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The US Patent and Trademark Office (USPTO) should only grant protection to intellectual properties (IPs) that fulfill the nonobviousness requirement. However, despite being crucial in filtering out patents with dubious validity (ie, weak patents), little academic research is devoted to detecting the presence of patents with questionable nonobviousness (ie, obvious patents). I address this gap by proposing a framework to detect obvious patents by employing AI. I first validate that indeed AI-based indicator captured obvious patents through two face validity tests. Using this validated measure, I analyze the impact of a policy strengthening the enforcement of nonobviousness requirements (ie, KSR) on patent examination process efficiency. Given that backlogs and long pendency have been a long-standing issue in patent systems around the world, especially in USPTO, investigating this previously overlooked policy …