The Window for Preventive Action Before AI Saturates Most Cognitive Benchmarks is Closing

This position paper argues that without coordinated intervention, AI systems will by default saturate most existing cognitive benchmarks by 2030, approaching or exceeding human expert performance across a broad range of measurable tasks. Using a joint hierarchical Bayesian model, we forecast frontier performance trajectories across 63 benchmarks spanning reasoning, mathematics, coding, scientific knowledge, and agentic capabilities. We find that nearly all current benchmarks (97% in our set, 80% CI: 95-100%) are on track to saturate within four years. This finding is robust to modeling choices: sensitivity analyses across 8 model variants and three saturation thresholds show that altering key assumptions yields qualitatively similar conclusions. Security-critical benchmarks (cybersecurity, autonomous AI R&D, biology, chemistry) show even faster trajectories, saturating before 2028. While benchmark saturation does not equate to artificial general intelligence, these findings add to a converging body of evidence indicating that superhuman performance on cognitive tasks is approaching faster than commonly assumed. Acknowledging that we neither understand nor control the behavior of current GPAI models, this timeline leaves limited runway before irreversible impacts. We outline implications for global governance and international coordination, AI safety research, and evaluation practices.