AI is everywhere in 2025. It is influencing different industries and the way we think, act, and plan our lives. As edge computing and AI move closer to the user, electronic components are evolving fast and engineers, buyers, and designers need to be able to keep up with this change.
In this article, we’ll check these changes and help you stay informed.
What Is Edge AI? (And Why Should You Care)
Edge AI means running AI tasks (like facial recognition or predictive maintenance) on the device instead of the cloud. This is important for:
- Speed: Instant response, no cloud latency
- Privacy: Data stays local
- Energy: Less back-and-forth means lower costs
- Reliability: It works even when offline
According to Statista, edge computing is growing at a great speed and will reach $350 billion by 2027.
How AI Is Shaping the Electronic Components Demand
Here’s how this is influencing the demand for electronic components:
Power Management Is Becoming Critical
Edge devices often run on batteries (smartwatches, earbuds, wearables, smart tags, and so on). They need to perform AI tasks (like gesture recognition or voice control) without draining the battery in a few hours. That’s where ultra-efficient PMICs (Power Management Integrated Circuits) and low-dropout regulators come in.
You’ll also see more intelligent power switching, sleep modes, and dynamic voltage scaling. In 2025, power efficiency is everything.
AI-Capable Microcontrollers (MCUs) Go Mainstream
Microcontrollers aren’t what they used to be. New AI-enabled MCUs come with:
- On-chip machine learning acceleration
- DSPs for fast signal processing
- TinyML support for running lightweight AI models
Here are some popular options in 2025:
- STM32H7 (STMicroelectronics): used in smart health devices
- NXP i.MX RT1170: used in edge voice assistants
- Kendryte K210: optimized for vision-based tasks
Smarter Sensors With Pre‑Processing
Sensors can now preprocess data, filter noise, and even perform local classification tasks. For example, a camera module can only send alerts when it detects a person, not every time something moves.
Sensors with built-in intelligence reduce system workload and latency, and these are all huge wins in wearables, vehicles, and industrial machines.
Memory and Storage Level Up
AI models (even the tiny ones) need memory. In 2025, designers are leaning into:
- LPDDR5 and LPDDR5X: They’re fast and efficient
- MRAM (Magnetoresistive RAM): They retain data without power
- HBM (High Bandwidth Memory): High capacity, ultra-fast access
The more complex these devices are, the more memory they need. And the market is here to respond to the growing demand.
What This Means for Engineers and Buyers
If you’re designing hardware or sourcing components, you need to adapt to this change. Here’s what it means for:
Engineers
AI is moving pretty fast. What’s new today can feel outdated in just six months. Hardware engineers now have to think in versions. Is your microcontroller or SoC capable of handling unexpected updates? Can it support newer AI models if you upgrade the firmware? You have to design with future improvements in mind.
This is why engineers are increasingly leaning toward modular PCB layouts that allow for easier upgrades. Think plug-and-play AI modules or daughterboards. That way, when a new AI accelerator hits the market, you don’t need to change your whole design.
Procurement
Components like AI-optimized memory (LPDDR5, GDDR6), neural processors, and vision sensors are in high demand, and supply isn’t always keeping up. Start talking with suppliers early on and monitor which parts are available regularly.
Startups
Many MVPs (minimum viable products) start with cloud-based AI for simplicity, but that’s not always scalable. If you expect your device to be used in areas with poor connectivity or need faster response times, edge AI becomes essential.
You also have to think about what parts will be available in 6 months. Will your AI pipeline still run efficiently on the same hardware?
The AI Revolution Is in the Details
The glamour of AI is everywhere around us. Humanoid robots and self-driving cars are a hot topic. But the real magic often happens where you don’t see it: on a PCB the size of your thumb, quietly running models, making decisions, and powering the AI-driven world around you.
As edge AI grows, it’s pulling the electronics world with it. And the winners won’t just be the ones with the flashiest software, but the ones with the smartest, leanest, most forward-thinking components.
