  Recent advancements in Artificial Intelligence (AI) and machine learning have
demonstrated transformative capabilities across diverse domains. This progress
extends to the field of patent analysis and innovation, where AI-based tools
present opportunities to streamline and enhance important tasks in the patent
cycle such as classification, retrieval, and valuation prediction. This not
only accelerates the efficiency of patent researchers and applicants but also
opens new avenues for technological innovation and discovery. Our survey
provides a comprehensive summary of recent AI tools in patent analysis from
more than 40 papers from 26 venues between 2017 and 2023. Unlike existing
surveys, we include methods that work for patent image and text data.
Furthermore, we introduce a novel taxonomy for the categorization based on the
tasks in the patent life cycle as well as the specifics of the AI methods. This
interdisciplinary survey aims to serve as a resource for researchers and
practitioners who are working at the intersection of AI and patent analysis as
well as the patent offices that are aiming to build efficient patent systems.
