Mind the Language Gap: Building an Inclusive AI Future for Southeast Asia

Southeast Asia’s AI systems remain predominantly trained on English and a handful of global languages, leaving over 1,000 regional languages underrepresented. This piece argues that closing this linguistic gap through initiatives like SEACrowd — which curates datasets for nearly 1,000 SEA languages and benchmarks performance across 38 languages — is essential for equitable digital inclusion and for preventing harmful misinterpretations in critical sectors like healthcare.