Email occupies a central role in the modern workplace. This has led to a vast increase in the number of email messages that users are expected to handle daily. Furthermore, email is no longer simply a tool for asynchronous online communication---email is now used for task management, personal archiving, as well both synchronous and asynchronous online communication. This explosion can lead to ``email overload''---many users are overwhelmed by the large quantity of information in their mailboxes. In the human--computer interaction community, there has been much research on tackling email overload. Recently, similar efforts have emerged in the artificial intelligence (AI) and machine learning communities to form an area of research known as intelligent email. In this paper, we take a user-oriented approach to applying AI to email. We identify enhancements to email user interfaces and employ machine learning techniques to support these changes. We focus on three tasks---summary keyword generation, reply prediction and attachment prediction---and summarize recent work in these areas.