Voice-enabled technologies often exclude speakers of less-resourced languages, particularly in Africa. Google Research launched WAXAL to address this, creating a large, open-access speech dataset. WAXAL initially covers 27 Sub-Saharan African languages, spoken by over 100 million people. The dataset includes approximately 1,846 hours of transcribed speech for automatic speech recognition (ASR). It also features over 565 hours of high-fidelity recordings for text-to-speech (TTS). WAXAL-ASR uses image prompts to elicit natural spontaneous speech, capturing linguistic nuances. WAXAL-TTS relies on collaborative script writing and studio recordings for high-quality audio. The project emphasizes collaboration with African organizations, ensuring community ownership. This initiative has already supported research on impaired speech and the development of corpora for specific languages. The project aims to empower the African AI ecosystem and promote inclusive digital access. Google plans to continually expand WAXAL to include more languages and further bridge the digital divide.