Kai-Fu Lee and Chen Qiufan gave themselves twenty years of runway and burned through most of it in five. That is the central problem with rereading *AI 2041* in 2026: the book's timeline was generous, its scenarios cautious, and the world was not. The hybrid structure — fiction by Chen, analysis by Lee — was designed to make AI legible to a general audience, pairing speculative stories set across the globe with explanatory essays grounding each one in technical plausibility. In 2021, this felt responsible. In 2026, it reads like a manual for things already happening, which is both a compliment and a limitation. Lee's prediction that deep learning would continue to dominate, that recommendation engines would reshape culture, that deepfakes would corrode trust — none of this required much prophetic courage even then, but the specificity of the scenarios has held up with uncomfortable accuracy. Insurance companies using AI to price human behavior, autonomous vehicles navigating ethical edge cases, AI-generated content flooding creative markets: these are not 2041 problems. They are Tuesday. Where the book genuinely anticipated our present is in its attention to the Global South as an AI battleground, not merely a recipient of Silicon Valley's exports. The stories set in Nigeria, India, and Sri Lanka gestured at a multipolar AI landscape that has, in fact, begun to materialize, even if the details differ.

The blind spots are instructive. Lee, for all his insider knowledge, operated within a framework that assumed AI development would remain roughly legible — that progress would be steep but continuous, that the major players would be identifiable corporations and nation-states, and that the primary risks would be economic displacement and privacy erosion. The book did not anticipate the sheer velocity of large language models, nor the strange cultural vertigo of a world where generative AI doesn't just automate tasks but produces passable art, legal briefs, and undergraduate essays. There is no story in *AI 2041* that quite captures the uncanny valley of conversing with a system that sounds like a person but isn't, because in 2021 that experience was still niche. The book also carries a quiet but persistent optimism about governance — a belief that regulation, while slow, would arrive in time to matter. Five years on, the regulatory landscape is a patchwork of half-measures and jurisdictional gaps, and the EU's AI Act, the most ambitious attempt, is already straining against the pace of deployment. Lee's faith in technocratic correction feels dated, not because it was wrong in principle, but because it underestimated the political entropy surrounding AI policy.