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Enterprises with lean IT budgets have little appetite for digitizing legacy data, which could slow AI adoption. So, bootstrapped startups, facing limited hardware, capital and talent, hope to make their workflows and processes AI-native from the start.
Even so, the lack of resources makes innovation and skills development difficult. Nvidia GPUs, for instance, are particularly scarce in Nepal and Sri Lanka and prohibitively expensive.
To work around the challenges, startups have turned to small language models (SLMs) and popular AI tools. “AI tools — which are powerful even at the free version — and open-source models have meant AI is truly democratized now,” Adhikary said.
