The AI Impact Award, presented by the German business newspaper manager magazin and Porsche Consulting, honors companies that successfully and effectively apply artificial intelligence in real-world practice. The award highlights solutions that create genuine economic and societal added value.
Infineon has been nominated for the AI Impact Award 2026 in the Production and Supply Chain category, which recognizes solutions that make processes across manufacturing, logistics, and supply chains more efficient, secure, or sustainable. In a short interview, Adrian Schmid, Senior Manager Digital Engineering & Customer Solutions in Infineon’s Power & Sensor Systems division, explains the challenges his team faced, how the AI-based approach was developed, the results achieved to date – and how Infineon is systematically advancing digitalization in chip development and manufacturing.
Mr. Schmid, what are the biggest technical and organizational hurdles in developing complex semiconductor test programs?
Developing test programs for semiconductors is a highly complex and time-consuming process. Test engineers must take into account large volumes of specifications, documentation, and test-specific details – often across multiple test platforms. This results in long development cycles, a strong reliance on individual experts, and limited reusability of existing test programs. At the same time, product complexity and time pressure continue to increase. From an organizational perspective, the sheer number of teams, tools, and processes makes consistent standardization difficult. The outcome is a process that is critical to quality and time-to-market, yet remains a structural bottleneck. For a semiconductor manufacturer with stringent requirements for quality and reliability, test engineering is a key lever for delivering robust products while maintaining rapid market entry.