AI in PCB design: hype or the future of engineering?

The world of electronics design is constantly evolving, and few topics are generating as much buzz (and sometimes apprehension) as Artificial Intelligence (AI). Is AI just a passing fad, or is it set to fundamentally transform how we approach Printed Circuit Board (PCB) design?

In last season’s episode of The Printed Circuit Podcast, host Steph Chavez sat down with Andre Alcaldé, co-founder of CELUS, to explore the role of AI in PCB design and the broader electronics engineering landscape. As someone with a deep background in hardware design, Alcaldé shares his unique perspective on how AI can optimize workflows, reduce design iteration time, and future-proof engineering careers.

AI in PCB design: fad or here to stay?

Alcaldé firmly believes that AI is not a passing fad. “I think AI is here to stay,” he states. He elaborates, “it has such a transformational nature, and it’s already helping a lot of people on the most varied tasks that we can think of.” From the widespread adoption of Large Language Models (LLMs) for text and graphics generation, AI is already proving its utility in saving time and empowering individuals. This implementation into various industries, including electronics engineering, is only set to deepen, indicating that AI is here to stay and will continue to transform our work.

Automation vs manual workflows: to what extent can AI take over PCB design, and what tasks will remain in human hands?

When considering the extent of AI’s automation in PCB design, Alcaldé draws a compelling parallel to the evolution of digital design for integrated circuits. Decades ago, IC design was a manual, transistor-by-transistor process. As complexity grew, automation tools (like synthesizers and place-and-route algorithms) emerged, shifting engineers’ focus from meticulous manual tasks to defining more complex systems and rigorous validation. Alcaldé predicts a similar trajectory for PCB design. AI-based automation will handle more complex, repetitive tasks, allowing engineers to dedicate more time to defining intricate design requirements, system architectures, and rigorous testing and simulation. This shift is not about replacing engineers but empowering them to tackle greater complexity and innovate faster. As Alcaldé puts it, “AI will allow us to deal with more complex designs. It will tackle complexity for sure.”

How companies can ensure data privacy and protect their intellectual property when using AI tools

A significant concern for many companies is the privacy and security of their intellectual property (IP) when using AI models. Unlike general LLMs trained on vast public datasets, PCB design data is proprietary and critical to competitive advantage. Alcaldé suggests a “hybrid approach” to address this: AI models can be pre-trained on foundational electronics design principles (specific design rules, university-level knowledge), creating a baseline understanding. Companies can then fine-tune these baseline models using their own proprietary data, design rules, and industry-specific approaches (automotive, consumer electronics). Critically, these fine-tuned models operate within a closed, secure environment (on a company’s cloud instance), ensuring no data leakage and maintaining IP confidentiality. This approach mitigates the risk of sensitive data being exposed, allowing companies to leverage AI’s power without compromising their competitive edge.

The changing skillset for engineers: how AI is shifting the role of PCB designers from execution to problem-solving and validation

The advent of AI will undoubtedly reshape the required skill sets for PCB designers and electrical engineers. The focus will shift from “doing specific tasks” to more strategic roles. Alcaldé explains, “I think a lot of the focus will turn from doing specific tasks to being able to analyze results, being able to constrain the problem so that the automation or the AI in this case is able to understand exactly what is to be done.” Engineers will need to excel at problem definition, clearly articulating design constraints and requirements for AI to understand. They will also need strong analytical skills to critically evaluate AI-generated solutions and understand trade-offs, alongside mastering simulation, and testing methodologies to ensure design integrity. The goal is to move beyond simply looking up datasheets to evaluate multiple complex solutions and optimize designs.

Job market impact: will AI reduce or increase opportunities in the PCB design field?

The fear that “AI will take my job” is a common one. However, Alcaldé believes AI will increase job opportunities in the PCB design field. With the ever-growing demand for smarter, connected devices, there is already a significant skill shortage in the electronics industry. AI will help alleviate this by tackling complexity, enabling engineers to design more intricate devices, which in turn increases demand for their expertise. It will also allow engineers to concentrate on higher-value, more innovative aspects of design. Just as automation in the semiconductor and software industries led to increased demand for professionals, AI in PCB design is expected to follow a similar path, driving growth and innovation.

The reluctance to adopt AI: why some companies are still hesitant and how expectations influence adoption

Despite the clear benefits, reluctance to adopt AI-driven solutions persists. Alcaldé attributes this largely to expectations, adding that “a lot of people have the impression or the expectation that AI is going to provide them with the correct answer always the first time.” The key is a mindset shift: view AI not as an oracle, but as a collaborator that augments human capabilities. AI can quickly generate multiple design variants, offer creative solutions, and help engineers think outside the box. Crucially, validation is always key, as models are trained on data and may not always capture every nuance. Alcaldé explains, “It’s not anymore the expectation, AI is going to do my job in the first time right, but it is much more AI is going to help me actually achieve a more optimized solution.” This collaborative approach unlocks the true potential of AI.

Speeding up time to market: how AI-driven automation can significantly improve design iteration cycles

AI promises to significantly improve design iteration cycles and, consequently, reduce time to market for new products. By streamlining the design process from constraint definition to architectural design, schematics, and PCB layouts, AI enables faster iteration. Engineers can quickly fine-tune constraints, regenerate outputs, and run simulations, leading to rapid design cycles. This creates a more agile approach, allowing engineers to iterate quicker and be more confident that their designs meet requirements before moving to production. It also reduces the variability often introduced by individual engineer experience levels. This agile approach is crucial in today’s fast-paced market, where the window of opportunity for new products can be incredibly small.

Balancing automation, creativity, and human oversight

The primary risk, as Alcaldé highlights, is “having this mindset of blindly trusting what the AI is generating without really evaluating or without really verifying what is being put out.” Understanding the limitations of different AI models and always validating outputs is crucial. However, the rewards, in Alcaldé’s view, far outweigh the risks. He states, “finding new solutions for existing problems…thinking a bit out of the box is one of the rewards that AI has to offer.” Ultimately, this benefits society by allowing “more complex and perhaps more satisfying products brought to the market.” Chavez eloquently summarizes the ultimate risk: “What is the cost of doing nothing and staying status quo and continuing using a legacy approach? It’s trying to attack today’s complex designs…the risk of doing nothing and potentially getting left behind or outpaced by your competitor.”

Closing thoughts on AI and innovation in PCB design

AI is poised to bring significant innovation to the electronics design industry. By better handling the vast diversity of components and complex design rules, AI offers an opportunity to elevate the industry, empower engineers, and address the growing skill shortage. Companies like CELUS are actively working to unlock this value, helping engineers move from architectural design through schematics and bill of materials with the power of machine learning and AI. Alcaldé concludes, “If we do nothing about that, I think it’s going to be pretty soon that we’ll have a limitation or a cap on the complexity of designs that we see or the number of new products brought to the market. And with AI, I think we can unlock that.” The future of PCB design is not about AI replacing human ingenuity, but rather augmenting it, fostering a new era of collaboration between engineers and intelligent systems. Those who embrace this shift will undoubtedly lead the way in delivering the next generation of innovative electronic products.

Listen to the full podcast here: https://blogs.sw.siemens.com/podcasts/printed-circuit/how-ai-is-changing-pcb-design-forever-and-what-it-means-for-you/

If you liked this article, you might also like our LinkedIn live session with Andre Alcaldé and David Wiens. https://www.linkedin.com/events/7288260306080776192/