Overall, the survey results indicated that while engineers believe AI will play an increasingly important role in component selection in the future, concerns persist regarding the potential for intentional or unintentional bias in AI systems. Some designers stated they would entrust AI with part of the selection task as long as they performed the reviews and verifications themselves. Although most respondents welcome complementary AI, they also believe that humans will always be necessary as part of the selection process, particularly for safety-critical systems and innovative designs.

Among the interesting opinions were the following:

A retired systems engineer said, "AI is no substitute for good engineering calculations. I've been following AI for over 40 years, and it's more overrated than ever." When others pointed out that humans make mistakes, this engineer said, "I'm more willing to tolerate human error than to rely on an AI solution where I have no control over the data used to train its model." This reflects concerns that engineers may not fully understand why an AI module selects certain products.

Another respondent highlighted the widespread view that AI could be more useful as an assistant rather than a replacement. They said, "That comes with the caveat that I would reserve the right to review everything the AI ​​selected. In that sense, AI would be used as a kind of enhanced search engine."

One respondent who supports using AI said, "I don't see why AI can't be fully integrated into the component selection process. Hardware design is fundamentally pattern-based. It's only a matter of time before people figure out how to get network lists and schematic PDFs online and use them as good-quality training data for AI. In fact, AI will be able to improve upon them once better digital representations of devices and their internal components, along with telemetry from all subsystems, are available. AI has a vast and abundant collection of resources it can draw upon to learn even more. There are already completely generic AI systems that can make impressive, albeit limited, selections, even by building simple VHDL, for example. You specify what logic to use and how to assemble it. The AI ​​writes the code for me. I just have to review it."

Another frequent user of AI for component selection, however, expressed reservations about AI's capabilities, stating that AI modules still have much to learn about reliability and how to make the best decisions consistently.

Cliff Ortmeyer, Global Head of Technical Marketing and Solutions Development at Farnell, says: "The survey results clearly show that engineers are beginning to see AI playing a role in component selection in their designs, especially when safety or innovation needs to be considered. As AI models advance, it's clear they will become more useful for modeling designs, selecting components, shortening design cycles, and reducing time to market for new products."

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