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== Functionality ==
AI-assisted virtualization software operates by leveraging AI techniques such as [[machine learning]], [[deep learning]], and [[neural network]]s to make more accurate predictions and decisions regarding the management of virtual environments. Key features include intelligent automation, [[predictive analytics]], and dynamic resource allocation.<ref>{{Cite book |last1=Sharma |first1=Sachin |last2=Nag |first2=Avishek |last3=Cordeiro |first3=Luis |last4=Ayoub |first4=Omran |last5=Tornatore |first5=Massimo |last6=Nekovee |first6=Maziar |title=Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies |chapter=Towards explainable artificial intelligence for network function virtualization |date=2020-11-23 |chapter-url=http://dx.doi.org/10.1145/3386367.3431673 |pages=558–559 |___location=New York, NY, USA |publisher=ACM |doi=10.1145/3386367.3431673|isbn=9781450379489 |s2cid=227154563 }}</ref><ref>{{Cite book |title=Artificial intelligence for autonomous networks |date=2019 |publisher=CRC Press, Taylor & Francis Group |isbn=978-0-8153-5531-1 |editor-last=Gilbert |editor-first=Mazin |series=Chapman & Hall/CRC artificial intelligence and robotics series |___location=Boca Raton London New York}}</ref>
* Intelligent Automation: Automating tasks such as resource provisioning and routine maintenance. The AI learns from ongoing operations and can predict and perform necessary tasks autonomously.
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