Can AI design circuit boards yet?

The EEBench project explores the current capabilities of artificial intelligence in the field of printed circuit board (PCB) design. As AI continues to disrupt various engineering sectors, this analysis investigates whether generative models and automated tools have reached a level of maturity sufficient to handle the complex constraints of hardware layout. The article examines the practical challenges of PCB design, including signal integrity, thermal management, and manufacturing requirements, which often prove difficult for current AI architectures to navigate autonomously. By evaluating existing benchmarks and design workflows, the authors provide a realistic assessment of the gap between theoretical AI potential and real-world hardware engineering applications. The study concludes that while AI shows promise in assisting with routine tasks and component placement, human expertise remains indispensable for complex, high-performance circuit design, suggesting that full automation in this domain is still a developing frontier.