Trends in components for embedded systems, IoT, and industrial automation

Over the last few years, priorities across embedded systems design have been shifting, sometimes subtly, sometimes abruptly. These days, energy savings, resilient hardware, and real-time data handling aren’t just selling points. They’re the heart of nearly every conversation in industrial automation and IoT development. Designers and manufacturers, facing volatile supply issues and mounting demands, find themselves adapting quickly.

By 2026, according to people deep in the field, edge AI, post-quantum security chips, and connectors built for rough handling will no longer be negotiable upgrades, but standard requirements. 

Markets are changing fast: IDC says edge computing could hit $380 billion globally by 2028. That’s no surprise with device counts likely to double from 15 billion (2023) to nearly 29 billion just four years on. So naturally, chipmakers have been scrambling to offer compact multicore CPUs, ASIC accelerators, and cameras with better vision sensors. These breakthrough pieces affect every level of electronic components distribution, shaping how quickly and efficiently IoT gets deployed.

Embedded intelligence getting closer to the edge

Walk into almost any lab or factory today, and you’ll find microcontrollers and processors equipped with features that once seemed premium, now treated as the norm. Gone are the days when developers had to choose between energy savings and raw pace. Today’s multicore MCUs can switch between power modes on the fly.

That’s especially relevant, since the next generation of IoT hardware is expected to draw energy from ambient light, noise, or nearby radio signals, if you believe predictions from N-iX about 2026’s embedded market. You’re already seeing microcontrollers with on-board AI doing localized anomaly detection, no trips to the cloud necessary. 

Miniature ASIC accelerators, which used to live in server racks, now sit inside rugged sensors and lightweight PLCs. Chiplet designs are squeezing costs and pushing die size down even more. Dual- and quad-core configurations? Those are just baseline with firmware threading now supporting both real-time control and background computing.

Pushing the boundaries: edge AI and vision tech

Edge-based AI, sometimes described as tinyML, is no longer a fringe topic. Today, a growing share of analytics, security checks, and pattern recognition happens right on the device, often powered by MCUs or integrated NPUs, instead of relying on remote data centers. Tighter regulations, less tolerance for lag, and rising expectations from manufacturers are driving these changes.

By the time 2026 arrives, IBM suggests nearly two out of three new industrial systems will run on-board AI acceleration. Under the hood, you’ll find inference engines trimmed for size, analog “AI” chips, specialized RAM, and hardware that supports vision processing right at the point where images are captured. 

Vision modules themselves are evolving: thermal cameras running without fans, cameras that minimize noise, and global shutter sensors are turning up wherever downtime has a real cost. For medical systems, IEC compliance is now table stakes. Stuff like smart inspection and predictive maintenance have become less of an exception and closer to a basic expectation.

Industrial IoT hubs are being built to handle all this extra data on the edge, often integrating vision modules, then only forwarding insights upstream.

Next-gen security and ruggedized connectivity

As embedded devices spread into critical infrastructure, the need for security has escalated rapidly. Hardware-based trust anchors, post-quantum cryptography components, and chip-level secure elements show up much earlier in the design process now.

Integrating these elements right from the beginning cuts down the need for expensive retrofits and improves long-term protection. Updates for firmware and physical copy protection, once optional, are standard across industrial systems these days. 

Meanwhile, the hardware connectors themselves are evolving, too. It’s not only about hitting higher data rates. These days, connectors have to survive shakes, bumps, chemicals, and heat, meeting stricter standards for compliance, especially across transport and automation settings. For factories and vehicle systems, rugged polymers and locking mechanisms have become the expectation.

Markets react and supply chains move

What happens when a global chip shortage exposes supply chain weaknesses? For one, manufacturers have stopped tying themselves to just a handful of vendors. They’re widening their networks, working more closely with regional suppliers, and building flexibility into their ordering systems.

That’s not just damage control, it’s become a competitive must, especially with the explosive growth in automotive electronics and smart infrastructure. Reports from industry analysts note that component traceability and the ability to push updates directly onto chips have become deal breakers for buyers. 

New sensors and software-defined hardware are changing the pace of deployments. Today, the focus is on less downtime, longer support cycles, and reducing maintenance headaches. As new tech rolls out into tricky domains, from environmental tracking to tightly choreographed industrial lines, the challenge is finding balance: keep up with innovation, but don’t lose track of reliability or compliance.