volume of around eight billion euros is forecast for 2025.
The growth is there. The question is who will benefit from it.
Industrial IoT (IIoT) refers to the networking of machines, systems, sensors and control systems in industrial environments - with the aim of collecting and evaluating data in real time and translating it into operational decisions. In contrast to consumer IoT, it is not about smart household appliances, but about production lines, supply chains, maintenance cycles and energy consumption.
In 2026, AI and IoT will increasingly merge to form the so-called AIoT architecture: IoT devices will no longer just act as passive data sources, but will make decisions independently. AI models run directly on gateways and embedded devices - a sensor in the production plant independently detects anomalies, evaluates them and initiates measures without going through a data center.
The fields of application are as diverse as the industry itself. Here is an overview of the most important ones:
IoT projects fail due to a lack of strategy, the wrong choice of platform or because the path from raw data acquisition to real use has not been thought through to the end.
The most common stumbling blocks in practice are well-known: 56% of companies operate several IIoT platforms in parallel instead of using a standardized and scalable technology. And only 22 percent define clear goals and KPIs for their IIoT implementation - without concrete KPIs, IoT projects often remain stuck at pilot level.
What works instead is a clear approach in four steps:
With the IoT-X Platform, we at prodot have developed a solution that addresses precisely this point. The IoT-X Platform enables companies to collect and analyze IoT data in real time and transfer it into productive processes - as a technical basis for data-driven services, automated workflows and new business models in the industrial environment. prodot products
The platform is available in the Microsoft Azure Marketplace, comes with ready-to-use modules for data aggregation, dashboards, alerting and reporting and allows a lean start with an initial use case that is gradually expanded. Follow-up processes in SAP are triggered directly from evaluated IoT data: Maintenance orders, spare parts orders, machine time allocation or alarm messages - without any manual intermediate step. prodot: IoT consulting
This can be seen in practice, for example, in use at a leading road construction company: data from various telematics systems such as MiX Telematics, CAT and Liebherr flows automatically into SAP - and reduces fuel costs by up to ten percent.
Predictive maintenance, digital twins and smart production lines are the driving use cases - and the trend shows that companies are no longer relying solely on hardware, but increasingly on platform solutions and analysis tools.
Those who use IoT strategically create real competitive advantages: lower operating costs, higher plant availability and the basis for data-driven business models. The first step is a clearly defined use case - not a major transformation project.
Would you like to know which IoT use cases offer the greatest leverage in your production - and how to get started with the prodot IoT-X Platform? Get in touch with us.