Countries build domestic AI capacity for strategic goals

Countries are expanding domestic AI capabilities to design, train and deploy models on local infrastructure using local datasets and expertise. The goal is to tailor AI systems to national priorities, citizen needs, regulatory requirements, languages and cultural context while supporting innovation across sectors such as healthcare, transportation, communications, commerce and entertainment.

National AI strategies increasingly combine physical computing infrastructure with data infrastructure. AI factories, described as next-generation data centers for advanced accelerated computing, are emerging as core infrastructure for training and inference. Governments are pursuing different models, including state-linked AI clouds and shared public-private computing platforms, while also developing workforces, local ecosystems and foundation models governed under domestic laws.

Since 2019, NVIDIA’s AI Nations initiative has supported countries building AI ecosystems and workforce capacity. Examples include ThinkDeep agents in France that cut document search times from two days to two minutes, saved 2 million euros for 10,000 employees and reduced energy use. India’s Sarvam platform supports the country’s 22 official languages on domestic infrastructure, while Widelabs tools in Brazil are helping legal services reach more than 8 million citizens across nearly 500 municipalities.