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Nordic Semiconductor integrates AI-assisted tools across full IoT product lifecycle
Nordic Semiconductor now offers AI-assisted tools across the full IoT device lifecycle, from early prototyping to post-deployment debugging. It claims to be the first wireless IoT platform to integrate AI support at every development stage.
Nordic Semiconductor Rolls Out AI Tools Across IoT Device Lifecycle
Nordic Semiconductor has made AI-assisted development tools available across the full lifecycle of wireless IoT devices, from prototyping through deployment and maintenance. The company said its chip-to-cloud platform is the first in the wireless IoT sector to integrate AI support at every development stage.
The platform combines hardware, software, and cloud services into a single system. Developers can use AI assistants during prototyping to turn ideas into proof-of-concept projects faster, and the tools remain available after devices ship for debugging and root-cause analysis.
What developers gain
AI assistants can reduce iteration cycles and lower costs associated with token usage while improving code reliability, Nordic said. The approach extends beyond typical embedded development, where AI assistance usually stops at code editing.
Once devices are deployed, developers access the same AI-assisted tools for troubleshooting without switching to separate systems. This continuity across the product lifecycle addresses common embedded development challenges: software migration, hardware configuration, and diagnosing problems in fielded devices.
How it works
The system works with AI assistants developers already use and is delivered through Nordic's MCP server infrastructure. Developers can choose which AI assistant to integrate with their workflow.
Vegard Wollan, Nordic's Chief Executive, said the company aims to "amplify" developer expertise rather than replace it. "Our ambition is to shape the next generation of developer experience in low-power wireless IoT," he said.
Jo Uthus, Executive Vice President of Marketing and Developer Experience, framed the capability as merging separate workflows into a single conversation. "This is the first step of a long commitment," he said.
The capability is available now.
Developers implementing AI-assisted workflows across product lifecycles may find value in exploring AI for Software Developers or AI Coding Courses to build skills in this area.