Natural Language Processing (NLP) and artificial intelligence (AI) can now provide methods for automated identification and interpretation of large numbers of text documents, which has been shown to be useful in identifying enemy items. During this session, results from two research projects will be shown: (1) the use of Anthropic's Claude Sonnet model via Amazon Bedrock to conduct enemy identification and (2) the use of similarity indices and cluster analysis across multiple item types and programs. Join this session and takeaway practical guidance for organizations considering using these methods to identify and manage enemies, including: what steps you should consider to ensure enemy items are being identified appropriately; how NLP, LLMs, or AI might be used in the enemy item identification process; and how different types of enemy relationships and item content/formats interact.