Embedded systems hit USD $585 billion as edge AI grows

IoT Analytics estimates the embedded systems market at USD $585 billion, accounting for about 32% of the USD $1.8 trillion global electronic systems market.

The estimate makes embedded systems the second-largest pillar of electronics, according to the research company's latest market analysis. The study tracks 40 product categories across five technology layers, from microcontrollers and AI chipsets at the silicon level to industrial PCs, gateways, and embedded operating systems higher up the stack.

The findings point to a market being reshaped by changes in hardware design, software development, and security requirements. Artificial intelligence is a central factor, with computing workloads increasingly distributed across sensing nodes, local edge systems, and cloud infrastructure.

Developer shifts

For developers, the research identifies three main opportunities: building edge AI through a connected toolchain, using a general-purpose coding agent on embedded code, and validating software before hardware is available.

At the same time, the report argues that longstanding design assumptions are becoming less reliable. Developers can no longer size a design on compute alone, may lose time trying to fit new silicon into an existing workflow, and must now account for security across the full product lifecycle.

Together, these shifts suggest a broader change in the embedded sector. Engineering decisions increasingly span chips, memory, accelerators, software, and update requirements rather than focusing on a single component. Choices once treated separately are now more tightly linked.

Vendor priorities

For vendors, IoT Analytics sets out five priorities: designing for heterogeneous architectures, optimising the whole system, owning more of the development workflow, treating security as a lifecycle issue, and building around vertical use cases and partners.

The focus on heterogeneous architectures reflects how embedded products now combine different types of processors and accelerators within the same design. In practice, suppliers are being pushed to support more complex hardware and software combinations while keeping development and maintenance manageable for customers.

The recommendation to own more of the development workflow also points to a competitive shift beyond silicon alone. Toolchains, integration paths, and software support are becoming more important in determining how quickly developers can move from design to deployment.

Security also emerges as a structural issue rather than an isolated feature. The analysis frames it as a requirement spanning deployment, updating, and long-term maintenance, reflecting how embedded devices are increasingly connected and expected to remain in service for years.

AI influence

The market view comes as edge AI drives a rethink of where processing should happen and how devices should be architected. Instead of relying on a single compute model, developers must split tasks between constrained devices, local systems, and cloud resources, increasing the importance of system-level trade-offs.

That is changing the role of embedded engineers, according to the analyst behind the research. The work is moving away from basic component integration toward aligning compute, memory, and software choices with operational and security demands over a product's life.

"Embedded systems developers are becoming the backbone of the edge AI transition. Their role is shifting from integrating components to making heterogeneous compute work as one product. The real engineering challenge is no longer choosing Arm versus RISC-V, or an NPU versus a GPU, in isolation. It is deciding which architecture, accelerator, memory, and software stack best fit the workload and can still be deployed, updated, and secured over the product lifecycle. In edge AI, the winning architecture will be the one that makes the whole system work, not the one with the strongest component on paper," said Satyajit Sinha, Senior Principal Analyst at IoT Analytics.

The scale of the market underlines why these changes matter for suppliers across the electronics chain. With embedded systems representing nearly a third of the wider electronic systems market, shifts in design practice and development workflows are likely to affect semiconductor groups, software providers, and industrial equipment makers alike.

IoT Analytics said its market model covers products from low-level silicon through to systems and operating software, giving a broad view of where value is created in embedded designs. That breadth also reflects how the boundary between hardware and software decisions is becoming less distinct as AI workloads move closer to the edge.