Generative artificial intelligence (GenAI), including large language models (LLMs), is reshaping how knowledge is created, problems are formulated, ideas are generated, and solutions are evaluated.

Systematic Innovation, particularly through methodologies such as the Theory of Inventive Problem Solving (TRIZ), provides structured approaches to innovation based on contradiction analysis, inventive principles, patterns of technological evolution, and systematic problem-solving.

This Special Issue, “Systematic Innovation and Generative AI,” aims to explore the emerging intersection between systematic innovation methodologies and generative artificial intelligence. Particular attention will be given to studies that integrate Generative AI with systematic, structured, or theory-driven innovation methodologies.

It welcomes theoretical, methodological, computational, and application-oriented studies addressing new methods and frameworks for AI-assisted innovation, human–AI collaborative problem-solving, intelligent engineering design, knowledge and patent analysis, contradiction identification and resolution, technology forecasting, and AI-supported decision-making.

Topics of interest include, but are not limited to:

• Generative AI for Systematic Innovation and TRIZ
• AI-Enhanced Inventive Problem Solving and Contradiction Resolution
• Large Language Models for Systematic Innovation
• Generative AI for Knowledge Discovery and Innovation
• Human–AI Collaboration in Systematic Innovation
• Generative AI for Engineering Design and Product Innovation
• AI-Assisted Technology Forecasting and Patent Intelligence
• Frameworks and Industrial Applications of Generative AI in Systematic Innovation