Indigenous languages of the Americas face severe endangerment, and the scarcity of culturally grounded resources remains a critical barrier to revitalization efforts. We present the AmericasNLP 2026 Shared Task on Cultural Image Captioning for Indigenous Languages, the first shared task dedicated to generating captions for images depicting Indigenous cultures of the Americas, written in the Indigenous languages themselves. To support this, we introduce and publicly release a newly constructed dataset spanning five cultures and their dominant languages: Bribri, Guaraní, Yucatec Maya, Central Veracruz Nahuatl, and Wixárika. Evaluation follows a two-stage process, combining automatic evaluation using ChrF++ with human evaluation of the top-performing systems for each language. Eight teams participate, submitting 27 systems in total. Results indicate that the task remains largely unsolved: while the strongest systems produce understandable captions, they fall short on descriptive detail and, critically, cultural grounding.