Google wanted Gemini to deepen its foothold in Indonesia’s student market but faced a system wired only for passing with assignment-first learning. Students prioritised fast, copyable outputs over exploration or comprehension, and this made their engagement with GenAI very surface-level.
Nation mapped students’ preferences, workflows, and friction points through quant surveys, diaries, immersions, and expert interviews to identify which use cases could deliver both immediate adoption and long-term business impact.
The work informed Gemini’s upcoming Exam Prep Model, under Flash 2.5, designed specifically for students. It reshapes Gemini from a “learning tool” into an immediate problem-solver, while planting the seeds for deeper learning over time. The way to deeper learning is to first reduce the effort to get there.
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