Demand for semiconductors is growing, driven by digitalization and industrial policies. Embedded systems are accelerating innovation toward specialized, energy-efficient chips.
In 2022France announced an investment of more than 5 billion euros in semiconductors, as part of a plan to strengthen its strategic technological sectors. This dynamic is part of a European context marked by strong growth in demand, driven by the digitalization of uses, the energy transition and the evolution of regulatory frameworks, in particular the European Chips Act. This aims to increase the European Union’s share of global semiconductor production to 20% by the end of the decade.
Real invisible infrastructures of modern technologies, semiconductors are at the heart of countless uses, from smartphones to industrial equipment. Faced with the explosion in global demand, States are investing massively in research and production capacities in order to secure their technological sovereignty and support their economic growth. In this dynamic, embedded systems play a central role, opening a new phase of innovation intended to improve the performance, energy efficiency and functional capabilities of chips.
How embedded systems are redefining semiconductor innovation
An embedded system is a specialized system, integrated into a product, connected watch, industrial machine or aircraft, and designed to perform a specific function in an optimized manner. As this equipment becomes smarter, more compact and more energy efficient, it places new demands on the semiconductor industry. This concerns in particular the reduction of electricity consumption to limit heat dissipation and extend battery life, as well as ever more miniaturized formats.
Unlike so-called general purpose chips, often associated with remote processing in the cloud, semiconductors dedicated to embedded systems execute calculations directly at the device level. They are tailor-made to meet targeted functions, within a wide variety of devices. The rise of the Internet of Things (IoT) and artificial intelligence are further accelerating this evolution, generating growing demand for specialized chips, optimized for well-defined uses.
Embedded systems, and the semiconductors that compose them, are at the heart of new generation equipment in many sectors: automotive, industrial automation, health or consumer electronics. For example, they power advanced driver assistance systems (ADAS), payment terminals, digital medical devices, intelligent temperature regulators and even video game consoles. For example, STMicroelectronics microcontrollers are integrated into electric vehicles as well as smartphones, industrial equipment, electronic keys or certain connected everyday objects.
Semiconductors and embedded intelligence: two inseparable levers
Semiconductors today make it possible to operate complex, connected environments, while embedded intelligence ensures tight integration between hardware and software. This complementarity improves performance, reliability and energy efficiency, in particular thanks to the movement of intelligent processing from the cloud to the edge, where it is executed locally by sensors and microcontrollers.
This approach requires joint design of the hardware and software from the outset, in order to meet strict constraints of size, power and functional capabilities. It relies on several key innovations: Neural Processing Units (NPUs), System-on-Chip (SoCs) integrating AI accelerators, quantification of models to reduce their footprint, as well as lightweight software frameworks designed for constrained environments, such as TensorFlow Lite for microcontrollers.
This hardware-software integration is decisive in many applications. In industry, sensors incorporating AI analyze data locally in order to anticipate failures and activate corrective actions. In autonomous vehicles, it allows safety decisions to be made in real time. Similarly, home automation devices rely on local processing to recognize voice commands or adapt to their environment.
Convergence, a driver of innovation
The convergence between embedded intelligence, artificial intelligence and edge computing is profoundly transforming the semiconductor value chain, from design to production. AI is now used to automate certain repetitive design tasks, such as generating layouts, while generative AI helps engineers optimize chip architectures.
The constraints of edge computing favor the emergence of specialized SoCs, with very high energy efficiency, capable of processing data in real time. In production, advanced analytics, computer vision and digital twins help optimize manufacturing lines, reduce downtime and improve quality. Intelligent algorithms are also used to validate new designs, anticipate potential weaknesses and strengthen test coverage.
Manufacturers are increasingly working closely with AI experts and technology services players to design next-generation chips designed for AI workloads. The French fabless manufacturer Kalray stands out, for example, in advanced processors intended for calculation-intensive applications, particularly in AI, telecoms and storage.
By capitalizing on these dynamics, France can strengthen the convergence between research, industry and technological services, develop deep tech skills and structure sovereign value chains around embedded AI and new generation semiconductors.
