The most important embedded AI trends in 2025

Artificial intelligence (AI) has made enormous progress in recent years and is now an integral part of many areas of daily life. Exciting developments are on the horizon for 2025, particularly in the field of embedded AI, i.e. the integration of AI directly on sensors in the corresponding semiconductors. Embedded AI makes it possible to make intelligent decisions directly at the source of the data without having to transfer it to central computing units or even the cloud. This is particularly important in times of IoT (Internet of Things), Industry 4.0 and increasing automation. The trend from AI on the cloud and edge to pure embedded AI systems was already apparent at Electronica.

Viacheslav Gromov, Managing Director of embedded AI provider AITAD, names the most important trends that will shape the field of embedded AI in 2025.

1 AI sovereignty – “Made in Germany” is becoming increasingly important

The US elections and geopolitical tensions have heightened awareness of the need for technological sovereignty in Germany and Europe. In 2025, it will be crucial not only to invest in the development of our own AI technologies, but also to promote and protect them.

AI “Made in Germany ” is becoming increasingly important if Germany, as an industrial and technology location, wants to maintain its independence from foreign providers, particularly from the USA and China. This applies not only to the development of algorithms, but also to the entire infrastructure, from semiconductors to data processing and cloud services. The focus must be on developing sovereign AI solutions that comply with European data protection regulations and guarantee national security.

As no sensitive information needs to be transmitted over the network when using embedded AI, the risk of data leaks and cyberattacks is significantly reduced. This development will be particularly important for critical applications in areas such as healthcare, the automotive industry and smart cities, where data protection and security requirements are especially high.

Initiatives such as the National AI Strategy and investment in research and development should help to establish Germany as a global AI hub that not only remains technologically independent, but is also considered a pioneer for ethical AI. In an increasingly networked world, it will be essential for Germany to develop its own trustworthy AI systems in order to ensure national independence and economic resilience.

2 Predictive maintenance as the key to sustainable business models

In 2025, machine and car manufacturers will increasingly focus on predictive maintenance in order to compete with other global manufacturers during the economic crisis. This is because wage and energy costs are constantly increasing the pressure to compete on a per-unit basis. Maintenance contracts, subscriptions and continuous service models are becoming increasingly important, as they not only help to optimize operating costs, but also offer long-term, recurring sources of income.

European companies in particular can gain a competitive edge here, as service understanding and a customer-oriented approach are traditionally strong in Europe, especially in Germany. The idea of offering customers not only a product but also a continuous, customized service is in line with the European approach of long-term partnership and quality.

Predictive or preventive maintenance, supported by embedded AI technologies, makes it possible to predict failures so that maintenance can be carried out flexibly and on time – a real added value for the customer. This trend towards data-driven business models and services will not only increase efficiency, but also promote greater customer loyalty and differentiation in the face of global competition.

3 Energy efficiency through the use of embedded AI instead of data centers

Climate change and the high energy costs in this country are a major challenge: a significant trend in 2025 will be the increasing use of embedded AI instead of energy-hungry central computers and servers for data processing, as this brings considerable advantages in terms of energy efficiency. Traditionally, processing large amounts of data in data centers requires enormous amounts of energy, not only for operating the servers, but also for air conditioning and securing the infrastructure (backup systems, firewalls). In contrast, embedded AI enables data to be processed directly on the devices or sensors, eliminating the need for energy-intensive data transfers and inefficient external computing capacity.

This development will not only reduce energy costs, but also promote a more sustainable use of resources. Embedded AI will become the standard solution as a key technology for energy-efficient systems (control solutions), particularly in application areas such as the Internet of Things (IoT), smart homes or Industry 4.0.