QUANTUM COMPUTING ASSISTED REDUCTION OF CARBON FOOTPRINT

The present disclosure describes a system and method for applying classical machine learning together with quantum machine learning to extract features from a draft email and from metadata of the draft email to identify issues that can influence the carbon emissions caused by the draft email upon sending. The system and method can further determine specific modifications for the draft email that can reduce the carbon emissions caused by the draft email upon sending. The system and method can offer the user with a selection to have the draft email automatically modified to reduce carbon emissions. The method may further include analysis of job profiles and behaviors of individual employees to determine whether the draft email is relevant to the recipients in the "to:" field of the draft email, as well as to provide analytics related to carbon emissions associated with emailing and printing behaviors of employees.