Carbon emissions have been identified as a major cause of global warming and are harmful to the environment. Given the seriousness of climate changes, businesses are encouraged to adopt corporate strategies to improve environmental performance. Staggered boards (or classified boards) are one of the controversial corporate governance devices being employed by corporations that protect managers from the market for corporate control. This paper explores whether staggered boards can be a useful business strategy to improve carbon emissions. Relying on a novel data set in which the presence of a staggered board is identified through advanced machine learning algorithms and textual analysis, we find that staggered boards bring about significantly worse emission performance by 10.67%. Our results corroborate the premise that staggered boards insulate self‐interested managers from market discipline and thus exacerbate agency problems, resulting in more unfavorable outcomes. Further analysis validates the results, that is, propensity score matching, entropy balancing, instrumental‐variable analysis, and generalized method of moments (GMM) dynamic panel data estimation. Importantly, we include firm fixed effects to account for unobserved heterogeneity. Our findings indicate that de‐staggered boards may help improve emission performance.