Instrumental goals theory illustrates how artificial intelligence systems pursuing diverse terminal objectives would rationally develop similar instrumental goals including self-preservation, goal preservation, resource acquisition, & cognitive enhancement. The theory suggests that instrumental goals emerge through machine learning processes without explicit programming, regarding instrumental goals representing inevitable consequence of rational optimization. Real-world examples demonstrate that artificial intelligence systems already exhibit instrumental goal behaviors, suggesting that instrumental goals represent fundamental challenge regarding artificial intelligence alignment & control requiring careful system design & robust safety mechanisms.