<p>The study examines the development and impact of a futures-oriented teaching module designed to cultivate foresight and engagement with climate change action. The module follows a scaffolding framework that guides undergraduate students through exploring possible future scenarios, identifying their underlying factors and drivers, and envisioning the desirable, sustainable futures connected to their present lives. Building on an earlier version, the module integrates generative Artificial Intelligence (GenAI) to help students visualize and articulate these future scenarios. The study involved two groups: one using Image GenAI and the other using Text GenAI. Through a pre and posttest design (<i>N</i> = 58 and 62, respectively), we assessed changes in students’ perceptions of the future, hope, and self-perceived action competence regarding climate change. Data collection included a word association test and two Likert scales, supplemented by post-instructional reflections on futures-oriented learning and GenAI integration. Results showed that after instruction, both groups associated the future with more positive, sustainability-related words, and their sense of hope significantly increased. Both groups felt more aware of their role and the implications of climate change after exploring future possibilities. Significant improvement in self-perceived competence was observed in the Image Group. While students responded positively to using GenAI, they also recognized its limitations, an important outcome that contributed to their AI literacy. Understanding the limitations of GenAI is a key component of developing critical thinking around AI tools. These findings highlight the potential of integrating GenAI-supported futures thinking into education to empower students with the mindset and competencies needed to address complex global challenges.</p>