The industry is currently undergoing profound technological change. Digital transformation is not only changing business models, but also the way companies develop software, design processes and make decisions. Two technologies stand out in particular: artificial intelligence (AI) and low-code platforms. Combining the two is no longer just a trend, but a strategic necessity. Together, they are fundamentally changing the dynamics of IT and engineering – away from rigid, lengthy development cycles and towards agile, data-driven and collaborative environments.

The low-code approach to software development, which enables applications to be created using visual tools and minimal manual programming, is of great importance here. This allows the challenges posed by sophisticated AI technology to be overcome more effectively.

High complexity as a starting point
With a rapidly developing technology such as AI, experimentation time is a crucial factor. This is because the development of new, increasingly complex products must now take place in ever shorter cycles. Therefore, a successful low-code development platform can keep pace with fast-moving technologies. As a result, low-code innovations are being driven forward at a similar pace.

While traditional automation relies on clearly defined processes, AI enables adaptive, adaptive action. In practice, this means:

  • AI systems can analyse data from product development, manufacturing or service, recognise patterns and derive recommendations.
  • This provides engineers and project managers with support in design decisions, resource planning and error analysis.
  • New potential is emerging, particularly in the field of digital twins and PLM systems, as AI meaningfully links large amounts of data from simulation, sensor technology and operational experience.

AI thus becomes a key enabler, helping to turn data into knowledge and the ability to act..

Low-code as an accelerator of digitalisation
At the same time, low-code and no-code platforms, whose market is growing at an incredible rate, are becoming increasingly important. They enable specialist departments to create digital applications without in-depth programming knowledge. This opens up great opportunities, especially in technical environments where processes are individual and complex, as routine tasks can be quickly digitised and adjustments can be made directly in the specialist departments (citizen development). In addition, IT departments are relieved of some of their workload and can concentrate on strategic issues.

Low-code thus bridges the gap between specialist knowledge and technology, significantly accelerating the implementation of digital strategies. By bringing together different perspectives, the interdisciplinary team promotes knowledge sharing and comprehensive employee involvement. Both of these factors lead to greater adaptability and agility.

Synergy between AI and low-code
However, the greatest leverage comes from combining both technologies. Low-code platforms are increasingly integrating AI-supported functions, such as code generation, process optimisation and quality assurance. At the same time, end-to-end automation with AI makes it possible to automatically suggest or test complex application logic. The result is drastically reduced development times, lower error rates and faster implementation of innovations.

In practice, using a collaborative approach, an interdisciplinary team can now develop a solution in a matter of weeks that would previously have taken months – such as an app for maintenance planning or a dashboard for real-time production data.

Challenges
As promising as the combination of AI and low-code is, its introduction also faces certain hurdles. The key challenges include:

  • Governance & IT security: Greater automation also means higher requirements for data protection, access controls and compliance.
  • Integration: Low-code applications must integrate seamlessly into existing system landscapes – from ERP to PLM.
  • Expertise: Specialist and IT departments must develop new forms of collaboration, as AI and low-code require interdisciplinary thinking.

Conclusion
AI and low-code are more than just buzzwords; they mark the transition to a new phase of digital value creation. The combination of the two is key to modern process automation and opens up entirely new possibilities. Companies that strategically combine these technologies not only gain speed, but also quality and innovative strength.

The key is to create the right conditions: clear data strategies, open architectures and empowered employees. Then technology becomes a real added value – throughout the entire life cycle of products and processes.