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Autism is one of the most prevalent neurodevelopmental conditions globally, and healthcare professionals including pediatricians, developmental specialists, and speech-language pathologists, play a central role in guiding families through diagnosis, treatment, and support. As caregivers increasingly turn to digital platforms for autism-related information, artificial intelligence (AI) tools such as ChatGPT, Gemini, and Microsoft Copilot are emerging as popular sources of guidance. However, little is known about the quality, readability, and reliability of information these tools provide. This study systematically evaluated responses from the three AI tools to 44 caregiver-focused questions spanning two key domains: foundational knowledge and practical supports. Responses were assessed across three countries (USA, England, and Türkiye) and two languages (English and Turkish), and coded for accuracy, readability, actionability, language framing, and reference quality. Results showed that ChatGPT generated the most accurate content but lacked reference transparency; Gemini produced the most actionable and well-referenced responses, particularly in Turkish; and Copilot used more accessible language but demonstrated lower overall accuracy. Across tools, responses often used medicalized language and exceeded recommended readability levels for health communication. These findings have critical implications for healthcare providers, who are increasingly tasked with helping families evaluate and navigate AI-generated information. This study offers practical recommendations for how providers can leverage the strengths and mitigate the limitations of AI tools when supporting families in autism care, especially across linguistic and cultural contexts.