This paper discusses selected publications that relate cybersecurity to artificial intelligence (AI) in general and to machine learning (ML) specifically. The focus is cybersecurity in the context of software development and lifecycle environments (SDLE) and their products. Because of the large volume of publications in this area, the survey includes publications that are themselves surveys of specialized subjects. A few papers are cautionary, pointing out that systems trained using AI/ML can be fooled; one of these papers investigates methods for the design of classifiers that exhibit resilience to adversarial actions and points to other literature in this emerging field. Several references are books, and the discussions of these provide some guidance for those who might be interested in further reading across the breadth of the field. A few relevant publications from the NIST 800 series are included as background to provide an appropriate setting for the discussion of AI/ML as applied to cybersecurity.