As artificial intelligence (AI) becomes increasingly embedded in educational systems, its potential to support more equitable and inclusive instructional practices demands closer scholarly attention. This presentation reports on a study examining how preservice mathematics teachers in a teacher preparation program utilized AI-driven tools to design culturally responsive, differentiated lessons for students from underserved communities.

Rooted in a design-based research framework, the study explores the integration of AI technologies in methods coursework to enhance preservice teachers’ capacity to address the learning needs of students from low-income and underrepresented backgrounds. Specifically, the study investigated how AI-supported platforms enabled participants to generate personalized mathematics lesson plans, receive formative insights about student engagement, and adapt instructional strategies in real time.

Data sources include participant-designed lesson plans, reflective journals, and structured interviews conducted over the course of one academic term. Qualitative analysis revealed three emergent themes: (1) AI facilitated more nuanced differentiation strategies, particularly for students with varied mathematical backgrounds; (2) participants reported increased awareness of equity-related considerations, including cultural relevance and representation; and (3) the use of AI prompted deeper reflection on student motivation and belonging—two constructs often underexplored in traditional lesson planning.

Findings suggest that AI tools, when embedded within critical pedagogical frameworks, can enhance preservice teachers’ instructional decision-making and support more inclusive learning environments. However, the research also identified challenges, including overreliance on algorithmic suggestions and varying degrees of digital literacy among participants. These findings underscore the need for structured scaffolding and pedagogical framing when integrating AI into teacher education contexts.

This presentation contributes to the broader discourse on technology-enhanced teacher preparation by demonstrating how AI can be leveraged not merely for efficiency, but for fostering equitable instructional design in mathematics education. The implications extend beyond the mathematics domain, offering insights for educator preparation programs seeking to promote justice-oriented pedagogy through the strategic use of emerging technologies.

The study aligns with global educational priorities related to digital transformation, inclusion, and innovation in teacher development. Attendees will gain evidence-based insights and practical considerations for responsibly incorporating AI into coursework and curriculum design.

Keywords: Artificial Intelligence in Education, Inclusive Mathematics Instruction, Teacher Preparation, Educational Technology, Equity in STEM, Preservice Teachers, Digital Pedagogy, Underserved Students, Culturally Responsive Teaching, Technology-Enhanced Learning.