According to @godofprompt, an analysis of 2,847 AI safety papers published between 2020 and 2024 shows that 94% of these studies rely on the same six benchmarks for evaluation (source: https://x.com/godofprompt/status/2011366443221504185). This overreliance creates a narrow research focus and allows researchers to easily manipulate results, achieving 'state-of-the-art' scores with minimal code changes that do not actually improve AI safety. The findings highlight serious methodological flaws and widespread p-hacking in academic AI safety research, signaling urgent business opportunities for companies to develop robust, diverse, and truly effective AI safety evaluation tools and platforms. Companies addressing these gaps can position themselves as leaders in the fast-growing AI safety market.