The State of AI in Embedded Engineering 2025
Gain exclusive insight into how embedded engineers are adopting, implementing, and evolving with AI — and what it means for your product strategy.
Understand the Future of AI in Embedded Design
AI is no longer experimental in embedded systems — it’s a design reality shaping performance, security, and time-to-market.
This 100+ page report reveals where engineers are investing, what tools they trust, and how their adoption patterns are redefining competitive advantage.
Built from survey data of 301 qualified engineers worldwide, this study quantifies the trends driving embedded innovation — from in-house AI deployment to hybrid edge-cloud architectures, open-source ecosystems, and security-first design.
What You'll Learn:
How engineers are integrating AI at the edge — and what’s driving or slowing adoption
The frameworks, processors, and ecosystems defining embedded AI development
Where engineers see the greatest value and performance gains from AI
The top barriers: data, security, explainability, and integration
How marketers can position products for an AI-accelerated design audience
Designed for technology marketers, product leaders, and ecosystem strategists
This report helps you:
Identify where your customers are in the AI adoption curve
Translate engineer sentiment into actionable product and content strategies
Benchmark your brand against the vendors engineers trust most
Discover emerging opportunities in automotive, IoT, and industrial AI design
Whether you’re shaping go-to-market messaging or planning your next-generation roadmap, these insights deliver the clarity you need to engage engineering audiences with precision.
Chapters include:
1.
Demographics & Decision Influence – who today’s embedded AI engineers are, and what they buy
2.
Experience & Outlook on Embedded AI – from early experimentation to production deployment
3.
Project Characteristics & Open Source Adoption – how tools, OSs, and connectivity shape design
4.
Techniques & Performance Benefits – where AI delivers measurable design value
5.
AI Tools & Frameworks – the platforms engineers rely on most
6.
Challenges, Data & Security Constraints – what’s slowing progress and how vendors can help
7.
Automotive AI Applications – use cases leading the next generation of mobility
8.
Chip Type & Vendor Usage – which vendors and ecosystems dominate design choices
9.
Learning Methods & Media Consumption – how engineers upskill and where they turn for trusted information
Each section includes analytical takeaways and marketing implications, connecting technical realities to go-to-market relevance.
AI is reshaping embedded systems — and engineer expectations.
The brands that understand how engineers are learning, designing, and integrating AI will own the next wave of influence. Use this data to align product positioning, content strategy, and innovation messaging with what truly drives design decisions.
Get the full report today
Complete your purchase to download The State of AI in Embedded Engineering instantly as a PDF.
AI in Embedded Engineering
AI in Embedded Engineering
$4,995
113 pages
Digital PDF (instant download)
The AI Trends and Innovations Within Embedded Systems study was conducted by Wilson Research Group, LLC and EETech Media, LLC in partnership. The report presented here is provided by EETech Media, LLC.
All rights reserved. The report is for internal organizational use only and may not be redistributed externally.
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