“2025 was a year in which AI spread incredibly quickly and became noticeably more professional,” says Konstantin Leitz, Vice President of Business Innovation at INFORM. "In 2026, this development will continue at an even faster pace. Hardly any other field of technology is currently experiencing so many innovations," says the expert. From autonomous AI agents and AI-native software architectures to specializable models and new governance standards, AI will become an integral part of operational value creation in many industrial companies in 2026. The focus will thus shift more toward the systematic integration of AI into software, processes, and infrastructures.

Trend 1: AI agents are increasingly taking on operational tasks

In 2026, AI agents will be increasingly integrated into daily operations. They track processes in real time, evaluate deviations, and prepare decisions when conditions change at short notice, for example when transport times fluctuate or material flows come to a standstill. The proliferation of individual agents will also give rise to a new form of interaction, as many companies will have several specialized agents working in parallel on different subtasks in the future. For example, a planning agent in production can recognize at an early stage that a material will not be available on time and automatically initiate coordination with logistics to check for an alternative supply and ensure smooth operations.

Trend 2: AI becomes the core of modern software architectures

With the increasing maturity of large language models, software development is also undergoing fundamental changes. Applications are no longer supplemented by AI, but are designed from the outset so that learning, data processing, and decision-making logic are integral parts of the architecture. At the same time, the development process itself is changing: AI-generated code segments, automated testing, and adaptive deployment pipelines will become standard in 2026. In the future, skills such as the precise formulation of prompts, the testing and validation of AI-generated results, and the design of complex system architectures and maintenance of existing systems, for which AI models are often not sufficiently sensitized, will be in demand.

Trend 3: AI systems are becoming more specialized and modularly combinable

The more widely AI is used in companies, the greater the demand for specialized intelligence. Instead of using universal models for all use cases, domain-specific systems that are specifically trained with specialist and industry data are gaining in importance. They deliver greater accuracy and efficiency, especially where processes are closely interdependent or smooth transitions between planning, control, and execution are crucial. At the same time, a modular architectural approach is gaining ground, enabling specialized models and components to be combined flexibly. For example, forecasts of available capacities can be linked to models for prioritizing time-critical processes or for evaluating current resource situations.

Trend 4: Transparent and compliant AI systems are becoming mandatory

As AI-based applications become increasingly complex, transparency is becoming a key quality feature. “AI observability” describes the ability to monitor the behavior, performance, and decision-making logic of AI components in real time. In 2026, specialized platforms and frameworks will emerge that make training, inference, and security systematically traceable. At the same time, key European regulations such as the AI Act, the NIS 2 Directive, and the Cyber Resilience Act will reach a new level. Companies will have to provide comprehensive evidence that their AI systems are operated in a secure, transparent, and compliant manner.

Trend 5: New roles and skills shape the use of AI

In 2026, there will be a greater focus on how people in companies work with AI and what new forms of collaboration this will give rise to. New responsibilities will emerge at the interfaces between departments, data, and AI applications, and existing job profiles will evolve as dispatchers, planners, and shift supervisors increasingly work with AI-based recommendations and assistance functions. At the same time, training and a conscious approach to change processes are becoming increasingly important so that AI systems can be mastered safely and used reliably in everyday life.

“Gain experience early on”

“For companies, 2026 will be a year in which the practical use of AI will mature significantly,” Leitz summarizes. “Many developments are moving closer to the operational core and showing where AI makes a difference. Companies that gain experience early on and adapt their processes step by step will benefit the most.”

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