AI-assisted virtualization software has hadbeen aused profound impact on various sectors. It has revolutionizedin cloud computing byto optimizingoptimize the use of resources and significantly reducingreduce costs. In healthcare, thethese technologies technologyhave isbeen used to create virtual patient profiles that can be easily accessed and updated, improving diagnosis and treatment. ItThey isare also used in data centers to improve performance and energy efficiency.<ref>{{Cite book |last=Anwar |first=Mohd. Sadique Shaikh |title=Bigdata and Business Virtualization |year=2018 |isbn=978-6139872022}}</ref> It has also been used in network function virtualization (NFV) to improve virtual network infrastructure.<ref>{{Cite book |last1=Jagannath |first1=Jithin |last2=Ramezanpour |first2=Keyvan |last3=Jagannath |first3=Anu |title=Proceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning |chapter=Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks |date=2022-05-16 |chapter-url=http://dx.doi.org/10.1145/3522783.3529519 |pages=81–86 |___location=New York, NY, USA |publisher=ACM |doi=10.1145/3522783.3529519|isbn=9781450392778 |s2cid=247957748 }}</ref>
Furthermore, AI-assisted virtualization has had notable contributions in the field of network function virtualization (NFV). It has enabled a more dynamic and flexible virtual network infrastructure, capable of auto-scaling based on network load, identifying potential threats, and autonomously recovering from faults.<ref>{{Cite book |last1=Jagannath |first1=Jithin |last2=Ramezanpour |first2=Keyvan |last3=Jagannath |first3=Anu |title=Proceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning |chapter=Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks |date=2022-05-16 |chapter-url=http://dx.doi.org/10.1145/3522783.3529519 |pages=81–86 |___location=New York, NY, USA |publisher=ACM |doi=10.1145/3522783.3529519|isbn=9781450392778 |s2cid=247957748 }}</ref>
