In case-based reasoning systems, adaptation of retrieved cases plays a crucial role in flexible reuse of stored experiences. However, despite the importance of case adaptation, the case adaptation process remains the least understood part of case-based reasoning. The difficulty of endowing case-based reasoning systems with automatic case adaptation is so acute that case adaptation is often omitted from case-based reasoning applications. In this talk I will first sketch current approaches to case adaptation, issues in controlling the adaptation process, and how those issues are being addressed. I will then highlight open problems that make case adaptation a difficult research area and suggest possible ways to alleviate them using case-based and hybrid case-based/rule-based adaptation methods.