["Journal of Behavioral Decision Making, Volume 39, Issue 3, July 2026. ", "\nABSTRACT\nOrganizations are increasingly using powerful AI aids to support decision‐making. Yet, performance improvements are difficult to predict, in part because employees vary in how they use them. We propose that such behavioral variation may stem from differences in how employees appraise these aids. Applying an opportunity–threat framework to AI augmentation (positing two primary cognitive AI appraisals—as either an opportunity or a threat to employees), we examine the effect of appraisal type on professionals' decision‐making when using powerful AI aids. Specifically, we examine the independent effort they invest in deliberate, vigilant information‐seeking during their initial decisions and their behavioral compliance with AI recommendations that diverged from their initial judgments during final decision‐making. Four simulation‐based experiments, in which we manipulated appraisal type and used the Wizard of Oz method to simulate recommendations from powerful AI aids, yielded consistent findings: Study 1, conducted among employees participating in a weight estimation simulation, revealed that opportunity (vs. threat) appraisals reduced participants' individual effort in making their initial decisions and increased their compliance with fictitious AI recommendations that contradicted their initial judgments in their final decisions. Studies 2–4, conducted among HR professionals and medical students engaged in realistic tasks within their work domains, further revealed that these effects of opportunity appraisals on decision‐making were driven by an increased preference for using the powerful AI aid rather than making decisions alone (an effect evident among those with higher domain experience; Studies 3–4). Our findings provide important implications for organizational decision‐making in hybrid human–AI environments.\n"]