Automatically merging duplicate files refers to using software to identify identical or similar file copies and then combining them into a single version. It works differently from simply detecting duplicates (which identifies copies for manual review) or manual merging (which involves comparing files line-by-line). Automated merging focuses on replacing multiple redundant copies with one file, reducing clutter. Some tools compare file content bit-by-bit for perfect matches, while others may analyze content similarity for near-duplicates, though automatic resolution is safest only for true exact copies.

Common use cases include organizing personal digital libraries, like merging duplicate photos or documents in cloud storage services (Google Drive, iCloud) or dedicated desktop organizers. Developers also use version control systems like Git to automatically merge code files when changes occur in different branches, provided no conflicts exist in the same lines. This prevents manual error in repetitive tasks.

The key advantage is immense time savings and storage reduction. However, limitations are significant: blindly merging files with potential subtle differences can cause critical data loss. Automated merging is generally reliable only for confirmed exact duplicates. For files with variations, human review is essential to prevent merging conflicting content, preserving data integrity. Future tools may use smarter content analysis to suggest merges more safely.