What Every Industrial Engineer Should Know About Artificial Intelligence in the Development of Industrial Patents: Innovation, Intellectual Property, and Responsible AI in Industrial Engineering

Artificial intelligence is expanding the technological resources available to industrial engineers for problem identification, design optimization, predictive modeling, process innovation, and technical knowledge management. These developments create opportunities for invention while raising questions about intellectual property, ownership of results, inventorship, transparency, reliability, and protection of confidential information.

This book outlines an interdisciplinary approach to the use of artificial intelligence in the development of industrial patents. The proposed framework combines industrial engineering, innovation management, patent information analysis, technical documentation, and responsible AI governance. It is organized into four units: (I) AI and industrial engineering innovation; (II) invention development and patent intelligence; (III) patent strategy, documentation, and legal-technical considerations; and (IV) implementation, technology transfer, and responsible innovation.

The manuscript is designed as a conceptual and applied educational resource for students, researchers, engineers, innovation managers, and technology-transfer professionals. Suggested activities include technical problem mapping, prior-art search planning, invention disclosure drafting, and creation of a patent-oriented innovation roadmap. The text distinguishes AI-assisted work from proof of patentability and emphasizes human verification, jurisdiction-specific legal review, and evidence-based assessment.

Its intended contribution is a coherent pedagogical foundation for managing AI-assisted industrial inventions without overstating the capabilities of automated systems or confusing technical innovation with the legal grant of patent rights.