By Philip Stoten
At APEX 2025, I had the opportunity to speak with four industry leaders about AI implementation in electronics manufacturing. While there’s significant enthusiasm around AI, these conversations revealed a refreshing focus on practical applications over hype.
Chintan Sutaria emphasized identifying specific business problems before applying AI solutions. He cautioned that AI isn’t always the right tool: “It’s really important to recognize what is the most pressing problem you want to solve and then evaluate whether AI is a valid tool to solve that problem.” Chintan also raised important concerns about data security, particularly with trade-controlled products.
Mark Besser of Symphony AI acknowledged the mixed industry sentiment: “There’s enthusiasm, there’s excitement, there’s curiosity, there’s fear, there’s paralysis.” Mark sees AI’s greatest value for contract manufacturers in time optimization, noting that “time is killer—time is labor and that’s where my cost is.” He also observed that many companies “don’t really need AI, they need help” with fundamental data management.
Philip Gulley described Cofactr’s approach to AI as “insanely boring and very practical,” which is exactly what the industry needs. Their system proactively identifies potential supply chain disruptions, connecting “bills of materials to purchase orders, invoices, and packing slips.” Philip emphasized the foundation of good data: “How do you get that foundation of data accurate and accessible?”
Timon Ruban of Luminovo shared his renewed enthusiasm for AI with the advent of large language models. He’s focusing on converting unstructured data to structured data—”PDFs, that’s the heartbeat and email and Excel of the supply chain.” Timon explained his framework for effective AI: “To really make it work for your decision-making workflow is basically context and tools.”
These discussions revealed common themes: focus on specific business problems, ensure quality data foundation, start with well-defined projects, and leverage human-AI collaboration rather than seeking full automation. The industry is learning from the disappointment of many Industry 4.0 initiatives and taking a more measured approach to AI adoption.
The electronics manufacturing industry appears to be approaching AI with a healthy mix of enthusiasm and pragmatism, finding ways to cut through the hype and deliver solutions that address real business needs.
