While AI can accelerate the decipherment of lost languages by quickly analyzing patterns and clusters of words, it cannot provide definitive translations or meaning on its own. The AI model learns statistical relationships between symbols and words but lacks true comprehension, making verification difficult without native speakers or established linguistic consensus.

This challenge is amplified by small surviving text corpora, such as Linear A's ~7,500 characters, where almost any hypothesis can find superficial support. Consequently, claims in this field rely on independent expert scrutiny and peer review, distinguishing between AI identifying a pattern and AI discovering correct meaning.

Despite these limitations, AI is a powerful tool, compressing years of manual cross-referencing into minutes and enabling broader participation in decipherment efforts. However, human review and a genuine comparative anchor remain crucial, alongside AI's speed, to distinguish breakthroughs from coincidences in ancient linguistic puzzles.