Arabic-First AI: Building From the Ground Up

Building effective AI for the Arab world requires an "Arabic-first" approach, as simply translating English systems fails to account for linguistic diversity and cultural context. This method involves creating systems from the ground up, using native Arabic data pipelines, in-language data labeling by local experts, and models tuned for regional dialects and terminology. Evaluation must extend beyond fluency to test for factuality, cultural fit, and safety, while local governance ensures data is controlled within the region. To ensure adoption, this approach is paired with Arabic-language upskilling programs that build institutional capability and user trust by teaching professionals how to apply AI within their specific workflows.