en.Wedoany.com Reported - Although AI has grown rapidly in many fields, its application has been more stable due to the complexity of the semiconductor industry. In 2026, AI-driven workflows will move from concept to deployment, bringing technical challenges and talent demands. Niels Faché, Senior Vice President of Design Engineering Software at Keysight Technologies, outlined the key trends for the year.
The role of prompt engineer will emerge, enabling interaction with EDA tools through natural language. Enterprises will need to support dual modes: traditional GUI and AI conversations. Small language models are gaining attention due to security and intellectual property protection concerns, prompting vendors to launch specialized localized AI tools. Synthetic data generation addresses data shortages but comes with high computational costs. Standardization will drive AI adoption, with digital design integrating AI more quickly due to mature standards. A disconnect between executives' high expectations for AI and engineering realities may cause friction, making it essential for companies to focus on measurable scenarios. Specialized skills are critical, with experts needed in fields like photonics, AI/ML. Enterprises are shifting towards internal training. The talent acquisition model will change in 2026, with internal training becoming a core strategy and talent retention deemed more critical than hiring. AI will reshape roles, enabling engineers to focus more on decision-making, but junior engineers will face a steeper learning curve.
The demand for talent and process in future innovation is as important as technology. Enterprises need to increase investment in employees to build smarter, faster, and more resilient systems. The design engineering software field is on the verge of a profound AI-driven transformation.
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