Recent breakthroughs in AI-driven research have significantly accelerated Carbon Capture and Utilization capabilities, delivering tangible gains in efficiency, cost, and speed. For example, the reduction of CO₂ simulation times from 100 days to 24 hours by replacing traditional supercomputer-based models with an AI-powered surrogate. In cement production, an AI-managed absorption system reportedly trimmed energy consumption by over 20%, while generative AI screening of 100,000 hypothetical metal-organic frameworks (MOFs) pinpointed new sorbents boasting 25% higher CO₂ capacity than conventional materials. These real-world examples underscore how AI can drive down costs and expedite innovation in both capture processes and CO₂-to-product pathways. This presentation aims to compile all those new AI technologies and create a framework for further development of these tools as well as CCU technologies.